<![CDATA[PhD Defense by Sarah Sundius]]> 27707 In partial fulfillment of the requirements for the degree of

 

Doctor of Philosophy in Quantitative Biosciences

in the School of Mathematics

Sarah Sundius

 

Will defend her dissertation
NOVEL COMPUTATIONAL MODELS FOR BACTERIAL DYNAMICS IN COMMUNITY AND TREATMENT CONTEXTS

 

Friday, December 8th, 2023

1:00pm

 

U.A. Whitaker Building, Room 1232

https://gatech.zoom.us/j/94862841926?pwd=S2JsWnFtcytieGNuaDhzeUJ6U3dVQT09

 

Thesis Advisors:

Dr. Rachel Kuske, School of Mathematics, Georgia Institute of Technology

Dr. Sam Brown, School of Biological Sciences, Georgia Institute of Technology

 

Committee Members:
Dr. Leonid Bunimovich, School of Mathematics, Georgia Institute of Technology

Dr. Sung Ha Kang, School of Mathematics, Georgia Institute of Technology

Dr. Marvin Whiteley, School of Biological Sciences, Georgia Institute of Technology

 

 

ABSTRACT. Microbes are key players in human health and disease; however, there is much debate over the nature, consequences, and importance of interactions between bacteria and their environments on the population scale. Interactions in bacterial communities and infection environments are complex and present challenges for modeling, measurement, and inference. However, rising interest in microbiomes (multi-species microbial communities), increasing antimicrobial resistance, and the quest for novel therapeutic strategies to combat human bacterial infection, all center around being able to answer common questions: how do bacteria grow and interact with each other and their environments on the population level? How do they respond to external perturbation from antibiotic exposure or bacteriophage? Using a range of mathematical approaches, we address these questions by integrating forward models and data-driven methods to assess the impacts of underlying mechanisms, abiotic and biotic perturbations, and spatio-temporal heterogeneity as they relate to microbial dynamics in human infections.

 

Throughout this dissertation, we employ mathematical modeling as a tool to bridge gaps between theoretical and empirical microbiology, highlighting that many standard models and inference methods fail to capture qualitative and quantitative features of microbial dynamics. First, we challenge the received wisdom that antibiotic resistance genes always worsen treatment outcomes and should be strictly minimized. We mathematically explore the effects of ecological interactions on antibiotic treatment in a two lineage system of a pathogen and commensal, proposing an optimization approach to antibiotic resistance management. We define conditions for competitive release and “beneficial” commensal resistance---namely, when commensals inhibit pathogens---and demonstrate generality to resource explicit and spatially extended models. These results are conserved in a four-species experimental community with phage, showing that the addition of phage, targeting the dominant competitor in the community, leads to extinction of the dominant species, competitive release of the next strongest competitor, and maintenance of community diversity. Next, we present an iterative approach for understanding antibiotic and inoculum effects on bacterial growth and yield. Using fine-scale experimental data and a menu of standard population models, we conclude that both growth rate and yield are modified by antibiotic exposure and that populations exhibit distinct regimes of dynamical behavior given distinct exposure conditions. Finally, we expand our modeling into two-dimensional space, building an agent-based simulation of bacterial cells and aggregates to explore physical and socio-microbiology mechanisms underlying relationships between bacterial growth rate and aggregate size.

 

This work has important implications for both theoretical and empirical studies of microbial systems---evaluating and informing methods for sampling, inference, and modeling to efficiently capture underlying complexities of interactions between bacteria and their environments. In the study of human infection, we provide a baseline toolkit to develop improved treatment strategies for acute and chronic infections and to increase predictability of treatment outcomes.

 

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<![CDATA[PhD Defense by Tong Zhou]]> 27707 Title: High-level Compiler Optimizations for Python Programs
Date: Thursday, December 7th
Time: 2 PM – 4 PM (ET)
Location: Klaus 3402
Virtual: https://gatech.zoom.us/my/tzhou80?pwd=b3EzUGRiWGY5Y2VkamZtdVJ2WTh5UT09

Tong Zhou
Ph.D. Candidate
School of Computer Science
Georgia Institute of Technology

Committee
Dr. Vivek Sarkar (Advisor) - School of Computer Science, Georgia Institute of Technology
Dr. Jun Shirako - School of Computer Science, Georgia Institute of Technology
Dr. Santosh Pande - School of Computer Science, Georgia Institute of Technology
Dr. Tushar Krishna - School of Electrical and Computer Engineering, Georgia Institute of Technology
Dr. Rich Vuduc - School of Computational Science and Engineering, Georgia Institute of Technology

Abstract:
As Python becomes the de facto high-level programming language for many data analytics and scientific computing domains, it becomes increasingly critical to build optimizing compilers that are able to generate efficient sequential and parallel code from Python programs to keep up with the insatiable demands for performance in these domains. Programs written in high-level languages like Python often make extensive use of arrays as a core data type, and mathematical functions applied on the arrays, in conjunction with general loops and element-level array accesses. Such a programming style poses both challenges and opportunities for optimizing compilers. We recognize that current compilers are limited in their ability to make effective use of the high-level operator and loop semantics to generate efficient code on modern parallel architectures.

This dissertation presents three pieces of work that demonstrate that compilers that leverage high-level operator and loop semantics can deliver improved performance for Python programs on CPUs and GPUs, relative to past work. On the CPU front, we present Intrepydd, a Python to C++ compiler that compiles a broad class of Python language constructs and NumPy array operators to sequential and parallel C++ code on CPUs. On the GPU front, we present APPy (Annotated Parallelism for Python), which enables users to parallelize generic Python loops and tensor expressions for execution on GPUs by simply adding compiler directives (annotations) to Python code. Then for programs consisting of sparse tensor operators, we introduce ReACT, which consists of a set of code generation techniques that achieve greater redundancy elimination than state-of-the-art.

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<![CDATA[PhD Defense by Chia-Wen Kuo]]> 27707 You are cordially invited to attend my dissertation defense on Wednesday, November 29th.

 

 

Chia-Wen Kuo

Robotics PhD Candidate

School of Electrical and Computer Engineering

Georgia Institute of Technology

 

Committee:

Dr. Zsolt Kira (Advisor) - School of Interactive Computing, Georgia Institute of Technology

Dr. Chao Zhang - School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Chunyuan Li - Principal Research Scientist, Microsoft Research

Dr. Judy Hoffman - School of Interactive Computing, Georgia Institute of Technology

Dr. Larry Heck - School of Electrical and Computer Engineering, Georgia Institute of Technology

 

Abstract:

The fusion of vision and language (VL) in artificial intelligence represents a crucial advancement in the creation of truly intelligent systems, echoing a fundamental aspect of human cognition: the ability to see and articulate the world. This integration has transformative potential across various sectors, notably enhancing human interaction with technology. However, developing effective VL models is challenging due to often incomplete or missing knowledge in both vision and language components. This limitation impacts the models' ability to accurately describe visual contents and answer complex, real-world questions. My research, presented in a series of three works, addresses these challenges. The first work, Xmodal-Ctx, introduces external knowledge into VL models to overcome their contextual limitations. The second, HAAV, expands this by integrating a diverse array of knowledge sources, enhancing the models' understanding of visual content. The final work, K-Aug, scales these concepts to larger, more complex multimodal models, addressing the integration and application of high-quality knowledge sources. This structured approach aims to bridge the knowledge gaps in VL models, thereby enhancing their overall interpretative and descriptive capabilities in a context-rich and linguistically coherent manner.

 

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<![CDATA[PhD Defense by Osman Emre Dai ]]> 27707 Name: Osman Emre Dai 

Title: Fundamental Limits and Algorithms for Database and Graph Alignment

Co-advisors:

    Dr. Negar Kiyavash, Business Analytics (Ecole Polytechnique Federale de Lausanne)

    Dr. Mohit Singht, School of Indsutrial and Systerms Engineering (Georgia Tech)

Committee Members:

    Dr. Daniel Cullina, School of Electrical Engineering and Computer Science (Pennsylvania State University)

    Dr. Cheng Mao, School of Mathematics (Georgia Tech)

    Dr. Ashwin Pananjady, Electrical Engineering and Computer Science (Georgia Tech)

Reader:

    Dr. Cheng Mao, School of Mathematics (Georgia Tech),

Time: Tuesday, December 5th at 1:00 PM

Location: ISyE Groseclose 226

Meeting Link (Zoom): https://gatech.zoom.us/j/91577958731

 

Abstract:
Data alignment refers to a class of problems where given two sets of anonymized  data pertaining  to overlapping sets of users, the goal is  to identify the correspondences between the two sets. If the data of a user is contained in both sets, the correlation between the two data points associated with the user might make it possible to determine that both belong to the same user and hence link the data points. Alignment problems are of practical interest in applications such as privacy and data junction. Data alignment can be used to de-anonymize data, therefore,  studying the feasibility of alignment allows for a more reliable understanding of the limitations of anonymization schemes put in place to protect against privacy breaches. Additionally, data alignment can aid in finding the correspondence between data from different sources, e.g. different sensors. The data fusion performed through data alignment in turn can help with variety of inference problems that arise in  scientific and engineering applications.

 

This thesis considers two types of data alignment problems: database and graph alignment. Database alignment refers to the setting where each feature (i.e. data points) in a data set is associated with a single user. Graph alignment refers to the setting where data points in each data set are associated with pairs of users. For both problems, we are particularly interested in the asymptotic case where n, the number of users with data in both sets, goes to infinity. Nevertheless our analyses often yield results applicable to the finite n case. To develop a preliminary understanding of the database alignment problem, we first study the closely related problem of planted matching with Gaussian weights of unit variance, and derive tight achievability bounds that match our converse bounds: Specifically we identify different inequalities between log n and the signal strength (which corresponds to the square of the difference between the mean weights of planted and non-planted edges) that guarantee upper bounds on the log of the expected number of errors. Then, we study the database alignment problem with Gaussian features in the low per-feature correlation setting where the number of dimensions of each feature scales as ω(log n):  We derive inequalities between log n and signal strength (which, for database alignment, corresponds to the mutual information between correlated features) that guarantee error bounds matching those of the planted matching setting, supporting the claimed connection between the two problems. Then, relaxing the restriction on the number of dimensions of features, we derive conditions on signal strength and dimensionality that guarantee smaller upper bounds on the log of the expected number of errors. The stronger results in the O(log n)-dimensional-feature setting for Gaussian databases show how planted matching, while useful, is not a perfect substitute to understand the dynamics of the more complex problem of database alignment. For graph alignment, we focus on the correlated Erdős–Rényi graph model where the data point (i.e. edge) associated with each pair of users in a graph is a Bernoulli random variable that is correlated with the data point associated with the same pair in the other graph. We study a canonical labeling algorithm for alignment and identify conditions on the density of the graphs and correlation between edges across graphs that guarantees the recovery of the true alignment with high probability.

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<![CDATA[PhD Defense by Jose Magalhaes]]> 27707 Title: Intelligent Data-Driven Aerodynamics Analysis and Optimization of Morphing Configurations

 

Date: Wednesday, November 29th, 2023

Time: 10:00 AM - 11:00 AM EST

Location: Montgomery Knight Building 317 - AE Department  (Physical)    

                  Microsoft Teams Meeting  (Virtual)

                  Meeting ID: 269 631 497 480 

                  Passcode: Pce4wA

 

 

 

Jose Magalhaes

Robotics PhD Candidate

School of Aerospace Engineering

Georgia Institute of Technology

 

Committee:

Dr. Kyriakos Vamvoudakis (Advisor) - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Seth Hutchinson - School of Interactive Computing, Georgia Institute of Technology

Dr. Daniel P. Schrage - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Lakshimi N. Sankar - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Gustavo L. O. Halila - Technology Development – EMBRAER S.A - Brazil

 

Abstract:

The aeronautical industry is continuously looking for more efficient aircraft and provide a reduction on fuel or power consumption while guaranteeing safety, optimality, and stability. The advances of composite materials enable building morphing structures that adapt to a variety of flight and environmental conditions. Airplanes that use morphing technologies can achieve optimal performance and minimize the drag over the entire flight envelope and operate even in dangerous weather conditions.

 

In this dissertation, we propose a data-driven framework to control morphing airfoils in the subsonic flight regime, considering high Reynolds numbers to reach, in efficient and safe way, a shape with improved values of the aerodynamic coefficients. The online solution is based on a data-driven controller combined with a surrogate model and a multi-gradient descent algorithm considering objective functions that are relevant in aerodynamics: increase lift-drag ratio, reduce drag and increase lift. Without full knowledge of the aerodynamic parameters (lift, drag, and pitching moment coefficients), the learning framework searches for an airfoil shape that minimizes a metric of performance associated to drag, lift, and pitching moment coefficients. The solution uses online data to improve the accuracy of the predictions of the aerodynamic coefficients provided by the surrogate model along the trajectory. The optimization framework focuses on subtle airfoil deformations to assure a smooth trajectory between the initial and the final shape. Finally, the efficacy and the robustness of our proposed solution is shown in numerical examples, resulting in a significant reduction in the prediction error.

 

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<![CDATA[PhD Proposal by David Martinez]]> 27707 Title: Image Guided High Precision Robotic Positioning in MRI for Medical Applications

Date: Tuesday, December 5th

Time: 10:00 am – 12:00 pm ET

Location (in-person): GTMI Auditorium

Location (remote): Click here to join the meeting

      Meeting ID: 239 038 384 563

      Passcode: 2BmTLv

 

Daniel Enrique Martinez

Robotics PhD Student

George W. Woodruff School of Mechanical Engineering

Georgia Institute of Technology

 

Committee:

Dr. Jun Ueda (Advisor)

Dr. Ai-Ping Hu

Dr. John Oshinski

Dr. F. Levent Degertekin

Dr. Yue Chen

 

Abstract:

Magnetic Resonance Imaging (MRI) is a powerful diagnostic tool that offers advanced visualization of human tissue, increasingly used to guide medical procedures such as biopsies and interventions. Nevertheless, navigation in the MRI environment remains challenging due to material, actuator, and sensor restrictions as well as scan time and cost of use. This work presents methods for ensuring high precision robotic positioning in MRI for use in emerging applications through three distinct aims. In the first aim, an MRI-analogous test bench implementing Position Sensitive Devices (PSDs) is established to measure the positioning performance of a previously developed MRI compatible robot, circumventing limitations of MRI resolution and scan time, validating the capability of MRI guided robot navigation methods. In the second aim, the validated high-precision navigation method is leveraged to enable the application of multi-image Super Resolution (SR) algorithms to construct enhanced resolution in-plane MRI slices, leading to improved positioning precision exceeding the limits of the native MRI resolution. In the third aim, mechanical characterization of a non-Newtonian fluid will be conducted through experimental modelling to compensate for resistive forces when the robot end-effector navigates through a complex fluid medium. Successful completion of this project will enable novel procedures in MRI requiring high positioning accuracy.

 

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<![CDATA[PhD Defense by Rachel Ringquist]]> 27707 Rachel Ringquist

BioE PhD Defense Presentation

Monday, December 4th at 8:30am

EBB CHOA room

https://gatech.zoom.us/j/99512704794

 

Advisor: Dr. Krishnendu Roy (Engineering, Vanderbilt) 

 

Committee: 

Dr. Ankur Singh (School of Mechanical Engineering, Georgia Tech)

Dr. Ahmet Coskun (School of Biomedical Engineering, Georgia Tech)

Dr. Hang Lu (School of Chemical and Biomolecular Engineering, Georgia Tech)

Dr. Rabin Tirouvanziam (Department of Pediatric Infectious Diseases, Emory)

 

An immune-competent microvascularized human lung-on-chip device for studying immunopathologies of the lung

 

      Severe influenza affects 3-5 million people worldwide each year, resulting in >300,000 deaths. Standard-of-care antiviral therapeutics have limited effectiveness in these patients where infection severity is driven by an aberrant immune response. In severe influenza, the hyperactive immune system causes acute cytokine storm, cytopenia, and local tissue damage. Current preclinical models of severe influenza, in small animal models and in vitro, fail to recapitulate the human immune response to severe viral infection accurately. Here, we bioengineered a human lung tissue model that represents small airway structures with tissue-resident and circulatory immune cells. The immune-competent lung tissue model comprises of a 3D, perfusable microvascular network underneath a mature, differentiated epithelium at an air-liquid interface.

      With this model, we demonstrate that a conventional lung-on-chip (LOC) that lacks immune cells induces limited cytokine response to severe influenza infection, and while a LOC with tissue-resident macrophages induces significant response in the airway, the presence of both tissue-resident and circulatory immune cells was necessary to elicit a significant airway and interstitial cytokine storm. We demonstrate through extensive microscopy, secretome, and single-cell RNA sequencing analyses that severe flu infection results in significant lymphopenia, extracellular matrix remodeling, and transcriptional shutdown in fully immune-competent lung tissues. Lastly, we highlight the prominent role of stromal-immune interactions in the response to severe influenza infection, with stromal cells participating in both cytokine signaling and ECM remodeling. The introduction of both tissue-resident and circulatory immune cells into this lung-on-chip model allows for investigation into the distinct role of each immune cell type in the initiation and progression of influenza and may shed light on potential therapeutic avenues targeting immune dysregulation.

 

 

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<![CDATA[PhD Defense by Tas Ahmed]]> 27707 Tas Ahmed
BME PhD Defense Presentation

Date: 2023-12-05
Time: 2:00 PM-4:00 PM
Location / Meeting Link: EBB CHOA

Committee Members:
Shuichi Takayama, PhD (Advisor) Blair K. Brettmann, PhD Felipe G. Quiroz, PhD Philip J. Santangelo, PhD Mark P. Styczynski, PhD


Title: Analysis of liquid-liquid phase separated systems for artificial cell applications

Abstract:
Protocells are promising tools for addressing clinical needs at the point of care, particularly when sample is minimal and technological capabilities are limited. Liquid-liquid phase separation of bioinert, low-cost and environmentally friendly polymers have previously been used to form protocells for this application, but underlying study of the specific polymers and the roles in which composition, interaction and enzymatic activity play are limited. In this thesis, we address this gap for two model protocells, a polyethylene glycol (PEG)-polysucrose (Ficoll) system and an adenosine triphosphate (ATP)-polydiallyldimethylammonium (PDDA) coacervate. We first address the shift in thermodynamics of PEG-Ficoll protocells that operate in a specialized cell-like buffer meant to facilitate transcription-translation reactions. This involves creation of a ternary phase diagram of the system through cloud point titration and tie line analysis, and further examination of interaction strengths and solvent quality as probed by fluorescence correlation spectroscopy (FCS) and theoretical analyses. The cell-like buffer lowers the threshold to phase separation, enacting binodal shifts through modulation of excluded volume in Ficoll. Partitioning of nucleic acids, essential to protocell function, are found to change phase preference in response to various protocell conditions, and the results are supported by atomic force microscopy imaging of DNA structural changes. We then shift to ATP:PDDA coacervates in order to study dynamics of a model diffusion-limited enzyme while compartmentalized compared to in bulk. Using FCS, diffusion of the enzyme dextranase is quantitated within coacervate droplets and is studied with respect to droplet viscosity and coacervate composition. Scaling changes in diffusion with respect to polymeric regime are found to be altered through catalysis and substrate inhibition. The work presented in this thesis sheds light on the fundamental variables that affect protocell operation, and the results suggest that engineering of polymer interactions through buffer selection, of protocell composition and of enzyme diffusivity could dramatically affect protocell success.

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<![CDATA[PhD Proposal by Arjun Majumdar]]> 27707 Title: Large-scale Offline Pre-training to Enable Embodied Intelligence

 

Arjun Majumdar

Ph.D. Student in Computer Science

School of Interactive Computing 

Georgia Institute of Technology

 

Date: November 29th, 2023

Time: 3:00pm - 5:00pm ET / 12:00pm - 2:00pm PT

Location: zoom link; Coda C1215 Midtown

Committee:

Dr. Dhruv Batra (Advisor) -- School of Interactive Computing, Georgia Institute of Technology

Dr. Zsolt Kira -- School of Interactive Computing, Georgia Institute of Technology

Dr. James Hays -- School of Interactive Computing, Georgia Institute of Technology

Dr. Jitendra Malik -- University of California Berkeley

Dr. Vincent Vanhoucke – Google DeepMind

Dr. Vladlen Koltun -- Apple

 

Abstract:

A central goal in Artificial Intelligence is building embodied agents (such as mobile robots) that are generalists -- capable of assisting with a wide-variety of tasks (specified in natural language) in any environment or setting. Such agents must understand a vast diversity of concepts in the visual world and be able to ground (or associate) this understanding with language to allow users to describe tasks and goals. How can we develop agents with such an extensive and functional understanding of the world?

 

In this thesis, we will argue that offline pre-training of foundation models on web-scale data enables embodied intelligence. In part 1, we present VC-1, a visual foundation model pre-trained (primarily) on video data collected from an egocentric perspective. We systematically demonstrate that such a model substantially benefits from increasing pre-training dataset diversity by introducing CortexBench, an embodied AI (EAI) benchmark curated from a diverse collection of existing EAI tasks (requiring locomotion, navigation, and dexterous and mobile manipulation of objects). In part 2, we first demonstrate that visual grounding learned from internet data (i.e., image-caption pairs from the web) can be transferred to an instruction-following visual navigation agent (VLN-BERT). Then, we present ZSON, a highly scalable approach for learning to visually navigate to objects specified in open-vocabulary, natural language instructions such as “find the kitchen sink.” The key idea is to leverage a pre-trained visiolinguistic embedding space (from CLIP) to decouple learning to represent semantic goals (such as a “a kitchen sink”) from learning to navigate to semantic goals. Finally, in proposed work, we will study combining vision-and-language models (VLMs) with large language models (LLMs) for the task of embodied question-answering (EQA), which requires an agent to answer open-ended questions about real-world environments.

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<![CDATA[PhD Defense by Qinsheng Zhang]]> 27707 Title: Learning, sampling and inference with stochastic differential equations

Date: Thursday, Nov 30 2023

Time: 13:30 PM – 15:30 PM EST

Location: Coda C1115 Druid Hills

 

 

Qinsheng Zhang

qsh-zh.github.io

Robotics Ph.D. Student

Georgia Institute of Technology

 

Committee:

Dr. Yongxin Chen (Advisor) – School of Aerospace Engineering, Georgia Institute of Technology

Dr. Humphrey Shi – School of Interactive Computing, Georgia Institute of Technology

Dr. Zsolt Kira – School of Interactive Computing, Georgia Institute of Technology

Dr. Danfei Xu – School of Interactive Computing, Georgia Institute of Technology

Dr. Molei Tao –  School of Mathematics, Georgia Institute of Technology

 

 

Abstract:

Stochastic differential equations (SDEs) constitute a formidable tool for modeling the dynamics of continuous-time stochastic processes and offer a natural framework for the probabilistic modeling of high-dimensional data. Consequently, they have garnered increasing attention in generative machine learning. Despite their promise, the applications of SDEs in machine learning have been limited due to the lack of scalable learning approaches that can train flexible neural networks to approximate stochastic processes, and the difficulty of conducting tractable inference and sampling caused by inefficient SDE solvers. In this work, I outline my efforts to develop novel computational models capable of efficient and scalable learning, sampling, and inference from SDEs. Specifically, I introduce several approaches to learning SDEs for probabilistic modeling, including fitting non-linear forward and backward SDEs with neural networks and learning with limited data. Next, I present a novel deep model designed to learn SDE dynamics while satisfying given constraints on the marginal probability of the SDE. Furthermore, I developed an efficient algorithm for drawing samples from high-dimensional SDEs, which proves effective in generating. This thesis represents an advancement in scalable neural Stochastic Differential Equations (SDEs), extending their applicability to a range of high-dimensional probabilistic modeling tasks, including building large-scale text-to-image / text-to-3d generative models.

]]> Tatianna Richardson 1 1701118755 2023-11-27 20:59:15 1701118755 2023-11-27 20:59:15 0 0 event Learning, sampling and inference with stochastic differential equations

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<![CDATA[PhD Proposal by Jaewon Lee]]> 27707 Title: HW-SW Co-Design to mitigate GPU Memory Safety Vulnerability and Power Side-Channel Attack

 

Date: Tuesday, November 28, 2023

Time: 3:30 PM - 5:30 PM ET

Location:

      In-Person: KACB 1315

      Virtual: Click here to join the meeting

 

Jaewon Lee

Ph.D. Student

School of Computer Science

College of Computing

Georgia Institute of Technology

 

Committee:

Dr. Hyesoon Kim (advisor), School of Computer Science, Georgia Institute of Technology

Dr. Moinuddin Qureshi, School of Computer Science, Georgia Institute of Technology

Dr. Tushar Krishna, School of Electrical and Computer Engineering & School of Computer Science, Georgia Institute of Technology

 

Abstract

Graphic Processing Units (GPUs) had been considered acceptable even if they were insecure; however, the surge in the usage of Artificial Intelligence (AI) applications now involves GPUs in critical life and financial decision-making. Recent studies successfully demonstrate that attackers can induce failures in AI models by exploiting vulnerabilities in GPU memory.

We propose GPUShield, an efficient GPU memory bounds checking scheme that utilizes the characteristics of GPU programs. GPUShield minimizes metadata access by leveraging GPU's region-based memory access, metadata caching, and memory coalescing.

Additionally, we introduce our ongoing work, BNPL, a practical fine-grain GPU memory safety scheme. We implement efficient all-time bounds checking with pointer alignment so that we can eliminate the need to access metadata bounds in memory, thanks to GPU characteristics.

Finally, we address another type of threat: power side-channel attacks, and propose mitigation with a frequency binning strategy.

 

 

]]> Tatianna Richardson 1 1701118429 2023-11-27 20:53:49 1701118429 2023-11-27 20:53:49 0 0 event  HW-SW Co-Design to mitigate GPU Memory Safety Vulnerability and Power Side-Channel Attack

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<![CDATA[PhD Defense by Chia-Wen Kuo]]> 27707 You are cordially invited to attend my dissertation defense on Wednesday, November 29th.

 

 

Chia-Wen Kuo

Robotics PhD Candidate

School of Electrical and Computer Engineering

Georgia Institute of Technology

 

Committee:

Dr. Zsolt Kira (Advisor) - School of Interactive Computing, Georgia Institute of Technology

Dr. Chao Zhang - School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Chunyuan Li - Principal Research Scientist, Microsoft Research

Dr. Judy Hoffman - School of Interactive Computing, Georgia Institute of Technology

Dr. Larry Heck - School of Electrical and Computer Engineering, Georgia Institute of Technology

 

Abstract:

The fusion of vision and language (VL) in artificial intelligence represents a crucial advancement in the creation of truly intelligent systems, echoing a fundamental aspect of human cognition: the ability to see and articulate the world. This integration has transformative potential across various sectors, notably enhancing human interaction with technology. However, developing effective VL models is challenging due to often incomplete or missing knowledge in both vision and language components. This limitation impacts the models' ability to accurately describe visual contents and answer complex, real-world questions. My research, presented in a series of three works, addresses these challenges. The first work, Xmodal-Ctx, introduces external knowledge into VL models to overcome their contextual limitations. The second, HAAV, expands this by integrating a diverse array of knowledge sources, enhancing the models' understanding of visual content. The final work, K-Aug, scales these concepts to larger, more complex multimodal models, addressing the integration and application of high-quality knowledge sources. This structured approach aims to bridge the knowledge gaps in VL models, thereby enhancing their overall interpretative and descriptive capabilities in a context-rich and linguistically coherent manner.

]]> Tatianna Richardson 1 1701118310 2023-11-27 20:51:50 1701118310 2023-11-27 20:51:50 0 0 event Knowledge-Augmented Vision-and-Language Assistant

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<![CDATA[Equity in Graduate Education Fall 2023 Discussion Series: Integrating Diversity and Inclusion Considerations Into Your Rubric ]]> 36363 This month's EGE Discussion series is entitled " Integrating Diversity and Inclusion Considerations Into Your Rubric". 

Optional pre-read: Redefining merit through new routines: Holistic admissions policy implementation in graduate education by Julie Posselt, Deborah Southern, Theresa Hernandez, Steve Desir, Fatima Alleyne, and Casey Miller

This "community jam session" is intended to create space for brainstorming and sharing ways to elicit applicants' lived experiences and potential to contribute to your mission-driven pursuit of diversity and inclusion. 

Each session begins with a brief presentation of principles and/or research evidence about equitable, lawful use of these tools. Followed by a 30-40-minute breakout session where attendees can brainstorm with colleagues from around the country. Breakout rooms will be by discipline, recognizing that there are field-specific ways that programs engage with applicants. Finally, the sessions end with a 15-20 minute discussion in a large-group format, led by members of the EGE leadership team and steering committee.

To register, please visit https://usc.zoom.us/meeting/register/tJUodOuvpzsvEtzb_OlJsZ90FuSsz-5jvOb-#/registration

]]> Brittani Hill 1 1695314365 2023-09-21 16:39:25 1701118246 2023-11-27 20:50:46 0 0 event      

 

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2023-10-18T15:00:00-04:00 2023-10-18T16:30:00-04:00 2023-10-18T16:30:00-04:00 2023-10-18 19:00:00 2023-10-18 20:30:00 2023-10-18 20:30:00 2023-10-18T15:00:00-04:00 2023-10-18T16:30:00-04:00 America/New_York America/New_York datetime 2023-10-18 03:00:00 2023-10-18 04:30:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> 671784 671784 image <![CDATA[EGE-LOGO-1024x1024.png]]> image/png 1695317614 2023-09-21 17:33:34 1695317614 2023-09-21 17:33:34 <![CDATA[Equity in Graduate Education Consortium at Georgia Tech ]]>
<![CDATA[Introduction to Equity-Minded Mentoring (Virtual) Workshop ]]> 36363 Georgia Tech is now an institutional member in the Equity in Graduate Education Consortium. As a member, participants within the have access to activities and workshop series that reimagine, refine, and institutionalize more equitable practices.

In this workshop, facilitated by Dr. Annie Woffard and Dr. Steve Desir, faculty will reflect on their current advising and mentoring practice and learn how to develop equity-minded mentoring relationships. Activities in this workshop will develop competencies in these areas and will help faculty develop equity-minded mentoring agreements as a tool that establishes shared expectations between mentors and mentees. 

This is the first workshop in its three-part series and is open to anyone within the Georgia Tech Community. 

]]> Brittani Hill 1 1665581898 2022-10-12 13:38:18 1701118217 2023-11-27 20:50:17 0 0 event In this workshop, faculty will reflect on their current advising and mentoring practice and learn how to develop equity-minded mentoring relationships.

This workshop will be facilitated by Dr. Annie Woffard, Assistant Professor of Higher Education in the Department of Educational Leadership & Policy Studies at Florida State University, and Dr. Steve Desir, a doctoral student in the Educational Leadership Program at the USC Rossier School of Education.   

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2022-10-25T12:00:00-04:00 2022-10-25T14:00:00-04:00 2022-10-25T14:00:00-04:00 2022-10-25 16:00:00 2022-10-25 18:00:00 2022-10-25 18:00:00 2022-10-25T12:00:00-04:00 2022-10-25T14:00:00-04:00 America/New_York America/New_York datetime 2022-10-25 12:00:00 2022-10-25 02:00:00 America/New_York America/New_York datetime <![CDATA[Register to Attend]]> For more information, please contact EGE liaison, Bonnie Ferri at bonnie.ferri@gatech.edu, or Consortium Manager, Stephen Ruffin, at stephen.ruffin@pe.gatech.edu. 

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662069 662069 image <![CDATA[Equity in Graduate Education Logo]]> image/png 1665669245 2022-10-13 13:54:05 1665669245 2022-10-13 13:54:05 <![CDATA[Equity in Graduate Education Resource Center]]>
<![CDATA[PhD Proposal by Anh Thai (Ngoc Anh Thai)]]> 27707 Title: Low-shot Object Learning with Mutual Exclusivity Bias

Date: Friday, December 1, 2023

Time: 10:30AM-12:00PM ET

In-person Location: Coda C1205 Five Points

Zoom link: https://gatech.zoom.us/j/97091549311

 

Anh Thai

PhD Student in Computer Science

School of Interactive Computing

College of Computing

Georgia Institute of Technology

 

Committee

Dr. James M. Rehg (advisor), College of Computing, Georgia Institute of Technology; Department of Computer Science and Industrial and Enterprise Systems Engineering, University of Illinois Urbana-Champaign

Dr. Judy Hoffman, College of Computing, Georgia Institute of Technology

Dr. James Hays, College of Computing, Georgia Institute of Technology

Dr. Michael C. Frank, Department of Psychology, Stanford University

Dr. Jia-Bin Huang, Department of Computer Science, University of Maryland, College Park

 

Summary

 

Despite rapid development of machine learning techniques that can generalize beyond the distribution of the training data, these models are still far behind the learning pace of young children. In this proposal, we leverage insights from developmental psychology regarding children's learning environment and strategies to apply to machine algorithms. To achieve this goal, we focus on two aspects of children's word and object learning: 3D information and mutual exclusivity bias. We conduct studies on the generalization ability of 3D reconstruction models, identifying key factors that affect this capability. Extending our exploration, we demonstrate that 2D feature representations with strong semantic correspondence matching ability can be effectively employed for 3D object part segmentation. Additionally, we introduce a novel paradigm for low-shot learning, requiring computational models to leverage mutual exclusivity bias to resolve ambiguity in learning signals. Our main goal is to develop a part-based self-supervised learning model that aggregates 3D information from multiple viewpoints. We plan to show that this approach can be applied to address the challenges of low-shot object learning with mutual exclusivity bias setting.

]]> Tatianna Richardson 1 1701118191 2023-11-27 20:49:51 1701118191 2023-11-27 20:49:51 0 0 event Low-shot Object Learning with Mutual Exclusivity Bias

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<![CDATA[PhD Defense by Chen Liang]]> 27707 Title: On Parameter Efficiency of Neural Language Models

 

Date: Nov 27th, 2023

Time:  11am - 1pm ET

Location: Groseclose 226 or https://gatech.zoom.us/j/97505299826

 

Chen Liang

Machine Learning PhD Student

H. Milton Stewart School of Industrial and Systems Engineering

Georgia Institute of Technology

 

Committee

Dr. Tuo Zhao, School of Industrial and Systems Engineering, Georgia Institute of Technology (Advisor)

Dr. Chao Zhang, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Diyi Yang, Computer Science Department, Stanford University

Dr. Aditya Prakash, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Yingyan (Celine) Lin, School of Computer Science, Georgia Institute of Technology

 

Abstract

Pre-trained neural language models have achieved remarkable capabilities across various natural language understanding and generation tasks. However, the trend of scaling these models to encompass billions of parameters, while enhancing adaptability and emergent capabilities, has brought forth significant deployment challenges. These challenges include constraints in model storage and inference latency for real-world deployment, intensive time and computational costs for task adaptation, and the presence of substantial redundant parameters that affect task adaptability. Inspired by these challenges, this talk will cover methods we have developed to enhance the parameter efficiency of these models, seeking to minimize storage requirements, accelerate inference and adaptation, and enhance generalizability. The content of the talk is organized as follows:

 

In the first section, we investigate the largely unexplored relationship between parameter redundancy and model generalizability. Observing that removing redundant parameters improves generalizability, we propose an adaptive optimization algorithm for fine-tuning to improve the utilization of the redundant parameters. Experimental results validate increased generalization across various downstream tasks.

 

In the second section, we propose model compression strategies, such as weight pruning and knowledge distillation, aiming at reducing model storage and accelerating inference. We first developed a reliable iterative pruning method that accounts for uncertainties in training dynamics. Then, we dive into the realm of knowledge distillation, addressing the large teacher-student ``knowledge gap" that often hampers the student's performance. To tackle this, we offer solutions for producing students for specific tasks by selectively distilling task-relevant knowledge. In scenarios demanding student adaptability across diverse tasks, we propose to reduce the knowledge gap by combining iterative pruning with distillation. Our approaches significantly surpass conventional distillation methods at similar compression ratios.

 

In the last section, we explore cost-effective task adaptation alternatives to expensive fine-tuning. We specifically focus on the hypernetwork approach, which uses an auxiliary hypernetwork to rapidly generate task-specific weights from few-shot demonstrations. We enhance the sample efficiency of the generation process by leveraging weight structure as an inductive bias, yielding superior performance on unseen tasks compared to existing methods.

]]> Tatianna Richardson 1 1701117960 2023-11-27 20:46:00 1701117960 2023-11-27 20:46:00 0 0 event On Parameter Efficiency of Neural Language Models

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<![CDATA[PhD Proposal by  Chrysoula Lydia Pastra]]> 27707  Chrysoula Lydia Pastra

(Advisor: Prof. Dimitri Mavris)

will propose a doctoral thesis entitled,

Methodology formulation for multi-energy sustainable turboprop regional aircraft sizing with airport infrastructure capability constraints

 On

 Friday, December 1st at 11:00 a.m. EST

Online: Click here to join the meeting,

Collaborative Design Environment (CoDE), 

Weber Space Science and Technology Building (SST II) 

 Abstract

 With climate change being a more prominent issue in our society, every industry is moving towards more sustainable solutions. The aviation industry has set forth certain goals that it needs to reach to reduce if not eliminate harmful emissions. The aviation industry has been focused on exploring the feasibility and viability of different technological solutions to minimize greenhouse gas emissions, with electrification and hydrogen usage being at the epicenter. Infrastructure and regulation changes are two missing pieces of the puzzle. Technology, infrastructure, and regulations are three pillars that need to be considered simultaneously to accurately evaluate the feasibility of shifting towards a net zero aviation reality in the future. All of these pillars are crucial aspects, and without one, the shift cannot occur.

Current state-of-the-art research focuses on technological solutions and their feasibility. Technological solutions such as hybrid electric aircraft, fully electric aircraft, hydrogen-powered aircraft, and sustainable aviation fuels are all evaluated. Researchers perform sizing and synthesis analysis for the new propulsive methods to evaluate the effects on Green House Gases by applying mission and performance constraints, while the infrastructure aspect is evaluated separately. Analysis of what will be required to support the new generation green aircraft is performed such as charging stations, hydrogen hydrants and pipelines, and charging schedule optimizations. The major identified gap in the literature and current research is that the infrastructure needs are not considered as constraints in aircraft sizing and synthesis research. Infrastructure poses a major obstacle to overcome in the transition towards a green aviation reality. Similarly, regulations and incentives have been previously identified but they have not been evaluated in conjunction with infrastructure and design. Additionally, with the variety of technological solutions available, there is an inherent uncertainty on which path different stakeholders will follow, causing further stagnation in infrastructure development. Using the automotive industry as a thought experiment, this thesis will explore these identified gaps.

The methodology that is proposed within this thesis stems from the realization that these technologies that have been proposed and evaluated in previous research cannot be implemented unless there is a drastic change in infrastructure or infrastructure and technologies are considered as two pieces of the same puzzle and evaluated together. This thesis will be composed of three experiments that will tie together the technology and infrastructure, and in the future can be expanded to also include the third pillar: regulations. The first aspect of this thesis tackles the lack of research that is done on multi-energy source regional aircraft. Although there has been research done on smaller aircraft and UAVs using both hydrogen fuel cells, and batteries for an energy-sharing topology, detailed trades and sizing evaluations have been lacking. The first experiment aims to show that an energy-sharing aircraft can provide significantly higher fuel savings than either a purely hybrid electric or hybrid hydrogen fuel cell-powered aircraft. The second experiment will be directly using the optimized multi-energy source aircraft to explore the fleet level impact within the US regional routes and compare those to the purely electric or hydrogen-powered aircraft, and evaluating the fleet level energy requirements that would be necessary to support such a multi-energy source solution. Finally, where the new methodology comes into place is the third experiment. Within this experiment, the optimized aircraft that was sized with traditional sizing and synthesis methods will be evaluated with infrastructure and operational constraints. The new design space will then be evaluated, and different scenarios will be performed to identify how the infrastructure and operational constraints need to be changed in

order to allow for the shift towards greener new-generation aircraft. This new design space will allow for constrained optimization and will generate a new optimized aircraft design which is hypothesized to be significantly different than the aircraft produced in experiment 1. This methodology will allow future researchers to evaluate new types of technologies in a more holistic way as the current state of the market can also be considered within the sizing and optimization of the aircraft.

 Committee

]]> Tatianna Richardson 1 1701117641 2023-11-27 20:40:41 1701117641 2023-11-27 20:40:41 0 0 event Methodology formulation for multi-energy sustainable turboprop regional aircraft sizing with airport infrastructure capability constraints

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<![CDATA[PhD Defense by Bryan Wang]]> 27707  

Bryan Wang

BioE PhD Defense Presentation

Monday, December 4th at 2 p.m.

EBB CHOA room

https://gatech.zoom.us/j/91298864526

 

 

 

Advisor: Krishnendu Roy, PhD – School of Biomedical Engineering, GT

 

Committee:

Stephen Balakirsky, PhD – Georgia Tech Research Institute

Fani Bukouvala, PhD – School of Chemical and Biomolecular Engineering, GT

Johnna Temenoff, PhD – School of Biomedical Engineering, GT

Carolyn Yeago, PhD – Institute of Bioengineering and Bioscience, GT

 

 

 

 

Process Development and Process Analytical Technology Integration for Cell Therapy Manufacturing

 

Biomanufacturing of cell therapies involves highly complex and labor-intensive processes, where the process parameters and biological variabilities can significantly influence product quality, reproducibility, and therapeutic efficacy of the products. The complexity and largely manual unit operations contribute to product variability and high cost. To address these manufacturing challenges, we designed a digital-twin-enabled closed-loop cell manufacturing platform with automation and feedback controls. This platform integrates process analytical technologies (PAT) to enable deeper process understanding and provide real-time control of process variables. Specifically, we designed bench-scale bioreactors with automated sampling, at-line and in-line monitoring, digital twin-enabled media nutrients estimation, and feedback-controlled feeding capabilities. Human umbilical cord tissue-derived MSCs (CT-MSCs) and T cells were used as the example cell therapy product. At-line glucose and lactate monitoring confirmed the accuracy of the digital twin estimations. Spent media samples and detailed functional characterizations of the MSCs and T cells end-products generated from the automation-controlled bioreactor demonstrated that high expansion and functions of the MSCs and T cells were maintained in these closed-loop bioreactors. Real-time imaging with quantitative oblique back illumination microscopy showed high-resolution images of cells in-process in a dynamic 3D environment. Overall, the digital twin-enabled bioreactor platform reduced costs, labor, time, and, more importantly, perturbations; and could improve yield while maintaining the phenotype and quality of cell therapy products. Our integrated automation system provides a blueprint for multiplexed PAT integration, process optimization, feedback-controlled intelligent automation to enable the discovery, monitoring, and control of critical quality attributes and critical process parameters for cell therapy manufacturing.

 

]]> Tatianna Richardson 1 1701117451 2023-11-27 20:37:31 1701117451 2023-11-27 20:37:31 0 0 event Process Development and Process Analytical Technology Integration for Cell Therapy Manufacturing

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<![CDATA[PhD Proposal by Viswanath Gorti]]> 27707 Viswanath Gorti

BME PhD Proposal Presentation

Date: 2023-12-06
Time: 9:30-11:30 AM
Location / Meeting Link: EBB CHOA Seminar Room [https://gatech.zoom.us/j/95856862674]

Committee Members:
Francisco E. Robles, PhD (Advisor); Shu Jia, PhD; Erin Buckley, PhD; Wilbur Lam, MD/PhD; Waitman Aumann, MD


Title: Deep-ultraviolet microscopy for point-of-care diagnostics and cell characterization

Abstract:
Deep-Ultraviolet (UV) microscopy enables high-resolution, label-free molecular imaging by leveraging unique absorption properties of biomolecules in the UV region of the spectrum (~200-400 nm). The use of UV light in microscopy has been historically limited, but recent advances in UV light sources and detectors have resulted in the re-emergence of the optical technique with various live-cell imaging applications, including quantitative biomolecular mass-mapping, hematological analysis, and histopathology. This proposal aims to expand the capabilities of UV microscopy for biomedical applications. We first advance UV microscopy for point-of-care diagnostic applications by developing compact, low-cost UV systems capable of fast molecular imaging. We demonstrate these systems for rapid hematology analysis and evaluation of bone marrow aspirate samples. We then leverage multispectral and multiscale capabilities of existing UV microscopes to interrogate cellular samples and further our understanding of biological phenomena. We apply these findings to subtype lymphocytes with high accuracy and phenotype cancer cell populations. Finally, we propose an epi-mode UV microscope for label-free, tomographic imaging of thick samples, which would not only address limitations of previous transmission-mode systems but enable vast diagnostic applications.

]]> Tatianna Richardson 1 1701116924 2023-11-27 20:28:44 1701116924 2023-11-27 20:28:44 0 0 event Deep-ultraviolet microscopy for point-of-care diagnostics and cell characterization

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<![CDATA[PhD Proposal by Daniel Nkemelu]]> 27707 Title: Tackling Online Threats to Democracy in High-Stakes Low-Resource Contexts

 

Date: November 28th, 2023

Time: 10:00 AM - 12:00 PM EST

Location: Hybrid

In-person: CODA C1015 Vinings

Virtual: Join Zoom meeting 

https://gatech.zoom.us/j/98346182572?pwd=UG9wemsyZWRGTGVLd2V2VmNyaUNxUT09

 

 

Daniel K. Nkemelu

Ph.D. student in Human-Centered Computing

School of Interactive Computing

Georgia Institute of Technology

 

Committee:

Dr. Michael L. Best (co-advisor) – School of Interactive Computing and Sam Nunn School of International Affairs, Georgia Institute of Technology

Dr. Irfan Essa (co-advisor) – School of Interactive Computing, Georgia Institute of Technology

Dr. Ellen Zegura – School of Computer Science, Georgia Institute of Technology

Dr. Munmun De Choudhury – School of Interactive Computing, Georgia Institute of Technology

Dr. Neha Kumar – School of Interactive Computing and Sam Nunn School of International Affairs, Georgia Institute of Technology

Dr. Monojit Choudhury - Turing India, Microsoft

 

Abstract

The rapid adoption of social media around the world has been accompanied by a surge in the dissemination of problematic content such as hate speech, disinformation, and misinformation. Social media platforms and regulators have historically overlooked the potentially devastating effects of these contents in non-Western contexts. Consequently, the burden of preserving online integrity falls on civil society actors who are often overworked, under-resourced, and underappreciated. With the relative success of machine learning applications in research and practice, there is an urgent need to understand how these technologies can support civil society organizations working to tackle these problems and build safer, more resilient democratic societies.

 

My dissertation focuses on two types of civil society actors: social media monitors and fact-checkers. Using a mixed-method approach, my research investigates how machine learning can effectively support these stakeholders' efforts to track and respond to hate speech, disinformation, and misinformation in low-resource contexts. In my completed work, I have partnered with social media monitors in Myanmar to source and label data, and train and deploy machine learning models to support hate speech monitoring during the 2020 Myanmar elections. I have drawn on lessons from this work to develop a contextual entity substitution method for hate speech data augmentation in limited data contexts. 

 

In my proposed work, I seek to center the perspectives of fact-checkers working to address online misinformation and disinformation. My research aims to understand their current strategies and tools for creating and disseminating fact-checked content, how users respond to published fact-checked content, and how the development of an AI-driven tool for making fact-checks accessible can reduce the burden and amplify the impact of their work. This dissertation will advance our understanding of online threats to democracy in the Global South and provide insights that improve the capacities of stakeholders to respond to these challenges.

 

Thank you,

Daniel Nkemelu

 

 

 

Daniel Nkemelu | dnkemelu@gatech.edu

PhD Student,

School of Interactive Computing,

Georgia Institute of Technology

 

From: Nkemelu, Daniel K <dnkemelu@gatech.edu>
Sent: Friday, November 24, 2023 3:18 PM
To: phd-coc-announce@cc.gatech.edu <phd-coc-announce@cc.gatech.edu>; faculty@cc.gatech.edu <faculty@cc.gatech.edu>; announcements@grad.gatech.edu <announcements@grad.gatech.edu>
Cc: Best, Michael <mikeb@gatech.edu>; Essa, Irfan A <irfan@gatech.edu>; Zegura, Ellen <ewz@cc.gatech.edu>; De Choudhury, Munmun <munmun.choudhury@cc.gatech.edu>; Kumar, Neha <neha.kumar@gatech.edu>; Monojit Choudhury <monojitc@microsoft.com>; Nash, Theresa L <tnash33@gatech.edu>
Subject: PhD Thesis Proposal Announcement

 

Dear all,

 

You are cordially invited to my thesis proposal on Tuesday, November 28th. 

 

Title: Tackling Online Threats to Democracy in High-Stakes Low-Resource Contexts

 

Date: November 28th, 2023

Time: 10:00 AM - 12:00 PM EST

Location: Hybrid

In-person: CODA C1015 Vinings

Virtual: Join Zoom meeting 

https://gatech.zoom.us/j/98346182572?pwd=UG9wemsyZWRGTGVLd2V2VmNyaUNxUT09

 

 

Daniel K. Nkemelu

Ph.D. student in Human-Centered Computing

School of Interactive Computing

Georgia Institute of Technology

 

Committee:

Dr. Michael L. Best (co-advisor) – School of Interactive Computing and Sam Nunn School of International Affairs, Georgia Institute of Technology

Dr. Irfan Essa (co-advisor) – School of Interactive Computing, Georgia Institute of Technology

Dr. Ellen Zegura – School of Computer Science, Georgia Institute of Technology

Dr. Munmun De Choudhury – School of Interactive Computing, Georgia Institute of Technology

Dr. Neha Kumar – School of Interactive Computing and Sam Nunn School of International Affairs, Georgia Institute of Technology

Dr. Monojit Choudhury - Turing India, Microsoft

 

Abstract

The rapid adoption of social media around the world has been accompanied by a surge in the dissemination of problematic content such as hate speech, disinformation, and misinformation. Social media platforms and regulators have historically overlooked the potentially devastating effects of these contents in non-Western contexts. Consequently, the burden of preserving online integrity falls on civil society actors who are often overworked, under-resourced, and underappreciated. With the relative success of machine learning applications in research and practice, there is an urgent need to understand how these technologies can support civil society organizations working to tackle these problems and build safer, more resilient democratic societies.

 

My dissertation focuses on two types of civil society actors: social media monitors and fact-checkers. Using a mixed-method approach, my research investigates how machine learning can effectively support these stakeholders' efforts to track and respond to hate speech, disinformation, and misinformation in low-resource contexts. In my completed work, I have partnered with social media monitors in Myanmar to source and label data, and train and deploy machine learning models to support hate speech monitoring during the 2020 Myanmar elections. I have drawn on lessons from this work to develop a contextual entity substitution method for hate speech data augmentation in limited data contexts. 

 

In my proposed work, I seek to center the perspectives of fact-checkers working to address online misinformation and disinformation. My research aims to understand their current strategies and tools for creating and disseminating fact-checked content, how users respond to published fact-checked content, and how the development of an AI-driven tool for making fact-checks accessible can reduce the burden and amplify the impact of their work. This dissertation will advance our understanding of online threats to democracy in the Global South and provide insights that improve the capacities of stakeholders to respond to these challenges.

]]> Tatianna Richardson 1 1701116571 2023-11-27 20:22:51 1701116571 2023-11-27 20:22:51 0 0 event Tackling Online Threats to Democracy in High-Stakes Low-Resource Contexts

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<![CDATA[PhD Defense by Annie Wang]]> 27707 Annie Wang

(Advisor: Dr. Robert Speyer)


will defend her doctoral thesis entitled,

 

Sintering Methodologies For Silicon Carbide Ceramics


On

Thursday, November 30th at 11:00 a.m.

Love 295

Committee

 

 

 

Abstract

 

Silicon carbide (SiC) ceramics are known for their high hardness, light weight, high strength, high oxidation resistance, high thermal shock resistance, low elevated temperature creep, and chemical inertness. Sintering of powder compacts has been via both eutectic liquid-phase and solid-state processes; both were investigated in this study.   

  

Solid-state sintering, following the method of Prochazka, requires both carbon and boron (or B4C) sintering aids.  In this work the use of C additives alone was shown to be necessary but insufficient for sintering.  The mechanical properties of SiC with varying B4C and C were studied with results of 98.31 to 99.66% relative density,  22.76 to 27.66 GPa for Vickers hardness and 3.0 to 4.18 MPam1/2 for Vickers indentation fracture toughness. The work showed that the merits of increasing B4C addition stopped at the solid solubility limit of B4C in SiC, demonstrated to be at ~0.26 wt%. 

  

To investigate the liquid-phase sintering methodologies for silicon carbide, 10 wt% of AlN and Y2O3 were added with a molar ratio of 3:2. The effect of different powder beds for the specimens to be immersed in, and different sintering atmospheres were studied. Four types of powder beds were investigated: pure SiC, 1:1 (wt%) SiC and AlN, the same composition used to make the samples, and pure AlN. It was found that the pure AlN powder bed yielded the highest relative density and finest grain size. This indicated that without the powder bed, the relatively high vapor pressure of AlN (or its vapor decomposition products) in the compact favored either evaporation/condensation particle coarsening or grain growth over sintering; the overpressure provided by the AlN powder bed surroundings thus improved sintering conditions.  

 

Four different atmospheres were then studied with the use of a 1:1 SiC and AlN powder bed. The results showed that different sintering dwell temperatures were required for optimum relative density using these different atmospheres.  Flowing He requires the lowest sintering dwell temperature (around 1700°C), followed by Ar, static vacuum, and then N2 requiring the highest temperature (~1950°C). These higher dwell temperatures were required from the more difficult diffusivity of larger molecular/atomic sized trapped gases out of sintered bodies of closed porosity.  Significant grain growth was observed for temperatures higher than their optimum temperatures, with associated decreasing sintered relative density. The highest relative density (96.37%) was achieved with an atmosphere created by pulling vacuum at room temperature, and then maintaining a static atmosphere during sintering. For optimally sintered specimens exposed to these atmospheres, lower Vickers hardness (15.03-18.35 GPa) were measured compared to solid-state sintered SiC, but very high Vickers indentation fracture toughness (2.92-7.85 MPam1/2) were obtained. This is associated with the relatively weak grain boundary phase deflecting/branching propagating cracks. 

 

This work then investigated the sintering of SiC with lower additive concentrations: 1-4 wt% of AlN and 0-2 wt% of Y2O3, using a flow-through He atmosphere, with the compacts immersed in a pure AlN powder bed. Relative densities were inferior to the previous study; it increased with increasing Y2O3 content. In the absence of Y2O3, AlN acted as a grain growth inhibitor, and points toward the potential merit of a Prochazka composition with AlN additions.   

 

A 2-D computer model of sintering was constructed using MATLAB. Green microstructures were represented in a 2-D view. The filled circles representing particles were generated with random number generator and a fall-and-roll algorithm. The sintering process was simulated with sequential algorithms of the initial, intermediate, and final stages of sintering. Each stage with controlling factors that could be input depicts microstructures that would result under differing conditions. The simulation depicted particle neck formation, particle re-shaping, pore elimination (densification), and grain growth, forming microstructures generally consistent with those observed after sintering. 

]]> Tatianna Richardson 1 1701116462 2023-11-27 20:21:02 1701116462 2023-11-27 20:21:02 0 0 event Sintering Methodologies For Silicon Carbide Ceramics

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<![CDATA[PhD Defense by Brian Day]]> 27707 School of Physics Thesis Dissertation Defense

 

Presenter:        Brian Day

Title:                   Abstract and Physical Effects of Curvature on Dynamics of Extended Body Systems

Date:                  Wednesday, November 29, 2023

Time:                  12:00 p.m.

Location:           Howey N202

 

Committee members:

Dr. Elisabetta Matsumoto, School of Physics, Georgia Institute of Technology (Advisor)

Dr. Steve Trettel, College of Arts and Sciences, University of San Francisco

Dr. Deirdre Shoemaker, Department of Physics, University of Texas at Austin

Dr. Simon Sponberg, School of Physics, Georgia Institute of Technology

Dr. John Wise, School of Physics, Georgia Institute of Technology

 

Abstract:

The presence of intrinsic curvature of an ambient space influences the dynamics of point particles moving through it as typically considered in applications of differential geometry in physical contexts, such as general relativity. We aim to utilize the mathematics of differential geometry to instead consider the collective curvature effects on extended body systems in some generic curved space. To this end we develop a mathematical framework which serves as the foundation of a general dynamics solver numerical toolkit in which users can simulate the dynamics of discrete extended body systems in generic curved spaces. Through analyzing the dynamics of such extended body systems we recognized a relationship between deformation of the body during its dynamics as a result of the ambient curvature. This led us to expand our mathematical model of extended bodies to include deformable bodies. We find that such deformable bodies can generate collective motion via deforming their body even in a ambient space lacking curvature. This is due to the presence of an abstract notion of curvature defined on the configuration space of the system via considering the system as being described by a mathematical object known as a fiber bundle. This revelation allows us to discuss the dynamics of such deformable control systems using the ideas of geometric mechanics. In particular, we consider recasting our system in a geometric mechanics framework to address the question of determining optimal controls of how to deform the system so as to minimize some cost function. This is based on considering the optimization problem as a variational problem whose solutions correspond to optimal controls of the system. We develop this variational approach into a numerical toolkit acting as the foundation of a more general purpose optimization toolkit for deformable control systems described by fibers bundles.

 

]]> Tatianna Richardson 1 1701116159 2023-11-27 20:15:59 1701116159 2023-11-27 20:15:59 0 0 event Abstract and Physical Effects of Curvature on Dynamics of Extended Body Systems

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<![CDATA[PhD Defense by Jose Torres Gonzalez]]> 27707  

Announced 7 days prior to defense due to holiday break and scheduling issues, with approval by Associate Chair of Graduate Programs and Office of Graduate Education.

 

School of Civil and Environmental Engineering

Ph.D. Thesis Defense Announcement

Towards the Implementation of a Geotechnical Asset Management Program in Georgia

By Jose Torres Gonzalez

Advisor:

Dr. Jorge Macedo (CEE)

Committee Members:  Dr. Susan E. Burns (CEE), Dr. Baabak Ashuri (CEE), Dr. Gervais W. Tabopda (CP),
Dr. Pablo Quinde (Univ. of Azuay)

Date and Time:  Monday, December 4th, 2023, 3:45 PM - 5:45 PM EST

Location: Mason 2119

Over the past decade, federal mandates (MAP-21, 2012; FAST, 2015) have emphasized the importance of managing transportation corridor assets from risk and performance perspectives. Despite these mandates, geotechnical assets in Georgia, which are crucial for reliable transportation networks, have been inadequately managed. This research evaluates Georgia's current practices in managing geotechnical assets, such as retaining walls, slopes, embankments, and bridge foundations, and develops a comprehensive Geotechnical Asset Management (GAM) framework and a modern GIS-based computational system (G-GAMS) to facilitate risk-based management and improve the state's efforts to comply with federal and state performance objectives.
 
Inspired by the National Cooperative Highway Research Program (NCHRP-903) and successful practices from other U.S. states, the proposed GAM framework follows a six-step sequence, including definition, inventory, inspection, risk analysis, communication of results, and the refinement process, with an emphasis on using innovative technologies like image-based systems and machine learning to improve data collection and asset inspection processes in future endeavors. The novel computational system developed supports the GAM framework for Georgia. This scalable system enables the progressive evolution of GAM maturity, incorporating elements like 10-year deterioration scenarios, geotechnical databases enriched with key features, and metrics to monitor the condition state of geotechnical assets and the progress of the statewide GAM implementation. Furthermore, the computational system incorporates redesigned components of the GAM Planner (NCHRP-903), transitioning from a stationary Excel-based tool to a dynamic, data-driven geospatial tool. Field trials validate the GAM framework and G-GAMS system, demonstrating their practicality and potential for significant financial and operational benefits. The findings stress the importance of proactive, risk-based management strategies for reducing costs, enhancing operational efficiency, and meeting federal compliance standards.
 
In conclusion, the dissertation presents a roadmap  for the successful implementation of a GAM program at an initial maturity level in Georgia, relying on improved geotechnical risk-driven strategies and the efficient allocation of resources based on GAM metrics, thereby improving the management and stewardship of the state's transportation infrastructure.

]]> Tatianna Richardson 1 1701115861 2023-11-27 20:11:01 1701115861 2023-11-27 20:11:01 0 0 event Towards the Implementation of a Geotechnical Asset Management Program in Georgia

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<![CDATA[PhD Defense by Ziheng Shen]]> 27707 School of Civil and Environmental Engineering

Ph.D. Thesis Defense Announcement

Silver Adsorbents for Radioactive Iodine Capture in Nulcear Energy Applications

By Ziheng Shen

Advisor:

Dr. Sotira Yiacoumi (CEE)

Committee Members:  Dr. Yongsheng Chen (CEE), Dr. Costas Tsouris (CEE/Oak Ridge National Lab), Dr. Xing Xie (CEE), Dr. Andrew Medford (ChBE)

Date and Time:  Tuesday, December 12th, 2023, at 2pm

Location: Room 4222, Price Gilbert Memorial Library; Zoom: https://gatech.zoom.us/j/93337914447?pwd=MVFuYkVSZXI2VmlQUmIxY2xwZmE0dz09.

Complete announcement, with abstract, is attached.

 

Nuclear power serves as a pivotal component of the global energy supply, yet managing spent nuclear fuel (SNF) produced during electricity generation remains a challenge. Reprocessing SNF to reuse uranium offers a viable solution in a sustainable fashion, but it releases radioactive iodine (129I), a hazardous byproduct that must be removed from the off gas streams. Silver (Ag) based adsorbents have shown efficacy in iodine capture, whereas further advancement on the material development and the process design relies on a more fundamental understanding of adsorption processes. In this context, the dissertation presented here addresses current knowledge gaps surrounding two prototype Ag adsorbents: reduced silver functionalized silica aerogel (Ag0-aerogel) and reduced silver exchanged mordenite (Ag0Z).
 
One critical challenge with Ag0-aerogel is the diminishment in adsorption capacity after exposure to reprocessing off-gas at elevated temperatures, a phenomenon termed as ‘aging.’ Experiments were designed to evaluate the impact of three potential aging-inducing factors – oxygen, nitrogen dioxide, and temperature – on aerogel’s capacity over time. Through extensive characterization of the aged samples, we deduced plausible mechanisms governing the capacity reduction and employed density functional theory (DFT) calculations for theoretical corroboration. The last part of this thesis focuses on Ag0Z, exploring its capture performance on long-chain alkyl iodides. Synchrotron pair distribution function (PDF) analysis provides insights into the mechanisms underlying the uptake of various iodine species by Ag0Z. A numerical modeling framework was implemented to describe and make predictions on the fixed-bed adsorption process. The methodology established in this study, integrating deep insights into the molecular-level adsorption mechanisms with practical considerations for large-scale applications, is instrumental to the optimization of iodine removal strategies in SNF reprocessing and related fields.

]]> Tatianna Richardson 1 1701115713 2023-11-27 20:08:33 1701115713 2023-11-27 20:08:33 0 0 event Silver Adsorbents for Radioactive Iodine Capture in Nulcear Energy Applications

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<![CDATA[PhD Defense by Abishek Kasturi]]> 27707  

School of Civil and Environmental Engineering

Ph.D. Thesis Defense Announcement

Capture of CO₂ Using Potassium Salts of Amino Acids and Guanidine-Based Ligands

By Abishek Kasturi

Advisor:

Dr. Sotira Yiacoumi (CEE)

Committee Members:  Dr. Ameet Pinto (CEE), Dr. Costas Tsouris (CEE/Oak Ridge National Lab), Dr. Fani Boukouvala (ChBE), Dr. Radu Custelcean (Oak Ridge National Lab)

Date and Time:  Monday, December 11th, 2023, at 10am

Location: Monday, December 11th, 2023, at 10am  Zoom:  https://gatech.zoom.us/j/98345225537?pwd=Tk13VlNFK1BMVGM2K0ZZZnZiaFVmQT09

Meeting ID: 983 4522 5537

Passcode: 619879

 


 The concentration of atmospheric CO₂ has been steadily increasing since the industrial revolution, posing a significant threat to the global climate. The well-established correlation between rising anthropogenic CO₂ levels and climate change necessitates urgent action to reduce global carbon emissions. To mitigate the potentially irreversible consequences of climate change, deploying technologies capable of capturing CO₂ from point source emissions and the atmosphere is crucial. This thesis addresses knowledge gaps in flue gas-based capture and direct air capture of CO₂, focusing on the use of aqueous amino acids and phase-changing guanidines as promising alternatives.

Amino acids and guanidines exhibit favorable kinetics, negligible volatility, and lower energy requirements for regeneration compared to commonly used materials. To advance carbon capture, comprehensive understanding of the thermodynamics, kinetics, regeneration energy requirements, scalability potential, and costs associated with large-scale implementation is essential. This research involves thermodynamic and kinetic measurements to identify rate-limiting steps and cyclic capacities of amino acid and guanidine-based materials for carbon capture. Differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR) were employed to measure regeneration energy requirements, sensible heat, desorption enthalpy, and vaporization enthalpy.

Process-scale up potential was explored by intensifying the amino acid loading and guanidine crystallization steps. A novel gas-liquid contactor with high specific surface area, good wettability, high corrosion resistance, and moderate pressure drop was developed to enhance process intensification. Additionally, a technoeconomic analysis, based on experimental data and ASPEN modeling, estimated the energy requirements and costs of a scaled-up 1 Mt CO₂ direct air capture facility.

The information presented in this thesis is instrumental for implementing solvent-based carbon capture technologies, contributing to the global effort to combat climate change.

]]> Tatianna Richardson 1 1701115526 2023-11-27 20:05:26 1701115526 2023-11-27 20:05:26 0 0 event Capture of CO₂ Using Potassium Salts of Amino Acids and Guanidine-Based Ligands

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<![CDATA[Ph.D. Dissertation Defense - Sai Rakesh Moha Vangapandu]]> 28475 TitleA Novel Heterogeneously Integrated Photonic Platform for Optical Interconnects

Committee:

Dr. Ali Adibi, ECE, Chair, Advisor

Dr. Benjamin Klein, ECE

Dr. Madhavan Swaminathan, ECE

Dr. Rick Trebino, Physics

Dr. Stephen Ralph, ECE

]]> Daniela Staiculescu 1 1701111548 2023-11-27 18:59:08 1701111548 2023-11-27 18:59:08 0 0 event Silicon has been the widely used material for integrated photonics due to the availability of the advanced foundry infrastructure. Recently, silicon carbide and lithium niobate have been widely investigated for chip-scale photonics, bringing owing to their unique photonic properties spanning across classical and quantum applications. Compared to silicon, these materials offer wide transparency and high-speed electro-optic effect which is necessary to address the energy-speed barrier in computing. In this research, I present a novel hybrid material platform enabled for the first time, through heterogenous integration of SiC and LN. While heterogenous integration through wafer bonding is a well-known process in photonics, especially for laser integration, we need to overcome the thermal expansion challenge of materials. I will discuss - 1) the process flow for developing the hybrid SiC-LN, 2) photonic device fabrication, and the 3) demonstration of electro-optic phase shift. This will be followed by the discussion of CMOS-photonics, and on-package interconnects – which is the state-of-the art technology used in industry with Si, silicon nitride, and glass  materials. Here, I discuss my research accomplishments in the fabrication of microheaters for reconfigurability, and the development of an on-package optical interconnects. The novel material platform demonstrated here will provide a new pathway for unique device architectures spanning across classical and quantum computing applications.

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<![CDATA[Ph.D. Dissertation Defense - Ahmad Mustafa]]> 28475 TitleMultiscale Integration of Cross-Modal Subsurface Data for Reservoir Characterization under Label-Constrained Environments

Committee:

Dr. Ghassan AlRegib, ECE, Chair, Advisor

Dr. Mark Davenport, ECE

Dr. David Anderson, ECE

Dr. Reza Rastegar, OXY

Dr. Zhigang Peng, EAS

]]> Daniela Staiculescu 1 1701111270 2023-11-27 18:54:30 1701111304 2023-11-27 18:55:04 0 0 event Accurately mapping and evaluating hydrocarbon resources in the subsurface is critical to meeting the energy needs of our modern world. Hydrocarbons, such as oil and natural gas, serve as a major source of energy, a vital feedstock for various industrial processes, and play a significant role in global economics and geopolitics. Successful hydrocarbon exploration efforts depend on the integration of various scientific disciplines, including but not limited to geology, geophysics, geochemistry, petrophysics, and environmental geoscience. To accurately map and characterize subsurface deposits, exploration companies acquire and interpret various kinds of data, such as seismic shots, well logs, and core samples. These data have different natures, resolutions, scales, and extents. Additionally, they yield insights into overlapping, but also complementary characteristics of the subsurface. Over the recent years, deep learning has shown promise in automating subsurface understanding for exploration. However, a more complete adoption of advanced deep learning algorithms requires overcoming challenges on two fronts: firstly, acquiring training labels for machine learning models is an expensive and time-consuming process. Consequently, models trained on limited labeled data are prone to overfitting. Secondly, the efficient integration of various subsurface data depends on machine learning models that can account for their unique spatio-temporal properties. Our work has served to address these challenges in a systematic fashion by leveraging advanced machine learning paradigms such as active learning, by developing novel training frameworks suitable for settings involving limited, incomplete labels, and by building machine learning models to better account for the spatio-temporal properties of subsurface data. 

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2023-12-06T13:00:00-05:00 2023-12-06T15:00:00-05:00 2023-12-06T15:00:00-05:00 2023-12-06 18:00:00 2023-12-06 20:00:00 2023-12-06 20:00:00 2023-12-06T13:00:00-05:00 2023-12-06T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-06 01:00:00 2023-12-06 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[Ph.D. Dissertation Defense - Sevda Gharehbaghi]]> 28475 TitleAnalysis of Joint Acoustic Emissions for Health Monitoring with Wearable Technologies

Committee:

Dr. Omer Inan, ECE, Chair, Advisor

Dr. Azadeh Ansari, ECE

Dr. Sampath Prahalad, Emory

Dr. David Ewart, U of Minnesota

Dr. Mark Davenport, ECE

]]> Daniela Staiculescu 1 1701111088 2023-11-27 18:51:28 1701111130 2023-11-27 18:52:10 0 0 event According to the World Health Organization (WHO), musculoskeletal chronic conditions are the leading causes of disability worldwide. Chronic conditions, such as arthritis, have no specific lab tests, and a diagnosis is formed based on a constellation of subjective exams. Physicians also listen to joint sounds to evaluate joint health, scientifically known as joint acoustic emissions (JAEs).  As Thomas R. Insel says, "The good news stories in medicine are early detection, early intervention". To facilitate early detection of joint disease, this work focuses on JAE analysis as a digital biomarker for knee health assessment through machine learning and signal processing techniques using wearable devices. To achieve this, JAEs from loaded and unloaded knees were recorded during the treatment of patients with juvenile idiopathic arthritis (JIA). Machine learning models were developed using JAEs to assign health scores. Model predictions supported the clinical records of successful treatment and showed that the loaded and unloaded exercises contained different and possibly clinically relevant information. To improve the pre-processing and reliability of JAEs a novel algorithm was developed to detect and exclude JAEs contaminated with rubbing artifacts. Then, JAEs were explored under two different loading conditions and compared against synchronously recorded knee biomechanical signals to determine their attribution to the biomechanics, verifying that JAEs contain salient information on knee tribology. JAEs result from friction between various knee surfaces during movement cycles, not all of which are clinically relevant. Those knee phases generating more informative JAEs to distinguish between patients with osteoarthritis (OA) and healthy controls were identified in three routine clinical maneuvers from several locations around the knee. Focusing on certain locations and phases significantly improved classification performance and reduced the computational load. This work lays the foundation for improved usability of JAEs as a quantitative diagnostic biomarker in patients with JIA or OA, and it establishes a strong quantitative correlation between JAEs and knee tribology. The importance of exercise type and microphone placement was highlighted, and informative phases were determined to enhance the computational efficiency of wearable devices.

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<![CDATA[Colloquium Seminar - Prof. Boone Prentice (University of Florida)]]> 36441 TBA

]]> slawrence67 1 1701107470 2023-11-27 17:51:10 1701107470 2023-11-27 17:51:10 0 0 event TBA

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2024-01-18T15:30:00-05:00 2024-01-18T16:30:00-05:00 2024-01-18T16:30:00-05:00 2024-01-18 20:30:00 2024-01-18 21:30:00 2024-01-18 21:30:00 2024-01-18T15:30:00-05:00 2024-01-18T16:30:00-05:00 America/New_York America/New_York datetime 2024-01-18 03:30:00 2024-01-18 04:30:00 America/New_York America/New_York datetime <![CDATA[]]> Host: Prof. Facundo Fernandez

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<![CDATA[Ph.D. Dissertation Defense - Vedula Venkata Bharadwaj]]> 28475 TitleDesign of high-performance and energy-efficient interconnection systems for heterogeneous multi-chiplet graphics processing units

Committee:

Dr. Tushar Krishna, ECE, Chair, Advisor

Dr. Hyesoon Kim, CoC

Dr. Arijit Raychowdhury, ECE

Dr. Bradford Beckmann, AMD

Dr. Mathew Sinclair, U Wisconsin

]]> Daniela Staiculescu 1 1701104291 2023-11-27 16:58:11 1701104328 2023-11-27 16:58:48 0 0 event The end of Dennard scaling followed by the slowing of Moore’s law has made computer systems increasingly complex, with the integration of not just multiple types of processing units but also multiple disintegrated chiplets on a single package. The adoption of multi-chiplet architectures by commercial vendors has propelled the need to develop new designs, tools, and methodologies for building high-performance and energy-efficient next-generation systems. Chiplet-based systems introduce several new design constraints and pose challenging research questions. Unfortunately, current state-of-the-art architectures and design methodologies do not efficiently adapt to the new constraints posed by these packaging technologies. Additionally, with the dramatic increase in the usage of Graphics Processing Units (GPUs) for general-purpose computation, it has become particularly important to optimize solutions for them. Thus, there is a broad need to revisit the system research and design approaches for these multi-chiplet GPUs. This thesis addresses some of these challenges by exploring GPU and interconnection system architectures, developing tools and methodologies, and proposing novel designs to enable efficient and tighter integration on next-generation GPU systems. The thesis approaches these objectives in three major directions. First, the thesis delivers tools to enable high-fidelity simulation tools and infrastructure for accurate and efficient exploration of multi-chiplet architectures. Second, it explores design that can enable efficient integration of interposer-based designs by enabling robust design semantics in the interconnection system. Third, it enables workload-aware dynamic power efficiency mechanisms in multi-chiplet GPUs by leveraging the improvement in power delivery systems. Overall, the insights and guidelines provided in this dissertation could serve as a valuable resource for future research and development in the field of chiplet-based GPU systems.

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2023-12-01T13:00:00-05:00 2023-12-01T15:00:00-05:00 2023-12-01T15:00:00-05:00 2023-12-01 18:00:00 2023-12-01 20:00:00 2023-12-01 20:00:00 2023-12-01T13:00:00-05:00 2023-12-01T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 01:00:00 2023-12-01 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[Ph.D. Dissertation Defense - Paprapee Buason]]> 28475 TitleSample-Based Power Flow Approximations: Computational Methods, Analysis, and Applications

Committee:

Dr. Daniel Molzahn, ECE, Chair, Advisor

Dr. Sakis Meliopoulos, ECE

Dr. Justin Romberg, ECE

Dr. Santiago Grijalva, ECE

Dr. Constance Crozier, ISyE

]]> Daniela Staiculescu 1 1701104129 2023-11-27 16:55:29 1701104147 2023-11-27 16:55:47 0 0 event The non-convex nature of the power flow equations poses a challenge for solving various power system optimization and control problems. To address these challenges, linear approximations are often employed. However, the accuracy of these linearizations can vary depending on the characteristics of the systems and the operational range. Existing linearizations typically rely on general assumptions that apply to broad classes of systems, which can result in constraint violations. In contrast to these existing approaches, we introduce conservative linear approximations of the power flow equations that intentionally over- or underestimate quantities of interest, aiming to make algorithms more tractable while avoiding constraint violations. Additionally, we introduce rational approximations with linear numerators and denominators. This choice is motivated by the resulting linear inequality constraints, making these approximations well-suited for optimization formulations, while still providing enhanced accuracy compared to linear functions. We enhance the conservativeness and accuracy of our approximations through an iterative sampling method. To further develop our approach, we establish an importance sampling method for constructing conservative linear approximations. This method's objective is to efficiently select the most informative samples. It does so by drawing samples from a relatively low-dimensional subspace exhibiting high curvature. This approach allows us to obtain highly accurate linear approximations with significantly fewer samples than random selection. Furthermore, we examine applications of conservative linear approximations in an optimal sensor placement problem that we formulate as a bilevel program. Our goals are to place a minimal number of sensors, avoid false sensor alarms, and ensure that sensors will detect any voltage violations. To make the bilevel problem tractable, we replace the nonlinear power flow equations with conservative linear approximations and apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors.

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2023-12-05T14:00:00-05:00 2023-12-05T16:00:00-05:00 2023-12-05T16:00:00-05:00 2023-12-05 19:00:00 2023-12-05 21:00:00 2023-12-05 21:00:00 2023-12-05T14:00:00-05:00 2023-12-05T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 02:00:00 2023-12-05 04:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Ph.D. Dissertation Defense - Milad Ghiasi Rad]]> 28475 TitleImprovements in the Modeling of High Dimension/Low Sample Size Imbalanced Clinical Data Sets

Committee:

Dr. Rishikesan Kamaleswaran, BME, Chair, Advisor

Dr. Omer Inan, ECE, Co-Advisor

Dr. David Anderson, ECE

Dr. Jocelyn Grunwell, Emory

Dr. Soheli Saedi, Florida Tech

Dr. Tony Pan, Emory

]]> Daniela Staiculescu 1 1701103928 2023-11-27 16:52:08 1701103950 2023-11-27 16:52:30 0 0 event This dissertation has tried to tackle three common problems in the field of biomedical research data analytic. The problems that are covered in this document fall around the concept of imbalance and high dimensionality that is in the nature of the datasets that are gathered in this field of research, although they can be extended to other fields as well. Both imbalance and high dimensionality suffer this area of research by impacting the predictive models negatively resulting in introduction of over-fit, or noise in the models. First high dimensionality of the whole blood gene expression arrays are addressed and a new approach using Stability Selection has been proposed to reduce the dimension of these datasets. Then a novel pipeline to combine single-cohort studies into multi-cohort studies is proposed. The pipeline is tested on two GSE datasets which verified the proposed approach. Then, Stability Selection was used to be combined with SMOGN to boost the performance of regression in imbalanced, small, and horizontal datasets. The increase in the regression accuracy enabled further discoveries on AirPICU dataset which and showed the importance of PRISM as a very effective predictor of Ventilation Free Days which indirectly indicates the mortality chance. Finally, the use of unsupervised generative models like CTGAN and TVAE was investigated to reduce the imbalance in imbalanced datasets. It was observed that CTGAN is a powerful model that can improve the performance of SMOTE in imbalance removal both with over-sampling and complete synthetic data modeling.

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2023-12-04T13:00:00-05:00 2023-12-04T15:00:00-05:00 2023-12-04T15:00:00-05:00 2023-12-04 18:00:00 2023-12-04 20:00:00 2023-12-04 20:00:00 2023-12-04T13:00:00-05:00 2023-12-04T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-04 01:00:00 2023-12-04 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Microsoft Teams Meeting link]]>
<![CDATA[Inclusivity in Disney Movies with Julie Ann Crommett]]> 36009 Julie Ann Crommett will speak about the company Disney, its racist history, and its current efforts regarding inclusive storytelling.

About the Speaker

Julie Ann Crommett has been working in the content and Diversity, Equity and Inclusion (DEI) spaces for over a decade, leading disruptive, systemic change across media and tech. She currently serves as Google’s director of trust strategy for content safety collaborating with Google's consumer product teams and other stakeholders on solutions to enhance user privacy and trust specifically around harmful content.

Previously, she was vice president of multicultural audience engagement at The Walt Disney Studios, spearheading efforts to diversify talent in front of and behind the camera, connect creative projects more closely to the communities they touch, and build a more inclusive culture within the Studios. Her team contributed to many projects including SOUL, COCO, BLACK PANTHER, RAYA AND THE LAST DRAGON, and ALADDIN as well as launching the critically acclaimed, NAACP Image Award-nominated Disney Launchpad: Shorts Incubator, an industry-leading program guaranteeing up to six directors from underrepresented backgrounds the opportunity to produce a short film for Disney+.

Julie Ann was also instrumental in Disney's library review process leading to a revised content advisory and proactive resources for families to discuss negative stereotypes in media. In partnership with Disney executive chairman Bob Iger, she launched and co-chaired the company's first-ever creative inclusion council dedicated to increasing inclusion and accountability in Disney's creative endeavors.

]]> cwhittle9 1 1701102680 2023-11-27 16:31:20 1701102680 2023-11-27 16:31:20 0 0 event Julie Ann Crommett will speak about the company Disney, its racist history, and its current efforts regarding inclusive storytelling.

]]>
2023-12-05T12:30:00-05:00 2023-12-05T13:15:00-05:00 2023-12-05T13:15:00-05:00 2023-12-05 17:30:00 2023-12-05 18:15:00 2023-12-05 18:15:00 2023-12-05T12:30:00-05:00 2023-12-05T13:15:00-05:00 America/New_York America/New_York datetime 2023-12-05 12:30:00 2023-12-05 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> Britta Kallin
britta.kallin@modlangs.gatech.edu

]]>
<![CDATA[Join Online]]>
<![CDATA[StressBuzzters at the Library ]]> 28817 As always, we'll have snacks, counseling and more in the Library during finals. This semester, it'll take place between 2 and 4 p.m. on the first floor of Price Gilbert. Stop by and take a break!

]]> Jason Wright 1 1701102420 2023-11-27 16:27:00 1701102495 2023-11-27 16:28:15 0 0 event As always, we'll have snacks, counseling and more in the Library during finals.

]]>
2023-12-06T14:00:00-05:00 2023-12-06T16:00:00-05:00 2023-12-06T16:00:00-05:00 2023-12-06 19:00:00 2023-12-06 21:00:00 2023-12-06 21:00:00 2023-12-06T14:00:00-05:00 2023-12-06T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-06 02:00:00 2023-12-06 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> 672445 672445 image <![CDATA[StressBUzzters_new branding.png]]> image/png 1701102457 2023-11-27 16:27:37 1701102457 2023-11-27 16:27:37
<![CDATA[Exploratory Advising Drop-Ins (Virtual)]]> 36490 Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]> jreid67 1 1701095170 2023-11-27 14:26:10 1701095182 2023-11-27 14:26:22 0 0 event Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]>
2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30 19:00:00 2023-11-30 21:00:00 2023-11-30 21:00:00 2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 02:00:00 2023-11-30 04:00:00 America/New_York America/New_York datetime <![CDATA[Join the Meeting]]> <![CDATA[Exploratory Advising]]>
<![CDATA[Exploratory Advising Drop-Ins (Virtual)]]> 36490 Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]> jreid67 1 1701095134 2023-11-27 14:25:34 1701095147 2023-11-27 14:25:47 0 0 event Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]>
2023-11-30T09:00:00-05:00 2023-11-30T10:30:00-05:00 2023-11-30T10:30:00-05:00 2023-11-30 14:00:00 2023-11-30 15:30:00 2023-11-30 15:30:00 2023-11-30T09:00:00-05:00 2023-11-30T10:30:00-05:00 America/New_York America/New_York datetime 2023-11-30 09:00:00 2023-11-30 10:30:00 America/New_York America/New_York datetime <![CDATA[Join the Meeting]]> <![CDATA[Exploratory Advising]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1701095079 2023-11-27 14:24:39 1701095095 2023-11-27 14:24:55 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]>
2023-12-01T15:00:00-05:00 2023-12-01T16:00:00-05:00 2023-12-01T16:00:00-05:00 2023-12-01 20:00:00 2023-12-01 21:00:00 2023-12-01 21:00:00 2023-12-01T15:00:00-05:00 2023-12-01T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 03:00:00 2023-12-01 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1701095042 2023-11-27 14:24:02 1701095053 2023-11-27 14:24:13 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]>
2023-11-30T15:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30 20:00:00 2023-11-30 21:00:00 2023-11-30 21:00:00 2023-11-30T15:00:00-05:00 2023-11-30T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 03:00:00 2023-11-30 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1699907075 2023-11-13 20:24:35 1701095021 2023-11-27 14:23:41 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]>
2023-11-29T15:00:00-05:00 2023-11-29T16:00:00-05:00 2023-11-29T16:00:00-05:00 2023-11-29 20:00:00 2023-11-29 21:00:00 2023-11-29 21:00:00 2023-11-29T15:00:00-05:00 2023-11-29T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 03:00:00 2023-11-29 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1701094969 2023-11-27 14:22:49 1701094982 2023-11-27 14:23:02 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]>
2023-11-28T15:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28 20:00:00 2023-11-28 21:00:00 2023-11-28 21:00:00 2023-11-28T15:00:00-05:00 2023-11-28T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 03:00:00 2023-11-28 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1701094884 2023-11-27 14:21:24 1701094947 2023-11-27 14:22:27 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]>
2023-11-27T15:00:00-05:00 2023-11-27T16:00:00-05:00 2023-11-27T16:00:00-05:00 2023-11-27 20:00:00 2023-11-27 21:00:00 2023-11-27 21:00:00 2023-11-27T15:00:00-05:00 2023-11-27T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 03:00:00 2023-11-27 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[**CANCELED** - Georgia Tech Neuro Seminar]]> 35486 New date for this seminar to be announced!

"Living Electrodes: Developing Optogenetic Neuronal Networks for Circuit Modeling & Biological Neural Interfaces"

Oladayo Adewole, Ph.D.
Postdoctoral Researcher, Brant Lab
University of Pennsylvania

To participate virtually, CLICK HERE

*Lunch provided for in-person attendees

Students and postdocs are invited to join our speaker for a discussion following the presentation. Sign-up HERE (add your name to the speaker's tab).

SPEAKER BIO
Dayo Adewole (they/them or he/him) is a Nigerian-American postdoctoral researcher at the Philadelphia VA Medical Center and University of Pennsylvania. As a neural tissue engineering researcher, they design & develop living, light-controlled neural networks as (1) a model for complex brain pathways and (2) an implantable neural input, with a long-term focus on the development of biological neuroprosthetic devices. Their experience broadly spans bioengineering and robotics—primarily additive manufacturing (3D-printing), the design and fabrication of mechatronic systems, and brain-computer interfaces—and he has trained and served as an educator in several undergraduate and graduate-level engineering courses. Alongside their research and teaching, they designed the core technology for and co-founded InstaHub, a sustainability-focused startup developing easy-to-install embedded sensor systems to help track energy use & reduce waste in buildings.

Faculty Host: Garrett Stanley, Ph.D.
Student Host: Elaida Dimwamwa

Sign-up here to receive future GT Neuro Seminar Series announcements.

]]> Christina Wessels 1 1693506316 2023-08-31 18:25:16 1701092464 2023-11-27 13:41:04 0 0 event "Living Electrodes: Developing Optogenetic Neuronal Networks for Circuit Modeling & Biological Neural Interfaces" - Oladayo Adewole, Ph.D. - University of Pennsylvania

]]>
2023-11-27T11:15:00-05:00 2023-11-27T12:15:00-05:00 2023-11-27T12:15:00-05:00 2023-11-27 16:15:00 2023-11-27 17:15:00 2023-11-27 17:15:00 2023-11-27T11:15:00-05:00 2023-11-27T12:15:00-05:00 America/New_York America/New_York datetime 2023-11-27 11:15:00 2023-11-27 12:15:00 America/New_York America/New_York datetime <![CDATA[]]> Sarah Peterson

]]>
<![CDATA[Insider to INTA @ Tech]]> 27469 A networking night to connect students of all years to the opportunities at Tech related to international affairs including classes, study abroads, research, and internships. We also plan to invite INTA professors, advisors, and IAC career educators.

]]> Kristen Bailey 1 1700578174 2023-11-21 14:49:34 1701055506 2023-11-27 03:25:06 0 0 event A networking night to connect students of all years to the opportunities at Tech related to international affairs including classes, study abroads, research, and internships

]]>
2023-11-30T18:30:00-05:00 2023-11-30T19:30:00-05:00 2023-11-30T19:30:00-05:00 2023-11-30 23:30:00 2023-12-01 00:30:00 2023-12-01 00:30:00 2023-11-30T18:30:00-05:00 2023-11-30T19:30:00-05:00 America/New_York America/New_York datetime 2023-11-30 06:30:00 2023-11-30 07:30:00 America/New_York America/New_York datetime <![CDATA[]]> Maxine McCalla

]]>
<![CDATA[International Affairs Student Organization on Instagram]]> <![CDATA[International Affairs Student Organization on Engage]]>
<![CDATA[Fall 2023 I2P Showcase]]> 36436 On Thursday, November 30, CREATE-X will host the Fall 2023 Idea to Prototype (I2P) Showcase in the Marcus Nanotechnology Building Atrium from 5 to 7 p.m. At the showcase, student inventors across campus will present functional prototypes with application to real-world problems. The event is free and open to the public.

The showcase is the culmination of the I2P course, where Georgia Tech students spend a semester turning their invention idea into a working product. Students earn research credit for the course, in addition to receiving financial support and faculty mentorship.
The I2P course was established through CREATE-X, a Georgia Tech initiative devoted to instilling entrepreneurial confidence in students and empowering them to launch successful startups. CREATE-X consists of three programmatic elements – LEARN-MAKE-LAUNCH – and I2P is a key part of MAKE.

The showcase in November will highlight the talent and hard work of students who participated in I2P throughout the spring semester. Prizes will be awarded for first, second and third place.

]]> bdurham31 1 1700683285 2023-11-22 20:01:25 1700683285 2023-11-22 20:01:25 0 0 event On Thursday, November 30, CREATE-X will host the Fall 2023 Idea to Prototype (I2P) Showcase in the Marcus Nanotechnology Building Atrium from 5 to 7 p.m. At the showcase, student inventors across campus will present functional prototypes with application to real-world problems. The event is free and open to the public. The showcase is the culmination of the I2P course, where Georgia Tech students spend a semester turning their invention idea into a working product.

]]>
2023-11-30T17:00:00-05:00 2023-11-30T19:00:00-05:00 2023-11-30T19:00:00-05:00 2023-11-30 22:00:00 2023-12-01 00:00:00 2023-12-01 00:00:00 2023-11-30T17:00:00-05:00 2023-11-30T19:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 05:00:00 2023-11-30 07:00:00 America/New_York America/New_York datetime <![CDATA[]]> Shavon Hunter

CREATE-X Event Coordinator

shunter47@gatech.edu

]]>
<![CDATA[Register for the 2023 Fall I2P Showcase]]>
<![CDATA[Performance Management @Tech | Self-Assessment Demo]]> 35084 Georgia Tech Human Resources (GTHR) has been working diligently to improve processes and remove inefficient practices and launching a digitized performance management module in ServiceNow called Performance Management @Tech. This module has streamlined the process.

To support staff with the update to the performance management submission process, GTHR is hosting this live demonstration of the self-assessment phase. 

 

]]> cgrant60 1 1700662676 2023-11-22 14:17:56 1700683044 2023-11-22 19:57:24 0 0 event Dec. 1, through Jan. 31, 2024 is the Georgia Tech self-assessment period for staff. Join GTHR as they review how to complete these self-assessments in the digitized Performance Management @Tech platform.

Performance Management @Tech provides an efficient way to electronically submit and track yearly goals. It also eliminates the use of manual paper, PDF and DocuSign submissions.

]]>
2023-12-12T13:00:00-05:00 2023-12-12T13:30:00-05:00 2023-12-12T13:30:00-05:00 2023-12-12 18:00:00 2023-12-12 18:30:00 2023-12-12 18:30:00 2023-12-12T13:00:00-05:00 2023-12-12T13:30:00-05:00 America/New_York America/New_York datetime 2023-12-12 01:00:00 2023-12-12 01:30:00 America/New_York America/New_York datetime <![CDATA[Join Meeting ]]> <![CDATA[Visit the Performance Management webpage]]> <![CDATA[Meeting Link]]>
<![CDATA[Performance Management @Tech | Self-Assessment Demo - For Supervisors]]> 35084 Georgia Tech Human Resources (GTHR) has been working diligently to improve processes and remove inefficient practices and launching a digitized performance management module in ServiceNow called Performance Management @Tech.

To support supervisors with the update to the performance management self-assessment process, GTHR is hosting this live demonstration. 

 

]]> cgrant60 1 1700663479 2023-11-22 14:31:19 1700682989 2023-11-22 19:56:29 0 0 event Performance Management @Tech provides an efficient way to electronically submit and track yearly goals. It also eliminates the use of manual paper, PDF and DocuSign submissions.

]]>
2023-12-07T13:00:00-05:00 2023-12-07T13:30:00-05:00 2023-12-07T13:30:00-05:00 2023-12-07 18:00:00 2023-12-07 18:30:00 2023-12-07 18:30:00 2023-12-07T13:00:00-05:00 2023-12-07T13:30:00-05:00 America/New_York America/New_York datetime 2023-12-07 01:00:00 2023-12-07 01:30:00 America/New_York America/New_York datetime <![CDATA[Join Meeting ]]> <![CDATA[Visit the Performance Management webpage]]> <![CDATA[Meeting Link]]>
<![CDATA[World AIDS Day Resource Fair]]> 36479 World AIDS Day is Dec. 1, and it is the mission of the Wellness Empowerment Center(W.E. Center) to educate the Georgia Tech campus community about HIV/AIDS and safe sex practices, encourage people to get tested regularly, and empower everyone to take charge of their own health and to seek resources and treatment, if necessary.  

W.E. Center will be partnering with the LGBTQIA Resource Center to offer a resource fair on Dec. 1 from 10 a.m.-1 p.m. in the Northside Room on the third floor of the John Lewis Student Center. The resource fair will include education, activities, games and giveaways, plus free HIV testing.  

Normally, we say “down with red” on this campus, but we’re asking you to join us as #TechGoesRed for the day in honor of those affected by HIV/AIDS. Wear something red or grab a red ribbon from the W.E. Center office and take a group photo with us on Nov. 30 at 11 a.m. at the Campanile. If you can’t make the group photo, you can take your own photo with you and your friends and share it with us on Dec. 1 by using #WorldAIDSDayGT and tagging the W.E. Center (@gtwellnesscenter).  


If you would like free red ribbons from the W.E. Center, please use this link to request ribbons for your office, department, group, student organization, or residence hall beginning on Nov. 20. Let us know how many ribbons you would like and your preferred date to pick them up. 

]]> abowman41 1 1700681733 2023-11-22 19:35:33 1700682163 2023-11-22 19:42:43 0 0 event W.E. Center will be partnering with the LGBTQIA Resource Center, another department within Student Engagement and Well-Being, to offer a World AIDS Day resource fair on December 1st from 10 AM – 1 PM in the Northside Room on the third floor of the John Lewis Student Center. The resource fair will include education, activities, and giveaways, plus free HIV testing.

]]>
2023-12-01T10:00:00-05:00 2023-12-01T13:00:00-05:00 2023-12-01T13:00:00-05:00 2023-12-01 15:00:00 2023-12-01 18:00:00 2023-12-01 18:00:00 2023-12-01T10:00:00-05:00 2023-12-01T13:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 10:00:00 2023-12-01 01:00:00 America/New_York America/New_York datetime <![CDATA[]]> Richelle Fields

richelle.fields@gatech.edu

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672425 672425 image <![CDATA[WEC_World AIDS Day_112023_REV1 3.png]]> image/png 1700584701 2023-11-21 16:38:21 1700584701 2023-11-21 16:38:21
<![CDATA[Deadline to Submit Invoices, SIR's, Ad Hoc Payments, and Expense Reports to AP - Cloned]]> 27164 All invoices, supplier invoice request (SIR’s), ad hoc payments, and expense reports are to be submitted to Accounts Payable by Friday, Dec. 8, at 5 p.m. 

]]> Rachael Pocklington 1 1700667358 2023-11-22 15:35:58 1700667358 2023-11-22 15:35:58 0 0 event All invoices, supplier invoice request (SIR’s), ad hoc payments, and expense reports are to be submitted to Accounts Payable by Friday, Dec. 8, at 5 p.m. 

]]>
2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 2023-12-08 22:00:00 2023-12-08 22:00:00 2023-12-08 22:00:00 2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 America/New_York America/New_York datetime 2023-12-08 05:00:00 2023-12-08 05:00:00 America/New_York America/New_York datetime <![CDATA[]]> Rachael Pocklington
Institute Communications
rpocklington@gatech.edu

]]>
<![CDATA[Accounts Payable Forms]]>
<![CDATA[Deadline to Submit Invoices, SIR's, Ad Hoc Payments, and Expense Reports to AP]]> 27164 All invoices, supplier invoice request (SIR’s), ad hoc payments, and expense reports are to be submitted to Accounts Payable by Friday, Dec. 8, at 5 p.m. 

]]> Rachael Pocklington 1 1700666019 2023-11-22 15:13:39 1700667101 2023-11-22 15:31:41 0 0 event All invoices, supplier invoice request (SIR’s), ad hoc payments, and expense reports are to be submitted to Accounts Payable by Friday, Dec. 8, at 5 p.m. 

]]>
2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 2023-12-08 22:00:00 2023-12-08 22:00:00 2023-12-08 22:00:00 2023-12-08T17:00:00-05:00 2023-12-08T17:00:00-05:00 America/New_York America/New_York datetime 2023-12-08 05:00:00 2023-12-08 05:00:00 America/New_York America/New_York datetime <![CDATA[]]> Rachael Pocklington
Institute Communications
rpocklington@gatech.edu

]]>
<![CDATA[Accounts Payable Forms]]>
<![CDATA[HP Explores ATL: Atlanta Botanical Gardens Holiday Lights ]]> 35695 Join us on Saturday, December 9th for a trip to the Atlanta Botanical Garden's "Garden Lights, Holiday Nights" winter event. We will be meeting at 6:30pm in front of West Village to head towards the location via charter bus, and we will be returning back to campus around 9pm. Note: your free ticket only includes entry to the gardens and its activities. You will be responsible for purchasing food or any other items you'd like while there. 

About Atlanta Botanical Garden

Renowned plant collections, beautiful displays and spectacular exhibitions make the Atlanta Botanical Garden the loveliest place in the city to visit. An urban oasis in the heart of Midtown, the Garden includes 30 acres of outdoor gardens, an award-winning Children’s Garden, the serene Storza Woods highlighted by a unique Canopy Walk, and the picturesque Skyline Garden.
Back for its 13th year, Garden Lights, Holiday Nights presented by Invesco QQQ features familiar favorites and new installations, including Skyline Frost, a new skynet by Patrick Shearn of Poetic Kinetics; illuminated metal birds and deer by Cédric Le Borgne and the return of White Rabbit to the Skyline Garden Pond.

 

Location
1345 Piedmont Ave NE, Atlanta, GA 30309
Google Maps

Have Questions?
Email Amara Anderson, the HP coordinator, at aanderson75@gatech.edu.

RSVP via Qualtrics: https://gatech.co1.qualtrics.com/jfe/form/SV_77EukRWcDI93GZM

]]> aanderson75 1 1700665582 2023-11-22 15:06:22 1700666161 2023-11-22 15:16:01 0 0 event Join us on Saturday, December 9th for a trip to the Atlanta Botanical Garden's "Garden Lights, Holiday Nights" winter event. We will be meeting at 6:30pm in front of West Village to head towards the location via charter bus, and we will be returning back to campus around 9pm. Note: your free ticket only includes entry to the gardens and its activities. You will be responsible for purchasing food or any other items you'd like while there. 

About Atlanta Botanical Garden

Renowned plant collections, beautiful displays and spectacular exhibitions make the Atlanta Botanical Garden the loveliest place in the city to visit. An urban oasis in the heart of Midtown, the Garden includes 30 acres of outdoor gardens, an award-winning Children’s Garden, the serene Storza Woods highlighted by a unique Canopy Walk, and the picturesque Skyline Garden.
Back for its 13th year, Garden Lights, Holiday Nights presented by Invesco QQQ features familiar favorites and new installations, including Skyline Frost, a new skynet by Patrick Shearn of Poetic Kinetics; illuminated metal birds and deer by Cédric Le Borgne and the return of White Rabbit to the Skyline Garden Pond.

 

Location
1345 Piedmont Ave NE, Atlanta, GA 30309
Google Maps

Have Questions?
Email Amara Anderson, the HP coordinator, at aanderson75@gatech.edu.

RSVP via Qualtrics: https://gatech.co1.qualtrics.com/jfe/form/SV_77EukRWcDI93GZM

]]>
2023-12-09T19:00:00-05:00 2023-12-09T20:30:00-05:00 2023-12-09T20:30:00-05:00 2023-12-10 00:00:00 2023-12-10 01:30:00 2023-12-10 01:30:00 2023-12-09T19:00:00-05:00 2023-12-09T20:30:00-05:00 America/New_York America/New_York datetime 2023-12-09 07:00:00 2023-12-09 08:30:00 America/New_York America/New_York datetime <![CDATA[]]> honorsprogram@gatech.edu

]]>
672433 672433 image <![CDATA[HP Explores ATL Botanical Garden.png]]> A graphic promoting the upcoming Honors Program trip to the Atlanta Botanical Garden. The image includes a QR code to sign up.

]]> image/png 1700666110 2023-11-22 15:15:10 1700666110 2023-11-22 15:15:10
<![CDATA[RSVP via Qualtrics]]>
<![CDATA[Performance Management @Tech | Self-Assessment Demo]]> 35084 Georgia Tech Human Resources (GTHR) has been working diligently to improve processes and remove inefficient practices and launching a digitized performance management module in ServiceNow called Performance Management @Tech. This module has streamlined the process.

To support staff with the update to the performance management submission process, GTHR is hosting this live demonstration of the self-assessment phase. 

 

]]> cgrant60 1 1700662297 2023-11-22 14:11:37 1700665013 2023-11-22 14:56:53 0 0 event Dec. 1, through Jan. 31, 2024 is the Georgia Tech self-assessment period for staff. Join GTHR as they review how to complete these self-assessments in the digitized Performance Management @Tech platform.

Performance Management @Tech provides an efficient way to electronically submit and track yearly goals. It also eliminates the use of manual paper, PDF and DocuSign submissions.

]]>
2023-12-07T10:00:00-05:00 2023-12-07T10:30:00-05:00 2023-12-07T10:30:00-05:00 2023-12-07 15:00:00 2023-12-07 15:30:00 2023-12-07 15:30:00 2023-12-07T10:00:00-05:00 2023-12-07T10:30:00-05:00 America/New_York America/New_York datetime 2023-12-07 10:00:00 2023-12-07 10:30:00 America/New_York America/New_York datetime <![CDATA[Join Meeting ]]> <![CDATA[Visit the Performance Management webpage]]> <![CDATA[Meeting Link]]>
<![CDATA[Performance Management @Tech | Self-Assessment Demo - For Supervisors]]> 35084 Georgia Tech Human Resources (GTHR) has been working diligently to improve processes and remove inefficient practices and launching a digitized performance management module in ServiceNow called Performance Management @Tech.

To support supervisors with the update to the performance management self-assessment process, GTHR is hosting this live demonstration. 

 

]]> cgrant60 1 1700663823 2023-11-22 14:37:03 1700664938 2023-11-22 14:55:38 0 0 event Performance Management @Tech provides an efficient way to electronically submit and track yearly goals. It also eliminates the use of manual paper, PDF and DocuSign submissions.

]]>
2023-12-12T10:00:00-05:00 2023-12-12T10:30:00-05:00 2023-12-12T10:30:00-05:00 2023-12-12 15:00:00 2023-12-12 15:30:00 2023-12-12 15:30:00 2023-12-12T10:00:00-05:00 2023-12-12T10:30:00-05:00 America/New_York America/New_York datetime 2023-12-12 10:00:00 2023-12-12 10:30:00 America/New_York America/New_York datetime <![CDATA[Join Meeting ]]> <![CDATA[Visit the Performance Management webpage]]> <![CDATA[Meeting Link]]>
<![CDATA[Ph.D. Proposal Oral Exam - Zhiyu Xu]]> 28475 Title:  Development, Fabrication and Characterization of III-Nitride Bipolar Devices: Rectifiers, Avalanche Photodiodes, and Laser Diodes

Committee: 

Dr. Dupuis, Advisor      

Dr. Cai, Chair

Dr. Adibi

Dr. Yoder

Dr. Otte

]]> Daniela Staiculescu 1 1700634860 2023-11-22 06:34:20 1700634883 2023-11-22 06:34:43 0 0 event The objective of the proposed research is to develop III-nitride (III-N) based optoelectronic and electronic bipolar devices, mainly focusing on device fabrication and characterization. Different III-N bipolar devices have their specific applications and implementations, nevertheless, fabrication process and characterization approaches share similarities in terms of improving device performance and understanding the III-N device physics. The major focuses of III-N devices discussed in the scope of this proposal are gallium nitride-based vertical p-i-n rectifier, avalanche photodiode, and ultraviolet laser diode.

]]>
2023-12-01T14:45:00-05:00 2023-12-01T16:45:00-05:00 2023-12-01T16:45:00-05:00 2023-12-01 19:45:00 2023-12-01 21:45:00 2023-12-01 21:45:00 2023-12-01T14:45:00-05:00 2023-12-01T16:45:00-05:00 America/New_York America/New_York datetime 2023-12-01 02:45:00 2023-12-01 04:45:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Ph.D. Proposal Oral Exam - Kennedy Lee]]> 28475 Title:  Covert Multi-Satellite Cooperative Communications

Committee: 

Dr. Barry, Advisor

Dr. Stuber, Chair

Dr. Bloch

]]> Daniela Staiculescu 1 1700634440 2023-11-22 06:27:20 1700634481 2023-11-22 06:28:01 0 0 event The objective of the proposed research is to develop techniques to enable covert communications, where the aim is to conceal the presence of the transmitter, within the uplink multi-satellite cooperative communications context through improving the uplink low probability of detection (LPD) performance, as well as to develop analyses to quantify the LPD performance. In this context, multiple satellites cooperate to jointly receive uplink transmissions from user terminals. The primary motivation of this research is to expand the techniques for and understanding of covert communications in the context of low Earth orbit communications satellite constellations, where constellations can be dense enough to permit cooperation among satellites to improve the uplink quality, which can then be leveraged to improve the uplink LPD performance.

]]>
2023-12-07T10:00:00-05:00 2023-12-07T12:00:00-05:00 2023-12-07T12:00:00-05:00 2023-12-07 15:00:00 2023-12-07 17:00:00 2023-12-07 17:00:00 2023-12-07T10:00:00-05:00 2023-12-07T12:00:00-05:00 America/New_York America/New_York datetime 2023-12-07 10:00:00 2023-12-07 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[Ph.D. Proposal Oral Exam - Carmen Jimenez Cortes]]> 28475 Title:  Barrier Functions For Safe Shared Autonomy

Committee: 

Dr. Coogan, Advisor     

Dr. Wardi, Chair

Dr. Egerstedt

Dr. Thitsa

Dr. Feigh

]]> Daniela Staiculescu 1 1700630836 2023-11-22 05:27:16 1700630880 2023-11-22 05:28:00 0 0 event The objective of the presented research is to design barrier function inspired algorithms that enable safe shared autonomy for humans and autonomous systems teams. While always guaranteeing safety, the autonomy should be reactive to humans’ cognitive state to enhance collaboration among them. In chapter 3 we present our preliminary research, where we solved the problems of guaranteeing the execution of robotic tasks over long time horizons, and building valid discontinuous high-order control barrier function candidates for piecewise continuous systems. Additionally, we also develop a Matlab-Simulink testing platform using Microsoft Flight Simulator for high-quality visualization. This simulator will soon enable us to test our theoretical findings with human in the loop experiments, as explained in the proposed work in chapter 4. Lastly, we also aim to develop the theory to build high-order nonsmooth but continuous control barrier functions, as it is still an open question within the barrier function literature.

]]>
2023-11-27T10:00:00-05:00 2023-11-27T12:00:00-05:00 2023-11-27T12:00:00-05:00 2023-11-27 15:00:00 2023-11-27 17:00:00 2023-11-27 17:00:00 2023-11-27T10:00:00-05:00 2023-11-27T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 10:00:00 2023-11-27 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[RCR: ETHICx Talk with Bernard Reber - 11/28/2023]]> 27832 Attending the ETHICx Talk on November 28 from 2:00-3:30 PM is an option for students and postdocs funded by applicable NSF or NIH awards to satisfy one hour of their discussion-based RCR compliance training requirement. The session is offered in both in-person and virtual/remote formats:

The Ethics, Technology and Human Interaction Center (ETHICx) invites you to a talk with Bernard Reber, CNRS-affiliated Senior Research Fellow at Centre for Political Research at Sciences Po, France, titled "Merging ethics and stakeholder participation in the design of technologies".

You do not need to pre-register, but to receive RCR contact hour credit for attending either the in-person event or the virtual/remote session, you must sign in on-site or fill out the survey code that you will receive at the session.

Refer to https://calendar.gatech.edu/event/2023/11/28/merging-ethics-and-stakeholder-participation-design-technologies for more information and for the link to join online.

 

For more information about the RCR Workshop Series, including additional dates/sessions offered, refer to RCR Workshops and Events and Workshop FAQs.

 

]]> Judy Willis 1 1700599505 2023-11-21 20:45:05 1700609794 2023-11-21 23:36:34 0 0 event Attending the ETHICx Talk on November 28 is an option for students and postdocs funded by applicable NSF or NIH awards to satisfy one hour of their discussion-based RCR compliance training requirement. The session is offered in-person and virtually/remote.

 

 

 

]]>
2023-11-28T14:00:00-05:00 2023-11-28T15:30:00-05:00 2023-11-28T15:30:00-05:00 2023-11-28 19:00:00 2023-11-28 20:30:00 2023-11-28 20:30:00 2023-11-28T14:00:00-05:00 2023-11-28T15:30:00-05:00 America/New_York America/New_York datetime 2023-11-28 02:00:00 2023-11-28 03:30:00 America/New_York America/New_York datetime <![CDATA[]]> Judy Willis

RCR Program Administrator

404-894-4764

]]>
<![CDATA[GT RCR - Topic Areas]]> <![CDATA[RCR Compliance Policy]]> <![CDATA[RCR Compliance Training Matrix]]> <![CDATA[GT Responsible Conduct of Research]]> <![CDATA[RCR Training Email List]]> <![CDATA[RCR Training Status]]>
<![CDATA[Vertically Integrated Projects (VIP) Info Session]]> 35695 Join us for a talk with speakers from Vertically Integrated Projects (VIP) for a chat about the program as well as a chance to ask questions about projects and research across campus. The session is on Tuesday, November 28th from 5:30pm-6:30pm. We will be in the LLC West Commons Classroom, in the Curran parking deck next to Eighth Street apartments. Snacks will be provided, no RSVP required. 

About VIP

The Vertically Integrated Projects (VIP) Program offers our undergraduates with valuable experience to take part in faculty research in a team-based context, while gaining course credits. VIP students have the opportunity to work in multidisciplinary teams, to build expertise, and become valued assets/leaders within their teams. We have been continuously growing, and are projecting to serve 90+ teams and 2000 students in Spring 2024!  

]]> aanderson75 1 1700604591 2023-11-21 22:09:51 1700604958 2023-11-21 22:15:58 0 0 event Join us for a talk with speakers from Vertically Integrated Projects (VIP) for a chat about the program as well as a chance to ask questions about projects and research across campus. The session is on Tuesday, November 28th from 5:30pm-6:30pm. We will be in the LLC West Commons Classroom, in the Curran parking deck next to Eighth Street apartments. Snacks will be provided, no RSVP required. 

About VIP

The Vertically Integrated Projects (VIP) Program offers our undergraduates with valuable experience to take part in faculty research in a team-based context, while gaining course credits. VIP students have the opportunity to work in multidisciplinary teams, to build expertise, and become valued assets/leaders within their teams. We have been continuously growing, and are projecting to serve 90+ teams and 2000 students in Spring 2024!  

]]>
2023-11-28T17:30:00-05:00 2023-11-28T18:30:00-05:00 2023-11-28T18:30:00-05:00 2023-11-28 22:30:00 2023-11-28 23:30:00 2023-11-28 23:30:00 2023-11-28T17:30:00-05:00 2023-11-28T18:30:00-05:00 America/New_York America/New_York datetime 2023-11-28 05:30:00 2023-11-28 06:30:00 America/New_York America/New_York datetime <![CDATA[]]> honorsprogram@gatech.edu

]]>
672430 672430 image <![CDATA[HP VIP Info Session 112823.png]]> A graphic promoting the Vertically Integrated Projects program info session on November 28, 2023.

]]> image/png 1700604919 2023-11-21 22:15:19 1700604919 2023-11-21 22:15:19
<![CDATA[Merging Ethics and Stakeholder Participation in the Design of Technologies]]> 36009 The Ethics, Technology, and Human Interaction Center (ETHICx) invites you to a talk with Bernard Reber, CNRS-affiliated senior research fellow at Centre for Political Research at Sciences Po, France, titled "Merging ethics and stakeholder participation in the design of technologies."

Participatory design refers to approaches to technology design that give those a voice in the design process who will be affected by a technology. The talk will provide an analysis of European regulatory frameworks on ethics and participation; a conceptual analysis of the ethics of responsible research and innovation and of participatory mechanisms; and an attempt to merge both ethics and participation in what could be defined as ethical participation. Also, new classifications aiming at a clearer view regarding new publics invited in the arena of research and innovation processes are suggested, in addition to the identification of key factors worth considering for responsive participation. The talk will end with a final suggestion for the design of an ethics framework, which is meant to be used as a tool for reflection and adaptation in any research and innovation context to properly identify who participation will be undertaken with, why and when, as well as the participatory mechanism that is relevant.

]]> cwhittle9 1 1700579750 2023-11-21 15:15:50 1700598824 2023-11-21 20:33:44 0 0 event The Ethics, Technology, and Human Interaction Center (ETHICx) invites you to a talk with Bernard Reber, CNRS-affiliated Senior Research Fellow at Centre for Political Research at Sciences Po, France, titled "Merging ethics and stakeholder participation in the design of technologies."

]]>
2023-11-28T14:00:00-05:00 2023-11-28T15:30:00-05:00 2023-11-28T15:30:00-05:00 2023-11-28 19:00:00 2023-11-28 20:30:00 2023-11-28 20:30:00 2023-11-28T14:00:00-05:00 2023-11-28T15:30:00-05:00 America/New_York America/New_York datetime 2023-11-28 02:00:00 2023-11-28 03:30:00 America/New_York America/New_York datetime <![CDATA[]]> Michael Hoffmann
michael.hoffmann@pubpolicy.gatech.edu

]]>
672428 672428 image <![CDATA[Merging Ethics and Stakeholder Participation in the Design of Technologies.png]]> image/png 1700598678 2023-11-21 20:31:18 1700598678 2023-11-21 20:31:18 <![CDATA[Join Online]]>
<![CDATA[Nano@Tech Fall 2023 Series | Development and Clinical Translation of Microtechnologies for Hematologic Applications]]> 35272 Abstract: Hematologic processes are frequently comprised of cellular and biomolecular interactions that are biophysical in nature and may involve blood cells (erythrocytes, leukocytes, and platelets), endothelial cells, soluble factors (coagulation proteins, von Willebrand factor, and cytokines), the hemodynamic environment, or all of the above. These phenomena are often pathologically altered in hematologic diseases but are difficult to study using standard in vitro and in vivo systems. With the capabilities to dissect cellular and biomolecular phenomena at the micro to nanoscales with tight control of the mechanical and fluidic parameters, micromechanical and microfluidic systems can serve as novel yet physiological in vitro disease models to provide insight into the pathophysiology of blood disorders. Due to their inherent portability, these microsystems can also be translated into diagnostic tests used at the point-of-care or even by patients at home, especially if those technologies are coupled to existing consumer-based devices like smartphones. Recently, our lab has also developed open source software for the entire field to analyze blood-based microfluidic data more easily as well as embark on developing combined microfluidic and analytical strategies to help improve the efficiency and lower the cost of cellular therapies for hematologic diseases. By developing state-of-the art microdevices to answer hematologic questions, microsystems engineering has the potential to significantly advance our understanding of blood disorders and to develop innovative diagnostic and therapeutic strategies for patients afflicted with those life-threatening diseases.

Bio: Wilbur A. Lam, MD, PhD is the W. Paul Bowers Research Chair and Professor of Pediatrics and Biomedical Engineering at Emory University and Georgia Tech. Dr. Lam serves as Principal Investigator of the Atlanta Center for Microsystems Engineered Point-of-Care Technologies that is part of the NIH’s Point-of-Care Technologies Research Network and Director of Emory’s Center for the Advancement of Diagnostics for a Just Society. He is an elected member of the National Academy of Medicine and the American Society for Clinical Investigation and a fellow of the American Institute for Medical and Biological Engineering. As a physician-scientist-engineer, his work involves the development of microtechnologies to study and diagnose hematologic and oncologic disorders, especially those that empower patients to more easily monitor their own diseases at home and in the global health and rural settings.

View a live stream of the seminar

A boxed lunch will be served on a first come, first served basis.
]]> aneumeister3 1 1700597885 2023-11-21 20:18:05 1700597965 2023-11-21 20:19:25 0 0 event Featuring Wilbur Lam, M.D., Ph.D, Professor; Coulter Department of Biomedical Engineering Pediatric Hematologist/Oncologist; Children’s Healthcare of Atlanta Professor of Pediatrics; Emory University School of Medicine

]]>
2023-12-12T12:00:00-05:00 2023-12-12T13:00:00-05:00 2023-12-12T13:00:00-05:00 2023-12-12 17:00:00 2023-12-12 18:00:00 2023-12-12 18:00:00 2023-12-12T12:00:00-05:00 2023-12-12T13:00:00-05:00 America/New_York America/New_York datetime 2023-12-12 12:00:00 2023-12-12 01:00:00 America/New_York America/New_York datetime <![CDATA[]]> David Gottfried

]]>
<![CDATA[UX/HF Professionals Panel]]> 36418 Come join HFES this month for our local UX/HF professionals panel! Hear from Atlanta-based UX researchers, designers, and human factors experts. Come with questions prepared or just sit in to enjoy the discussion!

]]> sgagliano3 1 1700595447 2023-11-21 19:37:27 1700595543 2023-11-21 19:39:03 0 0 event Come join HFES this month for our local UX/HF professionals panel!

]]>
2023-12-05T18:00:00-05:00 2023-12-05T19:00:00-05:00 2023-12-05T19:00:00-05:00 2023-12-05 23:00:00 2023-12-06 00:00:00 2023-12-06 00:00:00 2023-12-05T18:00:00-05:00 2023-12-05T19:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 06:00:00 2023-12-05 07:00:00 America/New_York America/New_York datetime <![CDATA[]]> Sidney Scott-Sharoni

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<![CDATA[Workshop by Tiny Doors ATL]]> 36418 Learn how to make tiny doors from the artist behind Tiny Doors ATL, Karen Anderson Singer. This is a free workshop and all supplies will be provided! The RSVP For the event will release on Nov. 22, so be on the lookout!

]]> sgagliano3 1 1700084549 2023-11-15 21:42:29 1700595203 2023-11-21 19:33:23 0 0 event Learn how to make tiny doors from the artist behind Tiny Doors ATL, Karen Anderson Singer. This is a free workshop and all supplies will be provided!

]]>
2023-11-29T18:00:00-05:00 2023-11-29T20:00:00-05:00 2023-11-29T20:00:00-05:00 2023-11-29 23:00:00 2023-11-30 01:00:00 2023-11-30 01:00:00 2023-11-29T18:00:00-05:00 2023-11-29T20:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 06:00:00 2023-11-29 08:00:00 America/New_York America/New_York datetime <![CDATA[]]> Nihanth Pinnaka

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<![CDATA[Ph.D. Dissertation Defense - Nael Mizanur Rahman]]> 28475 TitleSecure High Performance Compute Accelerators for Radio Frequency Signal Processing

Committee:

Dr. Saibal Mukhopadhyay, ECE, Chair, Advisor

Dr. Tushar Krishna, ECE

Dr. Justin Romberg, ECE

Dr. Visvesh Sathe, ECE

Dr. Yingyan (Celine) Lin,CoC

]]> Daniela Staiculescu 1 1700587357 2023-11-21 17:22:37 1700587397 2023-11-21 17:23:17 0 0 event This thesis is centered on the design of high-throughput compute accelerators, with a specific focus on applications in secure encryption, high-bandwidth RF emulation, and Multiple Input Multiple Output (MIMO) digital RF beamforming. We begin by proposing security-aware pipelining techniques that use algorithmic key diffusion to enhance the throughput of PRINCE encryption accelerators while maintaining robustness against side-channel attacks. This approach is crucial for securing high-bandwidth data transmission. Additionally, we introduce a custom lightweight power supply sensor that enables the detection of power side-channel attacks on encryption engines with minimal hardware overheads, further bolstering the security of these systems. Next, we present a near-memory digital compute accelerator for real-time emulation of RF interactions. This architecture allows for the simulation of complex RF interactions within dynamic environments, incorporating various physical phenomena. Lastly, we present a Compute-In-Memory based digital beamforming accelerator. This design confronts the core challenges of scalability and energy efficiency in large-scale MIMO RX digital beamformers. It achieves substantial power savings compared to traditional beamforming architectures while minimally impacting beam accuracy.

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2023-11-29T09:15:00-05:00 2023-11-29T11:15:00-05:00 2023-11-29T11:15:00-05:00 2023-11-29 14:15:00 2023-11-29 16:15:00 2023-11-29 16:15:00 2023-11-29T09:15:00-05:00 2023-11-29T11:15:00-05:00 America/New_York America/New_York datetime 2023-11-29 09:15:00 2023-11-29 11:15:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Microsoft Teams Meeting link]]>
<![CDATA[Ph.D. Dissertation Defense - Ishaan Batta]]> 28475 TitleMultimodal frameworks to learn salient brain subspaces from neuroimaging data

Committee:

Dr. Vince Calhoun, ECE, Chair, Advisor

Dr. David Anderson, ECE

Dr. Constantine Dovrolis, ECE

Dr. Shella Keilholz, BME

Dr. Tulay Adali, UMBC

]]> Daniela Staiculescu 1 1700587038 2023-11-21 17:17:18 1700587141 2023-11-21 17:19:01 0 0 event With brain disorders being highly heterogeneous and affecting both the structure and function of multiple subsystems of the brain, it is crucial to develop learning frameworks to study, characterize, and utilize the interplay of associated information from different modalities and brain subsystems. However, most learning frameworks for neuroimaging data either do not consider the target assessment information during the unsupervised extraction of lower-dimensional brain subspaces, or can extract only high-dimensional importance associations as an ordered list of involved features when making diagnostic predictions, making manual interpretation at the level of subspaces difficult. Starting with the use of learning models to study how structural and functional feature modalities differ in terms of their saliency towards diagnostic classification, this work presents novel subspace learning frameworks to understand various active and independent subspaces within the brain. This is achieved by performing a decomposition in the saliency space to extract robust multimodal subspaces that define the most significant change in a given cognitive or biological trait. Through rigorous cross-validation procedures on Alzheimer's disease (AD) data, the framework not only uncovers AD-related brain regions in the associated brain subspaces, but also enables automated identification of multiple collectively varying structural and functional sub-systems of the brain. This framework is further extended to find independently salient subspaces using deep learning models that can handle high-dimensional voxel-level neuroimaging features to automatically uncover intrinsic networks in the brain associated with disease-specific clinical assessments. Additionally, the utilization and study of sub-domain structures in deep learning models for neuroimaging are also explored by introducing a flexible deep learning framework to effectively incorporate multimodal features while accounting for and exploiting the heterogeneity in the sub-domains of the brain. Experiments with this framework demonstrate that the discriminatory information from structural and functional sub-domains can be better recovered and analyzed if the complexity of the subspace structure in the model can be tuned to reflect the extent of non-linearity with which each sub-domain encodes the information.

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2023-11-27T13:30:00-05:00 2023-11-27T15:30:00-05:00 2023-11-27T15:30:00-05:00 2023-11-27 18:30:00 2023-11-27 20:30:00 2023-11-27 20:30:00 2023-11-27T13:30:00-05:00 2023-11-27T15:30:00-05:00 America/New_York America/New_York datetime 2023-11-27 01:30:00 2023-11-27 03:30:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[Hacking the Cycle: Femtech, Internalized Surveillance, and Productivity]]> 36009 This Ethics & Coffee event features Alzbeta Hajkova, postdoctoral teaching fellow in the School of Public Policy, and Tom Doyle, postdoctoral fellow at the Center for Bioethics, Indiana University to discuss "Hacking the Cycle: Femtech, Internalized Surveillance, and Productivity."

Femtech refers to a range of technologies that address health needs typically associated with women’s bodies, such as maternal health, fertility, menstruation, sexual wellness, or contraception. Our talk will examine a specific popular femtech product, cycle-tracking applications, as instruments of self-surveillance. We first discuss the relationship between technology and the experience of individual temporarility. Specifically, we focus on the relationship between surveillance workplace technologies and a sense of time discipline as an internalized drive toward increased worker productivity. We then apply this framework to the analysis of cycle-tracking apps, arguing that cycle-tracking apps perpetuate the attitude that the menstruator needs to manage their cycle for the sake of reliable participation in productivity, creating a disconnect between their internal experience of the temporality of menstruation and external pressures. Our critique contributes to the existing worries surrounding femtech—namely, the understanding of cycle-tracking apps as selling a false sense of women empowerment and separating users, under the guise of science, from self-knowledge of their bodies.

]]> cwhittle9 1 1700580010 2023-11-21 15:20:10 1700585768 2023-11-21 16:56:08 0 0 event Featuring Alzbeta Hajkova, postdoctoral teaching fellow in the School of Public Policy, and Tom Doyle, postdoctoral fellow at the Center for Bioethics, Indiana University.

]]>
2023-11-30T11:00:00-05:00 2023-11-30T12:00:00-05:00 2023-11-30T12:00:00-05:00 2023-11-30 16:00:00 2023-11-30 17:00:00 2023-11-30 17:00:00 2023-11-30T11:00:00-05:00 2023-11-30T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 11:00:00 2023-11-30 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> Michael Hoffmann
michael.hoffmann@pubpolicy.gatech.edu

]]>
<![CDATA[Join Online]]>
<![CDATA[McCamish Parkinson's Disease Innovation Conference]]> 27195 This conference will feature a mixture of local, as well as national and international speakers. Our goal is to showcase local area work to the outside world as well as develop a forum to share cutting-edge neurotechnology, facilitate discussions, and create synergies between scientists, clinical researchers, engineers and technologists to strengthen our community in an effort to eradicate Parkinson’s disease.

*NOTE* - Registration for the McCamish Parkinson's Disease Innovation Conference is now closed.

For complete program and information, Visit Conference Website.

]]> Colly Mitchell 1 1693594368 2023-09-01 18:52:48 1700584648 2023-11-21 16:37:28 0 0 event Understand, Treat, and Cure through Science, Engineering, and Data

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2023-12-05T08:00:00-05:00 2023-12-05T18:30:00-05:00 2023-12-05T18:30:00-05:00 2023-12-05 13:00:00 2023-12-05 23:30:00 2023-12-05 23:30:00 2023-12-05T08:00:00-05:00 2023-12-05T18:30:00-05:00 America/New_York America/New_York datetime 2023-12-05 08:00:00 2023-12-05 06:30:00 America/New_York America/New_York datetime <![CDATA[]]> Fadrika Prather

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672347 672347 image <![CDATA[McCamish Conference - 12-5-23]]> image/png 1699628851 2023-11-10 15:07:31 1699628918 2023-11-10 15:08:38
<![CDATA[BioE PhD Defense Presentation- Bryan Wang]]> 27917 Advisor: Krishnendu Roy, PhD – School of Biomedical Engineering, GT

 

Committee:

Stephen Balakirsky, PhD – Georgia Tech Research Institute

Fani Bukouvala, PhD – School of Chemical and Biomolecular Engineering, GT

Johnna Temenoff, PhD – School of Biomedical Engineering, GT

Carolyn Yeago, PhD – Institute of Bioengineering and Bioscience, GT

 

 

 

 

Process Development and Process Analytical Technology Integration for Cell Therapy Manufacturing

 

Biomanufacturing of cell therapies involves highly complex and labor-intensive processes, where the process parameters and biological variabilities can significantly influence product quality, reproducibility, and therapeutic efficacy of the products. The complexity and largely manual unit operations contribute to product variability and high cost. To address these manufacturing challenges, we designed a digital-twin-enabled closed-loop cell manufacturing platform with automation and feedback controls. This platform integrates process analytical technologies (PAT) to enable deeper process understanding and provide real-time control of process variables. Specifically, we designed bench-scale bioreactors with automated sampling, at-line and in-line monitoring, digital twin-enabled media nutrients estimation, and feedback-controlled feeding capabilities. Human umbilical cord tissue-derived MSCs (CT-MSCs) and T cells were used as the example cell therapy product. At-line glucose and lactate monitoring confirmed the accuracy of the digital twin estimations. Spent media samples and detailed functional characterizations of the MSCs and T cells end-products generated from the automation-controlled bioreactor demonstrated that high expansion and functions of the MSCs and T cells were maintained in these closed-loop bioreactors. Real-time imaging with quantitative oblique back illumination microscopy showed high-resolution images of cells in-process in a dynamic 3D environment. Overall, the digital twin-enabled bioreactor platform reduced costs, labor, time, and, more importantly, perturbations; and could improve yield while maintaining the phenotype and quality of cell therapy products. Our integrated automation system provides a blueprint for multiplexed PAT integration, process optimization, feedback-controlled intelligent automation to enable the discovery, monitoring, and control of critical quality attributes and critical process parameters for cell therapy manufacturing.

]]> Laura Paige 1 1700577403 2023-11-21 14:36:43 1700577403 2023-11-21 14:36:43 0 0 event BioE PhD Defense Presentation- "Process Development and Process Analytical Technology Integration for Cell Therapy Manufacturing" - Bryan Wang

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2023-12-04T14:00:00-05:00 2023-12-04T16:00:00-05:00 2023-12-04T16:00:00-05:00 2023-12-04 19:00:00 2023-12-04 21:00:00 2023-12-04 21:00:00 2023-12-04T14:00:00-05:00 2023-12-04T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-04 02:00:00 2023-12-04 04:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[BioE PhD Defense Presentation- Thomas Pho]]> 27917 Advisor: Julie Champion, Ph.D. (Chemical and Biomolecular Engineering)

 

Committee Members:

Jennifer E. Curtis, Ph.D. (Physics)

James E. Dahlman, Ph.D. (Biomedical Engineering)

Ravi S. Kane, Ph.D. (Chemical and Biomolecular Engineering)

Mark Prausnitz, Ph.D. (Chemical and Biomolecular Engineering) 

 

 

 

Surface Engineering of Protein Nanoparticles for Intranasal Vaccination

 

Intranasal delivery of vaccines offers a promising alternative approach to invasive intramuscular injection, with additional benefits such as inducing mucosal antibodies and cellular responses to neutralize pathogens before entering systemic circulation. However, nasal secretions and mucosa are biological barriers that have been shown to inhibit the delivery of antigens and nanoparticles to nasal-associated lymphoid tissue (NALT) and lungs. Protein nanoparticles are composed of proteins at high mass-to-carrier ratio, while allowing for biocompatibility and tunable physiochemical properties. They have been demonstrated to be effective vaccines and drug delivery carriers. The surfaces of these carriers can be decorated with coatings and chemical modifications, which can alter transport and immune responses due to their interaction with biological barriers and cells. In this work, we evaluate intranasal localization of engineered surface-coated protein nanoparticles and assess their immune response following vaccination in murine models. To understand the principles behind modifying nanoparticle surface formulations will assist in improving accessibility to the NALT and delivery of protein-based nanocarriers for non-vaccine intranasal delivery. We screened ovalbumin nanoparticles coated with polyethylene glycol (PEG) and layer-by-layer coating of trimethyl chitosan and CpG oligodeoxynucleotide adjuvants delivered intranasally in murine models and compared to unmodified protein nanoparticles. The localization and biodistribution were observed using non-invasive in vivo imaging and for regional localization and tissues using both flow cytometry and immunohistochemistry. Surface-coated nanoparticles were used for intranasal vaccination in a murine model and characterized for the mucosal antigen-specific response, as well as systemic humoral and cellular responses through antibody titers and T-cell activation. The findings and designs from screening coatings with model ovalbumin nanoparticles were incorporated into influenza antigen nanoparticle formulations.  Two influenza antigens (hemagglutinin and matrix protein 2 - (A/California/07/2009(H1N1)) were used to construct a subunit protein nanoparticle vaccine with surface structure control using bioconjugation. A layer-by-layer (LBL) coating approach was used to survey specific formulation based on their administration route. Overall, our findings indicated that LBL surface formulation improved nasal biodistribution and immune response upon intranasal delivery, highlighting a new nanoparticle formulation for nasal vaccines. 

]]> Laura Paige 1 1700577216 2023-11-21 14:33:36 1700577216 2023-11-21 14:33:36 0 0 event BioE PhD Defense Presentation- "Surface Engineering of Protein Nanoparticles for Intranasal Vaccination" - Thomas Pho

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2023-11-29T10:00:00-05:00 2023-11-29T12:00:00-05:00 2023-11-29T12:00:00-05:00 2023-11-29 15:00:00 2023-11-29 17:00:00 2023-11-29 17:00:00 2023-11-29T10:00:00-05:00 2023-11-29T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 10:00:00 2023-11-29 12:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[BioE PhD Defense Presentation- Alex Beach]]> 27917 Advisor:

Dr. Krishnendu Roy (Engineering, Vanderbilt University)

 

Committee Members:

Dr. Andres García (ME, Georgia Institute of Technology)

Dr. Erik Dreaden (BME, Georgia Institute of Technology)

Dr. Valeria Milam (MSE, Georgia Institute of Technology)

Dr. Susan M. Thomas (ME, Georgia Institute of Technology)

 

Utilizing Combinatory Adjuvant-Loaded Chitosan-Derived Nanoparticles for a Joint SARS-CoV-2/Influenza Vaccine

In the wake of the SARS-CoV-2 pandemic and the need for yearly vaccination for flu, there is an ever-growing demand for a single vaccine formulation that can target and immunize against both pathogens. While investigation is ongoing for joint vaccine candidates, the current focus has been mainly on the simultaneous administration of separate vaccines rather than a new hybrid vaccine design. In this work, we have designed and synthesized chitosan and chitosan-IAA-based nanoparticles to use as a platform for combinatorial delivery of multiple vaccine-adjuvants together with soluble delivery of flu and SARS-CoV-2 antigens. Specifically, we have used a combination of the TLR9 agonist CpG and the RLR agonist pUUC. In vitro testing in two distinct primary bone-marrow-derived antigen-presenting cell (APC) cultures demonstrated a strong cell-phenotype-dependent cytokine response to these nanoparticle systems. After administering these with SARS-CoV-2 and H5N1 influenza antigens in a dual-vaccine formulation, we confirmed high pathogen-specific antibody titers in serum and BAL fluid. Our results provide further insights into the impact of immune cell phenotype on vaccine responses and show promise for creating a novel joint subunit vaccine for two prevalent pathogens.

]]> Laura Paige 1 1700577030 2023-11-21 14:30:30 1700577030 2023-11-21 14:30:30 0 0 event BioE PhD Defense Presentation- "Utilizing Combinatory Adjuvant-Loaded Chitosan-Derived Nanoparticles for a Joint SARS-CoV-2/Influenza Vaccine" - Alex Beach

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2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27 14:00:00 2023-11-27 16:00:00 2023-11-27 16:00:00 2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 09:00:00 2023-11-27 11:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PACE Instructional Cluster (ICE) Info Session]]> 35120 PACE’s instructional cluster (ICE) supports educational efforts in scientific computing across campus at no cost to instructors or to students in the class. For more information about ICE, deadlines and application process, please see our ICE homepage. We can also host non-credit workshops requiring computing resources.

If you are teaching a course outside the College of Computing or planning a non-credit workshop, please fill out this application for ICE. If you are teaching a course in the College of Computing, please contact the TSO's instructional team.

We will be holding a drop-in information session about ICE on Wednesday, December 6, 3:00-4:00 on Zoom. Feel free to come to the session at any time if you would like to learn more about how ICE can support your course this spring. You can also contact us at pace-support@oit.gatech.edu with any questions.

]]> mweiner3 1 1700519862 2023-11-20 22:37:42 1700520027 2023-11-20 22:40:27 0 0 event PACE’s instructional cluster (ICE) supports educational efforts in scientific computing across campus at no cost to instructors or to students in the class. For more information about ICE, deadlines and application process, please see our ICE homepage. We can also host non-credit workshops requiring computing resources.

If you are teaching a course outside the College of Computing or planning a non-credit workshop, please fill out this application for ICE. If you are teaching a course in the College of Computing, please contact the TSO's instructional team.

We will be holding a drop-in information session about ICE on Wednesday, December 6, 3:00-4:00 on Zoom. Feel free to come to the session at any time if you would like to learn more about how ICE can support your course this spring. You can also contact us at pace-support@oit.gatech.edu with any questions.

]]>
2023-12-06T15:00:00-05:00 2023-12-06T16:00:00-05:00 2023-12-06T16:00:00-05:00 2023-12-06 20:00:00 2023-12-06 21:00:00 2023-12-06 21:00:00 2023-12-06T15:00:00-05:00 2023-12-06T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-06 03:00:00 2023-12-06 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> Michael Weiner, mweiner3@gatech.edu

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<![CDATA[PhD Defense by Faris Almatouq]]> 27707 School of Physics Thesis Dissertation Defense

 

Presenter:       Faris Almatouq

Title:                Synthesis and Characterization of Hexagonal Boron Nitride for Neutron Radiation Detection

Date:               Tuesday, December 5, 2023

Time:               12:00 p.m.

Location:        Howey N110

 

Committee members:

Dr. Zhigang Jiang, School of Physics, Georgia Institute of Technology (advisor)

Dr. Walter de Heer, School of Physics, Georgia Institute of Technology

Dr. Phillip N. First, School of Physics, Georgia Institute of Technology

Dr. Sharmistha Mukhopadhyay, School of Mechanical Engineering, Georgia Institute of Technology

Dr. Thomas Orlando, School of Chemistry and Biochemistry, Georgia Institute of Technology

 

Abstract: The assessment of radiation impact on astronauts during extravehicular activities is limited to post-mission analysis, using data collected and reported by dosimeter badges. This highlights the necessity for advancements in dosimeter technology, such as the development of systems capable of real-time radiation detection, to enhance the safety of astronauts from radiation exposure. This research focuses on developing such a technology by incorporating graphene field-effect transistors (gFETs) with monoisotopic hexagonal boron nitride (hBN).

The monoisotopic hBN studied in this work was synthesized in-house through a metal flux method using nickel and chromium. The hBN was characterized through various spectroscopic techniques, including Raman, photoluminescence, ultraviolet-visible absorbance, and X-ray diffraction, before and after exposure to neutron irradiation. The study used two types of neutron sources, a deuterium-deuterium neutron generator, and an Americium-Beryllium isotopic source, to observe the effects of neutron irradiation on hBN. It was found that neutron irradiation could induce specific defects in hBN, particularly the VB- defect. Then, monoisotopic hBN was transferred to a gFET to fabricate the proposed device. The resistance of the device was observed to increase in correlation with the total thermal neutron flux. This change in resistance can be attributed to the interaction between the device and alpha particles generated from thermal neutron capture by Boron-10. The ability of this device to detect changes in resistance under neutron irradiation in real time may offer a significant advancement in ensuring astronaut safety by providing real-time monitoring of neutron exposure, which is a critical aspect of cosmic radiation.

]]> Tatianna Richardson 1 1700519661 2023-11-20 22:34:21 1700519661 2023-11-20 22:34:21 0 0 event    Synthesis and Characterization of Hexagonal Boron Nitride for Neutron Radiation Detection

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2023-12-05T12:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05 17:00:00 2023-12-05 19:00:00 2023-12-05 19:00:00 2023-12-05T12:00:00-05:00 2023-12-05T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 12:00:00 2023-12-05 02:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[MS Defense by Sophia Marie Madelone]]> 27707 Sophia Marie Madelone

Advisor: Prof. Mark Losego, Dr. Madhavan Swaminathan

 

will defend a master's thesis entitled,

 

Characterization of Commercial Dielectric Zaristo-700 as a Redistribution Layer Material for Advanced Packaging 


On

 

Thursday, November 30th at 1:00 p.m.

Pettit Room 102A

 Virtually via MS Teams 

https://teams.microsoft.com/l/meetup-join/19%3ameeting_OWY0ZTM0ODQtYWM2YS00NTRjLTlmZWItNWI2YjdlMDU2NTA4%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22db086d94-341c-4a1f-91f3-e63b60463810%22%7d

 

 

Committee

            Prof. Madhavan Swaminathan – School of Electrical Engineering  (co-advisor)
            Prof. Mark Losego – School of Materials Science and Engineering (co-advisor)
            Prof. Mohanalingham Kathaperumal  – School of Electrical Engineering 
           

 

Abstract 

      This body of work, in detail, outlines the fundamental steps taken to characterize a material for novel use in RDL build-up layers for advanced packaging. The material (Zaristo-700) discussed in this thesis was only used in RF applications, and now we are exploring its use in the wiring layers. In the PRC, research into thin films, spin-on films, and many other dielectrics have been published before. It is essential to understand that this work is necessary to establish a “library” or catalog of information on all the materials we use to provide the correct material, depending on the goals of future projects. The material and electrical properties of Zaristo-700 are characterized through JEDEC adhesion testing (Peel test), leakage current measurements on ITO glass slides before and after Highly Accelerated Stress Testing (HAST) treatment, a series of dose tests to document the most optimized pitch-scalability at 8.0 m L/S, and lastly Shadow-Moire warpage studies of one layer and three-layer RDL samples. Leakage current measurements taken before and after HAST stayed at or below 2.0 nA. As we will explore, the CTE and adhesion of Zaristo-700 are excellent and contribute to making a great material for the RDL wiring layers. Taiyo Ink. has stated that this version of the dielectric film accounts for issues such as stability in how long it can sit, delamination during or after curing, delamination during fabrication processes, and so on. Whereas some of the dielectric films of other companies still have these problems. This research is working towards answering the unknowns about this dielectric and how well it will function as a future RDL build-up material through characterization and analysis of its properties. These results are a positive indication for use as an RDL dielectric in advanced packaging

]]> Tatianna Richardson 1 1700519557 2023-11-20 22:32:37 1700519557 2023-11-20 22:32:37 0 0 event Surface Modification of Nb Oxide Anode Materials via Chemical Vapor Deposition (CVD) for Lithium-ion Batteries

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2023-12-01T12:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01 17:00:00 2023-12-01 19:00:00 2023-12-01 19:00:00 2023-12-01T12:00:00-05:00 2023-12-01T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 12:00:00 2023-12-01 02:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Prahalad Murali]]> 27707  

Prahalad Murali

(Advisor: Prof. Madhavan Swaminathan & Co-advisor: Prof. Mark D. Losego)

 

will defend his doctoral thesis entitled,

 

Materials and processes for high conversion ratio high efficiency package embedded inductors for Integrated Voltage Regulators

 

On

Tuesday, November 28 at 1:00 pm

Pettit Microelectronics Building – Room 102 A

And

Via Zoom

https://gatech.zoom.us/j/97718265765?pwd=T3BJN2M5UTVPT2NMUEs0WmJWZTE5UT09

Meeting ID: 977 1826 5765

Passcode: 633456

 

Abstract

Datacenter advancements demand faster and denser chiplets within a single package, driven by the imperative to meet future performance metrics. The pursuit of faster computing has consequently pushed power delivery boundaries to these chiplets. Traditionally, input voltages in data center racks were uniformly converted to 1 V on the PCB, with modifications to design mitigating IR drop caused by path resistances, thereby maintaining overall system efficiency. However, the limitations of this approach have become apparent due to the emergence of larger packages and higher power density requirements facilitated by increasing transistor density and 3D stacking of chiplets.

 

To overcome these challenges, there is a paradigm shift towards bringing power at higher voltages to reduce current, and subsequently, copper losses, which are directly proportional to the square of current (I²). Enabling high input voltages into the package substrate necessitates the integration of a single stage of power conversion into the package. Voltage-down conversion involves incorporating actives like Integrated Voltage Regulator (IVR) chiplets and passives like capacitors and inductors to form a buck converter circuit—an efficient topology for high conversion ratio voltage conversions—integrated into the package.

 

Gallium Nitride (GaN) IVR chiplets are advocated for voltages greater than 5 V due to their wide bandgap compared to Silicon-based Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). The use of GaN FETs mandates inductors capable of handling high currents, current ripples, low losses, and generating high inductance to meet the stringent 12 V - 1 V DC-DC down conversion requirements. Achieving inductor efficiency above 95% and system efficiency exceeding 90% is crucial for this purpose. To meet these efficiency targets, exploration of new inductor designs and materials for the magnetic core is essential. To enhance system efficiency and address IR drop challenges, the inductor should be positioned as close to the chiplet as possible.

 

Current state-of-the-art inductors, integrated into the package core, utilize magnetic pastes for the magnetic core, ensuring compatibility with substrate processing. These inductors generate 2.5 nH of inductance in each of the six phases, capable of handling 8 A current with less than 12 mΩ of total path resistance from the board to the chiplet through the inductor. However, their optimal usage is within the 100-140 MHz range for 1.75 V to 1.08 V DC-DC conversion.

 

The objectives of this research are to address gaps in understanding the impact of metal filler shape and heat treatment on inductor properties. It includes the fabrication of toroidal and spiral inductors, reliability assessment, and the integration of inductors as close to the chiplet as possible. The research aims to develop models, materials, and processes to investigate the structure-property correlation of metal fillers in a metal-polymer composite for high conversion ratio applications, demonstrate and compare toroidal and stacked spiral inductor designs, and showcase a Redistribution Layer (RDL) embedded inductor spanning multiple buildup layers.

 

Committee

 

]]> Tatianna Richardson 1 1700519367 2023-11-20 22:29:27 1700519367 2023-11-20 22:29:27 0 0 event Materials and processes for high conversion ratio high efficiency package embedded inductors for Integrated Voltage Regulators

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2023-11-28T13:00:18-05:00 2023-11-28T15:00:18-05:00 2023-11-28T15:00:18-05:00 2023-11-28 18:00:18 2023-11-28 20:00:18 2023-11-28 20:00:18 2023-11-28T13:00:18-05:00 2023-11-28T15:00:18-05:00 America/New_York America/New_York datetime 2023-11-28 01:00:18 2023-11-28 03:00:18 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[MS Defense by Shineui Hwang]]> 27707 Shineui Hwang

(Advisor: Prof. Meilin Liu)

will defend a master’s thesis entitled,

 

Surface Modification of Nb Oxide Anode Materials via Chemical Vapor Deposition (CVD) for Lithium-ion Batteries

 

On

 

Friday, December 1st at 12:00 p.m.

Virtually via MS Teams at:

https://teams.microsoft.com/l/meetup-join

 

 

Abstract

 

Batteries used for energy storage applications increasingly require higher power and energy densities, with ambitious performance goals such as rapid charging and sustained performance over long-term cycles. Nb-based oxide anode materials, which offer high rate capability, significant volumetric capacity, and stable intercalation with minimal volume expansion, have emerged as promising candidates for next-generation energy storage applications. Due to limited electronic conductivity, however, their potential for electrochemical energy storage has primarily been demonstrated in electrodes with low mass loading (~1 mg cm−2). In this study, a carbon layer is applied to the surface of Nb-based oxides using chemical vapor deposition (CVD) to create a highly interconnected conductive network. This network enhances electron transport in electrodes with a practical mass loading of approximately 8 mg cm−2. In addition to optimized charge transport, the enhanced mechanical strength of the carbon–Nb oxide composite prevents direct contact between the electrode and liquid electrolyte, thereby reducing structural degradation over extended cycles. Systematic optimization of the thickness and quality of the carbon layer in the composite resulted in improved charge transport and reduced structural degradation, enabling high-rate capabilities and excellent stability at high mass loading of active electrode materials. This advancement represents a significant step towards realizing the practical application of Nb-based anode materials in lithium-ion batteries.

 

 

Committee

 

 

]]> Tatianna Richardson 1 1700519267 2023-11-20 22:27:47 1700519267 2023-11-20 22:27:47 0 0 event Surface Modification of Nb Oxide Anode Materials via Chemical Vapor Deposition (CVD) for Lithium-ion Batteries

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2023-12-01T12:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01 17:00:00 2023-12-01 19:00:00 2023-12-01 19:00:00 2023-12-01T12:00:00-05:00 2023-12-01T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 12:00:00 2023-12-01 02:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Venkatavaradan Sunderarajan]]> 27707  

Venkatavaradan Sunderarajan
Advisor: Prof. Suman Das


will defend a doctoral thesis titled,


Multi-Scale Materials Characterization and Analysis of In-Situ Process Monitoring Data towards enabling Multivariate Statistical Process Control

in Laser Powder Bed Fusion Metal Additive Manufacturing


On


Thursday, November 30 at 3:15 p.m.

at MRDC Room 4211

and

 Virtually via Zoom 

https://gatech.zoom.us/j/97282558604?pwd=cS91QUJ5ZWpZZE5SMUh5djc2N3BXZz09
Meeting ID: 972 8255 8604
Passcode: 113736

 

 

Committee

Prof. Suman Das, Advisor, ME/MSE

Prof. Hamid Garmestani, MSE

Prof. Sandra Magnus, AE/MSE/INTA

Prof. Jianjun Shi, ISyE/ME

Prof. Preet Singh, MSE


Abstract
Widespread adoption and industrial scaling of Laser Powder Bed Fusion (L-PBF) Metal Additive Manufacturing (AM) is currently challenged by a variety of issues including dimensional and form errors, undesired (and oftentimes stochastic) porosity, delamination of parts, extreme variations in part properties, undesirable failure rates, and significant costs to optimize processes for gaining acceptable part quality, albeit with limited statistical confidence. Currently accepted industry standards, such as ASTM F3001, do not address the inherent variations present in the parts produced by L-PBF. Such property variations, present even in an extensively researched alloy such as Ti6Al4V, greatly hinder the acceptance of L-PBF to produce mission critical parts without substantially expensive qualification procedures. To date, a significant volume of research has focused on the capabilities of AM, but there is a lack of research focused on its repeatability and reproducibility. The objective of this dissertation is to evaluate variations in post-process multi-scale part characterization and to utilize in-situ process monitoring in an industrial L-PBF Metal AM platform to enable a framework for Qualification, Validation and Verification (QVV) by:

 

i.   Studying variations in static tensile properties of parts manufactured across multiple builds under the same regimen.

ii.  Studying variations in critical dimensional features of multiple parts manufactured in a single build under the same regimen.

iii. Utilizing heterogeneous data input from multi-fidelity in-situ monitoring sensors to develop process control charts using multivariate statistics.

 

The tensile properties thus investigated highlight the variations encountered even while using a combination of machine, process and material that has been fully operationally qualified to produce mission critical parts. Property dependence on controlled process parameters as well as challenges to repeatability and reproducibility in L-PBF Metal AM are presented, and pathways to address the same are proposed. Finer layer thicknesses, coupled with locations either closer to the shielding gas source or at the center of the build plate, even while incorporating powder re-use between successive builds offer the least coefficients of variations in tensile properties.

 

The dimensional measurement of critical geometric features proved that the practically achievable limit of resolution and repeatability for producing thin-walled and thin-gap specimens using this platform is around 500 µm. An effective geometric constraint can be provided by a base to provide tighter control in dimensional variations, although it may not be a design permissible for practical applications. For features with nominal dimensions less than 500 µm, the scatter in the measurements is equal in value or is a low multiple of the largest diameters of the feedstock powder. Therefore, this may pose a challenge that cannot be overcome easily, especially without innovative post-processing methods.  The repeatability of fine feature dimensions is favored by larger powder layer thicknesses, whereas the opposite is generally true for obtaining a smoother surface finish. The build location at the center of the build plate exhibits the tightest control over variations and results in the most predictable outcomes.

 

Four considerations are critical for the successful implementation of a robust in-situ monitoring methodology that can also benefit from scaling up and successful adoption in the production of mission-critical and/or safety-critical AM parts. These include targeting the reliable detection of stochastic flaws representative of real-world applications as opposed to seeded defects; developing methods to collect, analyze and act on data collected over the duration and volume of an entire build; developing process control methods that rely on fundamental statistics with robust and transparent algorithms as opposed to “black-box” ML based algorithms requiring tremendous time and financial investment to actually realize the promise they offer; and interpreting results from less complex statistical algorithms will enable a higher confidence in the detected outcomes as well as a higher likelihood of the eventual method gaining traction for adoption in the manufacturing of service critical parts.

 

Simultaneous usage of multi-fidelity in-situ monitoring sensors enabled an enhanced capture of process signatures to understand deviations and develop corrective actions. 2D-Wavelet transformation-based approach to identify recoater streaking defects from optical images of the powder bed and a Sobel gradient operator-based approach to detect hot and cold spots from photodiode signals are useful examples demonstrating the capability of direct image processing techniques to identify defects encountered during a build. Such methods enable extraction of layer-wise statistical measures for subsequently monitoring the L-PBF Metal AM process via multivariate statistical process control charts.

 

The outcomes of this dissertation provide valuable insights into the inherent complexities of the L-PBF Metal AM process and underscore the challenges in achieving repeatability and reproducibility. Future work can extend the proposed QVV framework using robust in-situ monitoring methodologies to enhance process reliability enabling the widespread industrial adoption of L-PBF Metal AM for to produce mission-critical parts.

 

]]> Tatianna Richardson 1 1700519159 2023-11-20 22:25:59 1700519159 2023-11-20 22:25:59 0 0 event Multi-Scale Materials Characterization and Analysis of In-Situ Process Monitoring Data towards enabling Multivariate Statistical Process Control

in Laser Powder Bed Fusion Metal Additive Manufacturing

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<![CDATA[PhD Proposal by William Griffin]]> 27707 School of Physics Thesis Proposal

 

Presenter:       William Griffin

Title:                Semiconducting Epigraphene on Atomically Flat Silicon Carbide Terraces

Date:               Monday, November 20, 2023

Time:               9:00 a.m.   

Place:              Boggs 1-44

 

Committee:    

Dr. Claire Berger, School of Physics, Georgia Institute of Technology (Advisor)

Dr. Walt de Heer, School of Physics, Georgia Institute of Technology (Advisor)

Dr. Phillip First, School of Physics, Georgia Institute of Technology

Dr. Zhigang Jiang, School of Physics, Georgia Institute of Technology

Dr. Azad Naeemi, School of Electrical and Computer Engineering, Georgia Institute of Technology

 

 

]]> Tatianna Richardson 1 1700518988 2023-11-20 22:23:08 1700518988 2023-11-20 22:23:08 0 0 event Semiconducting Epigraphene on Atomically Flat Silicon Carbide Terraces

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<![CDATA[PhD Defense by Pragna Bhaskar]]> 27707 Pragna Bhaskar
Advisor: Prof. Madhavan Swaminathan

Co-advisor: Prof. Mark D. Losego


will defend her doctoral thesis entitled,


Reliability assessment and demonstration of advanced ultra-low-k dielectric materials for advanced interposers


On


Friday, December 1 at 2:00 p.m.
Pettit Microelectronics Building 102 A&B

and

 Virtually via Zoom

https://gatech.zoom.us/j/97541898638?pwd=NTg5anh2SzAzUEIvZVVHREpINWhWQT09

Meeting ID: 975 4189 8638

Passcode: 136236

 

 

Committee

 


Abstract
The number of connected devices in homes, cars and offices has increased and there is also an increase in advanced data processing algorithms. These have been enabled by artificial intelligence (AI) unprecedented need for ultra-high bandwidth computing. This need for ultra-high bandwidth is driving transistor density on single-chips. Moore’s Law had enabled the scaling and integration of compute, memory, and other functionalities on a single silicon chip by increasing transistor density on-chip at lower cost per transistor. This is known as the System on Chip (SoC) approach.

 

In the recent past, Moore’s law has slowed down and the cost of large SoCs has increased. There are two important reasons for this exponential increase in cost. The first reason is that the cost/mm2 of transistors has continued to increase due to increase in technology complexity. The second reason is that yields have reduced for larger SoCs as the limits of the reticle field are approached. One of the methods to address these requirements is by adopting Heterogeneous Integration. In this approach, separately manufactured dies are integrated onto an advanced interposer which provides better functionality and operating characteristics. These dies need to communicate with high bandwidth density at low energy per bit (EPB). Bandwidth density depends on wiring density, wire length, and signaling data rate on each wire. Signal speed is determined primarily by the dielectric constant. Low wire capacitance can be achieved by shorter wires between dies and low dielectric constant materials. Therefore, there is need for integration of ultra-low k materials in the redistribution wiring layers (RDLs) of the package. Earlier studies involved materials having dielectric constant in the range of 2.65 to 3.2. 

 

It has been reported that when the dielectric constant (k) is reduced from 3.9 to 2.4, the EPB is reduced by 40%. Therefore, the present study evaluates ultra-low-k dielectric materials which have dielectric constant in the range of 2.1 to 2.4 with respect to different reliability aspects. This study describes electrical characterization of these materials by measuring the insertion losses in the range of 10-170 GHz and losses. Typically, the ultra-low-k materials have inert chemistries and there is a possibility of lower adhesion to metal layers. Therefore, there is a need to study chemical reliability. This study involves improving the adhesion between dielectric and metal layer by optimizing plasma processes and curing condition. The effect of Vapor Phase Infiltration (VPI) on adhesion of these materials has been studied. Another aspect of chemical reliability is moisture absorption. This is evaluated by comparing the behavior of these materials before and after highly accelerated stress test (HAST). For the ultra-low-k materials to be suitable for use in RDL having high wiring density, there is need to demonstrate fine line features and formation of vias. Therefore, fabrication of fine line features has been demonstrated on these materials. The effect of seed layer thickness and surface roughness on the resolution of fine lines and spaces has been studied. Methodologies have been developed to measure via dimensions since reliability of vias depends on their dimension. In addition, different methods to measure the coefficient of thermal expansion (CTE) of these thin polymer dielectric films and VPI has been explored as a method to reduce CTE.

 

]]> Tatianna Richardson 1 1700518849 2023-11-20 22:20:49 1700518849 2023-11-20 22:20:49 0 0 event Reliability assessment and demonstration of advanced ultra-low-k dielectric materials for advanced interposers

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<![CDATA[PhD Defense by Peng Li]]> 27707 Title: Cleaning and Learning over Dirty Tabular Data

 

Date: Friday, Dec 1, 2023

Time: 15:00 – 17:00 EST

Location: Teams Link

 

Peng Li

Ph.D. Candidate in Computer Science

School of Computer Science

College of Computing

Georgia Institute of Technology

 

Committee: 

Dr. Xu Chu (advisor) – School of Computer Science, Georgia Institute of Technology

Dr. Kexin Rong (co-advisor) – School of Computer Science, Georgia Institute of Technology

Dr. Joy Arulraj – School of Computer Science, Georgia Institute of Technology

Dr. Shamkant Navathe  School of Computer Science, Georgia Institute of Technology

Dr. Yeye He – Data Management, Exploration and Mining Group, Microsoft Research

 

Abstract: 

The quality of machine learning (ML) applications is only as good as the quality of the data they train on. Unfortunately, real-world data is rarely free of errors, especially for tabular data, which frequently suffers from data issues like missing values, outliers, and inconsistencies. Therefore, data cleaning is widely regarded as an essential step in an ML workflow and an effective way to improve ML performance. However, data cleaning is often a time-consuming task that reportedly takes up to 80% of data scientists' time. Traditional data cleaning approaches often treat data cleaning as a standalone task independently of its downstream applications, which may not effectively improve ML performance and can sometimes even worsen it. Furthermore, it often leads to unnecessary costs for cleaning errors that have a minor impact on ML performance.

 

This dissertation jointly considers data cleaning and machine learning, and focuses on developing algorithms and systems for cleaning and learning over dirty tabular data, with the dual objectives of (1) optimizing downstream ML performance and (2) minimizing human efforts. We start with a CleanML empirical study that systematically evaluates the impact of data cleaning on downstream ML performance. We then present CPClean, a cost-effective human-involved data cleaning algorithm for ML that minimizes human cleaning efforts while preserving ML performance. We subsequently demonstrate DiffPrep, an automatic data preprocessing method that can efficiently select high-quality data preprocessing (cleaning) pipelines to maximize downstream ML performance without human involvement. Finally, to obviate the need for humans to manually program table-restructuring transformations, we present Auto-Tables that can automatically transform tables from non-standard formats into a standard format without any human effort. Combining the works in this dissertation, we build an end-to-end system for cleaning and learning over dirty tabular data.

]]> Tatianna Richardson 1 1700518664 2023-11-20 22:17:44 1700518664 2023-11-20 22:17:44 0 0 event Cleaning and Learning over Dirty Tabular Data

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<![CDATA[PhD Defense by Nicolas Shu]]> 27707 Title: Coupled Auto-Enrollment and Speaker Identification Platform for Real-Time Applications

When: Monday, 4 December 2023, 9:00 EST

Where: Technology Square Research Building (TSRB) 509

PhD Candidate: Nicolas Shu

Committee:

  1. David Anderson (advisor), School of Electrical and Computer Engineering
  2. Matthieu Bloch, School of Electrical and Computer Engineering
  3. Justin Romberg, School of Electrical and Computer Engineering
  4. Larry Heck, School of Electrical and Computer Engineering
  5. Mikle South, Emory School of Medicine
]]> Tatianna Richardson 1 1700518549 2023-11-20 22:15:49 1700518549 2023-11-20 22:15:49 0 0 event Coupled Auto-Enrollment and Speaker Identification Platform for Real-Time Applications

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<![CDATA[PhD Proposal by Shreyas Malakarjun Patil]]> 27707 Title: Leveraging sparsity in deep neural networks for training efficiency, interpretability and transfer learning

 

Date: November 30th 

Time: 10:30 AM

Physical attendance: conference room (Midtown) on Coda 12th floor

Virtual attendance: https://gatech.zoom.us/j/96615684093

 

Shreyas Malakarjun Patil

Machine Learning PhD Student

ECE
Georgia Institute of Technology

 

Committee

1. Dr. Constantine Dovrolis (Advisor)

2. Dr. Ling Liu

3. Dr. Zsolt Kira

 

Abstract

 

Sparse neural networks (NNs) exhibit fewer connections between consecutive layers compared to dense NNs. As a result, sparse NNs have been shown to enhance generalization and computational efficiency. However, the diverse sparse network structures and benefits beyond efficiency and generalization remain largely unexplored. 

 

In this dissertation, I present an exploration of sparse network structures and their ensuing benefits. First, we propose a new method, PHEW, to identify sparse NNs at initialization without using training data. PHEW leads to sparse NNs that learn fast and generalize well, thus enhancing training efficiency. Second, we propose Neural Sculpting to uncover the hierarchically modular task structure in NNs. We iteratively prune units and edges during training and combine it with network analysis to detect modules and infer hierarchy, thereby enhancing NN interpretability. Finally, we plan to examine how efficiently hierarchically modular NNs, that reflect the task’s structure, transfer to new tasks as compared to dense NNs. Given the assumption that the new tasks introduced in transfer learning share similarities with the previous tasks, our investigation will specifically explore the degree of sub-task reuse from the initial tasks. In summary, this dissertation advances the understanding and capabilities of sparse NNs in terms of training efficiency, interpretability, and transfer learning.

]]> Tatianna Richardson 1 1700518226 2023-11-20 22:10:26 1700518410 2023-11-20 22:13:30 0 0 event Leveraging sparsity in deep neural networks for training efficiency, interpretability and transfer learning

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<![CDATA[PhD Defense by Zihao Hu]]> 27707 Title: Learning and Optimization on Geodesic Metric Spaces

Date: Tuesday, Nov 21st, 2023

Time: 12:00pm-2:00pm

 

Location: Coda C1215 Midtown

Teams link

Join conversation

teams.microsoft.com

 

Zihao Hu

Machine Learning Ph.D. Candidate

School of Computer Science

Georgia Institute of Technology

 

Committee

Dr. Jacob Abernethy (Advisor), School of Computer Science, Georgia Institute of Technology

Dr. Santosh Vempala, School of Computer Science, Georgia Institute of Technology

Dr. Molei Tao, School of Mathematics, Georgia Institute of Technology

Dr. Vidya Muthukumar, School of Electrical and Computer Engineering, Georgia Institute of Technology

Dr. Andre Wibisono, Department of Computer Science, Yale University

 

Abstract

There has been growing interest in designing optimization algorithms with convergence guarantees when the parameter space is not a Euclidean set but a Riemannian manifold. This has attracted considerable attention because it allows for the encoding of constraints, and in many cases, it addresses the non-convexity in both the feasible set and the objective function. But thus far, this has been mainly limited to vanilla convex optimization, and there has been limited research in the online setting and in minimax problems, which is the focus of the present work.

 

In the first part, we explore minimizing dynamic regret on Riemannian manifolds. We introduce optimistic mirror descent on manifolds in the online improper learning setting and apply the technique to establish adaptive dynamic regret bounds.

 

In the second part, we consider projection-free (online) optimization on Riemannian manifolds. We illustrate how to design algorithms that rely solely on a linear optimization or separation oracle and how to achieve sub-linear regret on manifolds.

 

Lastly, we consider the problem of the last-iterate convergence of Riemannian extragradient. The result obtained in Euclidean space using the extragradient method is O(1/sqrt{T}). In this study, we demonstrate a similar behavior in the context of the manifold setting.

]]> Tatianna Richardson 1 1700518378 2023-11-20 22:12:58 1700518378 2023-11-20 22:12:58 0 0 event Learning and Optimization on Geodesic Metric Spaces

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<![CDATA[PhD Defense by Jose Magalhaes]]> 27707 Dear faculty members and fellow students,

 

You are cordially invited to attend my dissertation defense on Wednesday, November 29th.

 

Title: Intelligent Data-Driven Aerodynamics Analysis and Optimization of Morphing Configurations

 

Date: Wednesday, November 29th, 2023

Time: 10:00 AM - 11:00 AM EST

Location: Montgomery Knight Building 317 - AE Department  (Physical)    

                  Microsoft Teams Meeting  (Virtual)

                  Meeting ID: 269 631 497 480 

                  Passcode: Pce4wA

 

 

 

Jose Magalhaes

Robotics PhD Candidate

School of Aerospace Engineering

Georgia Institute of Technology

 

Committee:

Dr. Kyriakos Vamvoudakis (Advisor) - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Seth Hutchinson - School of Interactive Computing, Georgia Institute of Technology

Dr. Daniel P. Schrage - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Lakshimi N. Sankar - School of Aerospace Engineering, Georgia Institute of Technology

Dr. Gustavo L. O. Halila - Technology Development – EMBRAER S.A - Brazil

 

Abstract:

The aeronautical industry is continuously looking for more efficient aircraft and provide a reduction on fuel or power consumption while guaranteeing safety, optimality, and stability. The advances of composite materials enable building morphing structures that adapt to a variety of flight and environmental conditions. Airplanes that use morphing technologies can achieve optimal performance and minimize the drag over the entire flight envelope and operate even in dangerous weather conditions.

 

In this dissertation, we propose a data-driven framework to control morphing airfoils in the subsonic flight regime, considering high Reynolds numbers to reach, in efficient and safe way, a shape with improved values of the aerodynamic coefficients. The online solution is based on a data-driven controller combined with a surrogate model and a multi-gradient descent algorithm considering objective functions that are relevant in aerodynamics: increase lift-drag ratio, reduce drag and increase lift. Without full knowledge of the aerodynamic parameters (lift, drag, and pitching moment coefficients), the learning framework searches for an airfoil shape that minimizes a metric of performance associated to drag, lift, and pitching moment coefficients. The solution uses online data to improve the accuracy of the predictions of the aerodynamic coefficients provided by the surrogate model along the trajectory. The optimization framework focuses on subtle airfoil deformations to assure a smooth trajectory between the initial and the final shape. Finally, the efficacy and the robustness of our proposed solution is shown in numerical examples, resulting in a significant reduction in the prediction error.

 

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<![CDATA[PhD Defense by Nithin Nedumthakady ]]> 27707  

Nithin Nedumthakady 

(Advisor: Prof. Vanessa Smet, Co-advisor: Prof. Rao Tummala) 

 

will defend his doctoral thesis entitled, 

 

Magnetoelectrodeposition of Copper-Graphene Composites:  

A New Method to Tailor Properties of Copper in Advanced Packaging 

 

on 

 

Monday, December 4th, 2023 at 1:00PM EST 

Pettit Microelectronics Building – Room 102A 

and 

Via Microsoft Teams 


https://teams.microsoft.com/l/meetup-join/19%3ameeting_Nzk2MjY3YjUtYzcxZC00ZTJiLWI5NjYtN2Q0ZWVmNzRhZTRh%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%226601c060-850a-4925-9bf3-b07f7d7f7982%22%7d  

Meeting ID: 224 519 609 146
Passcode: ofHwmT  

 

As device performance continues to scale, so too does the need for increased integration of metals, specifically electrodeposited copper (Cu), which has traditionally been the conductor of choice for many electronic applications due to its low electrical resistivity (1.72 μΩcm), excellent thermal conductivity (398 W/mK), ease of integration allowing for patterning of interconnects and thermal structures on package substrates, and relatively low cost. However, the biggest drawback of Cu within electronic packages remains its relatively high coefficient of thermal expansion (CTE) of ~17 ppm/K compared to traditional semiconductor and substrate core materials: ~3 ppm/K for Si, ~4 ppm/K for silicon carbide, ~4.5 ppm/K for gallium nitride (GaN), and a tailorable ~3 - 9.5 ppm/K for glass. This CTE mismatch prevents the desired increased integration and density of Cu within electronic packages. For example, fully-filled through-package vias provide incredible performance enhancements over conformal ones, particularly at high aspect ratios; however, these vias have various critical stress points due to CTE mismatches between the substrate and the via Cu, and thus limits and constrains what can be designed and manufactured reliably today. In parallel, thermal densification of electronic packages is driving the need for more integrated, near-junction passive heat spreading solutions such as thermal vias or heat slugs. However, the amount of metal, specifically Cu, that can be integrated within electronic packages is limited by CTE-mismatch driven thermomechanical stresses that induce warpage, delamination, or, more severely, cracking of semiconductor devices. Materials such as Cu-Mo-Cu or Cu-W have been explored to help mitigate CTE mismatch, but while such materials may mitigate stress, they come with the tradeoff of deteriorated electrical and thermal performance. Thus, the best way to design a material that meets or exceeds the desired properties for advanced packages is through the development of metal matrix composites (MMCs) where the reinforcement material has properties that exceed that of Cu. 

                 

Graphene (Gr) reinforcement of metals has recently gained momentum to not only enhance electrical, thermal, and mechanical properties but also control the metal matrix composites' grain structure and its evolution at the nanoscale. Specifically, electrodeposited copper-graphene (CuGr) composites have been explored as a material that maintains or exceeds all the electrical, thermal, ease of use, and cost benefits of Cu while retaining electronic package processability. The final composition is mainly governed by the initial volume loading of Gr in the plating bath and any applied agitation methods, giving, so far, limited returns in terms of property improvements. Achieving the theoretical maximum material performance requires 1) a high Gr relative content, 2) homogeneous dispersion of Gr throughout the composite, and 3) controlled alignment of Gr within the material. To address this grand challenge, a novel magneto-electrodeposition process is proposed in this paper wherein a low-magnitude magnetic field is applied during plating to tailor the microstructure, composition and, subsequently, the material properties of CuGr composites. 

 

This thesis will focus on assessing the effect of applied magnetic fields on electrodeposited copper-graphene composites in terms of their material composition, microstructure, morphology, and subsequent electrical, mechanical, and thermomechanical properties for use in next-generation advanced packaging. Key results will demonstrate the effects of magnetic fields on graphene, establish theories for the effects of Gr-reinforcement in Cu matrices, experimental setup, methodology, and proof-of-concept for magneto-electrodeposition of copper-graphene composites, characterization of morphology and mechanical and electrical property improvements, theoretical modeling of potential property improvements of graphene-reinforcement of copper, and finite-element modeling to evaluate the potential benefits of copper-graphene composites in various advanced packaging applications. 

 

Committee:  

 

 

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A New Method to Tailor Properties of Copper in Advanced Packaging 

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<![CDATA[PhD Defense by Aashray Narla]]> 27707  Aashray Narla

Advisor: Prof. Gleb Yushin

 

 

will defend his doctoral thesis entitled,

 

 

Borohydride-based Solid Electrolytes And Polymer Composite Separators For Lithium-ion Batteries

 

 

On

 

Friday, December 1st at 11:00 a.m.

 

 Virtually via Zoom

Closed Meeting

 

Committee:

Prof. Gleb Yushin - School of Materials Science and Engineering (Advisor)

Prof. Preet Singh - School of Materials Science and Engineering

Prof. Faisal Alamgir - School of Materials Science and Engineering

Prof. Seung Soon Jang - School of Materials Science and Engineering

Prof. Alexander Alexeev - School of Mechanical Engineering

 

Abstract:

 

Lithium-ion batteries (LIBs) have garnered a lot of interest over the past decade due to their high-energy and power density, prolonged cyclability and long shelf-life. While electric vehicles (EVs) and portable electronics necessitate long range and battery life respectively, we are reaching the limits of energy densities of conventional LIBs that use intercalation active materials and liquid electrolytes. As the current LIB technology additionally relies on highly flammable and toxic electrolytes that are detrimental to the environment, solid electrolytes LIBs have gained more interest over the past years. The solid-state LIBs may offer higher energy densities, lower toxicity and lower flammability compared to their liquid electrolyte equivalents. However, current solid-state electrolytes (SSE) suffer from poor ionic conductivity, low volumetric density, high cost, complicated synthesis, and slow manufacturability at high yields.

 

In this work, we explore low-melting point anion-substituted/doped borohydride SSEs synthesized by a novel melt-synthesis process capable of being quickly manufacturable at high yields. We systematically investigate the structure and composition of various borohydride SSEs and study the key electrochemical properties such as critical current density to realize their use in all solid-state LIBs. We further fabricate all solid-state LIBs using the melt infiltration method, to assess the borohydride solid electrolyte performance with various LIB active materials. The cycling data of such cells presented similar voltage profiles and capacity retentions to the cells of the same electrodes with liquid organic electrolytes. The promising performance characteristics of such cells will open new opportunities for the accelerated adoption of all solid-state LIBs for safer electric vehicles (EVs).

 

Additionally to the work on SSEs, we study separators for conventional LIBs. Current LIB technology uses separators made from polyolefins, such as polypropylene and polyethylene, which generally tend to suffer from low porosity, low wettability, and slow ionic conductivity and tend to perform poorly against heat-triggering reactions that may cause potentially catastrophic thermal event issues, such as fire. To overcome these limitations, in this dissertation, we report that a porous composite membrane consisting of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers functionalized with nanodiamonds (NDs) that can realize a more thermally resistant, mechanically robust, and ionically conductive separator. We systematically investigate the role of NDs in the polymer matrix of the membrane to improve the thermal, mechanical, crystalline, and electrochemical properties of the composites. Taking advantages of these mechanistic characteristics, the ND-functionalized nanofiber separator enables high-capacity and stable cycling of lithium anode cells with LiNi0.8Mn0.1Co0.1O2 (NMC811) as the cathode, much superior to those using conventional polyolefin separators in otherwise identical cells.

 

]]> Tatianna Richardson 1 1700517387 2023-11-20 21:56:27 1700517387 2023-11-20 21:56:27 0 0 event Borohydride-based Solid Electrolytes And Polymer Composite Separators For Lithium-ion Batteries

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<![CDATA[PhD Defense by Moyosore Afolabi ]]> 27707 School of Civil and Environmental Engineering

Ph.D. Thesis Defense Announcement

Synthesis of Two-Dimensional Nanomaterials for Contaminant Removal, Resource Recovery, and Ion-selective Monitoring 

by 

Moyosore Afolabi 

 

Advisor(s): 

Dr. Yongsheng Chen (CEE) 

Committee Members: 

Dr. Sotira Yiacoumi (CEE), Dr. Xing Xie (CEE), Dr. Katherine Graham(CEE), Dr. Zhaohui Tong (ChBE), Dr. Dequan Xiao (University of New Haven) 

 

Date &Time: Monday, December 4th, 2023, 9:00 AM - 11:00 AM 

 

Location: DEEL 303, MS teams 

 

   To address the escalating demands of a rising global population gravitating toward urban centers, the imperative for sustainable practices in managing food, water, and energy is evident. Wastewater bears both emerging micropollutants (EMPs) such as pharmaceuticals with unknown health risks, also harbors resources crucial for sustainable agriculture (nitrogen, phosphorus, etc.)  and manufacturing (lithium). Leveraging the potential of two-dimensional nanomaterials becomes instrumental in purifying water and selectively sensing lithium ion, and extracting resources from various municipal and industrial wastewater and brines. 
 
   In this thesis, Graphene oxide (GO) and titanium carbide MXenes (Ti3C2Tx) are synthesized and tuned to address environmental challenges, specially focusing on  emerging pollutant removal, nutrient salt resource recovery, and real-time lithium-ion monitoring in water. 
In the first part of our work, the impact of MXene synthesis conditions on surface chemistry and adsorption on antibiotics on MXene membranes is investigated. Through systematic material characterization, adsorption experiments, and density functional theory (DFT) calculations, favorable surface chemistry and synthesis conditions were identified for adsorption of antibiotics. 
   In the subsequent phase of our work, GO membranes were modified with hydrophilic cellulose nanocrystals (CNC) to enable the hybrid membrane. This modification enhances water permeability, antibiotics rejection, and high nutrient salt recovery. 
   The final section of this thesis focuses on lithium ion-selective electrodes (ISE) sensors for precise lithium quantification in wastewater. A MXene-SO3H coating is applied to the Li+ sensor, resulting in heightened sensitivity, rapid response time, and prolonged durability when deployed in wastewater and brine environments. This comprehensive research contributes valuable insights and practical solutions to the pressing challenges associated with the sustainable management of water resources and the mitigation of environmental pollutants.
 

]]> Tatianna Richardson 1 1700514780 2023-11-20 21:13:00 1700514780 2023-11-20 21:13:00 0 0 event Synthesis of Two-Dimensional Nanomaterials for Contaminant Removal, Resource Recovery, and Ion-selective Monitoring 

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<![CDATA[PhD Defense by Jacob Logas]]> 27707 Casualizing Privacy: Bridging the Gap between Anti-Facial Recognition and Everyday Motives for Sharing

  

Jacob Logas
Ph.D. Student in Computer Interaction
School of Interactive Computing
Georgia Institute of Technology 

 

Date: December 1st, 2023

Time:  3:00 pm

Location:
 

Physical: TBD
Virtual: https://gatech.zoom.us/j/91047694579?pwd=OE9BS3E4WWMvNnlQNWxobTYrQjZ2Zz09

Committee
Rosa Arriaga (Advisor) - School of Interactive Computing, Georgia Institute of Technology
Sauvik Das (Advisor) - Human-Computer Interaction Institute, Carnegie Mellon University
Thad Starner
Polo Chau
Annie Anton
Kelley Caine

 

Abstract:
Advancements in computer vision over the past decade have generated an infrastructure for effortless and ubiquitous surveillance through facial recognition. Online users, in turn, face challenges in maintaining anonymity as their faces become tools to index their activities across various social networks. This intrusion into individual privacy not only compromises personal development but also denies individuals respite from normative social attitudes, including those related to political opinions and sexuality.

While previous efforts have sought to provide users with tools to protect their privacy online, these systems are often either underutilized or reserved for extreme circumstances. This limited adoption can be attributed, in part, to a historical emphasis on technical efficacy rather than human factors. My research addresses this gap by focusing on how anti-facial recognition obfuscation design can transition towards casual use, promoting its integration into users' everyday digital interactions.

In the three studies detailed in this document, I approach anti-facial recognition obfuscation with the overarching goal of prioritizing the user. In the first two studies, I emphasize the importance of understanding and addressing user needs, placing their preferences and concerns at the forefront of anti-facial recognition obfuscation advancement. By integrating these considerations, designers can develop solutions that seamlessly integrate into users' daily activities, offering effective protection while aligning with their primary goals. Additionally, designing obfuscation tools that cater to users' motivations, such as image sharing for social interaction and self-expression, facilitates the casual use of these techniques. Ultimately, this research aims to advocate for anti-facial recognition tools that empower individuals to safeguard their privacy in the face of the increasing surveillance prevalent in today's digital landscape.

 
 

]]> Tatianna Richardson 1 1700512116 2023-11-20 20:28:36 1700512116 2023-11-20 20:28:36 0 0 event Casualizing Privacy: Bridging the Gap between Anti-Facial Recognition and Everyday Motives for Sharing

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<![CDATA[CAREing Paws at the Library ]]> 28817 Are you stressed out? Final exams got you down? 

Take a break and relax with registered therapy dogs from CAREing Paws! Volunteers will be at the Library to offer the community a chance to spend relaxing downtime with furry friends.

]]> Jason Wright 1 1700499767 2023-11-20 17:02:47 1700499951 2023-11-20 17:05:51 0 0 event Are you stressed out? Final exams got you down? 

]]>
2023-12-05T11:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05 16:00:00 2023-12-05 19:00:00 2023-12-05 19:00:00 2023-12-05T11:00:00-05:00 2023-12-05T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 11:00:00 2023-12-05 02:00:00 America/New_York America/New_York datetime <![CDATA[]]> 672413 672413 image <![CDATA[PAWS dec 5.png]]> image/png 1700499919 2023-11-20 17:05:19 1700499919 2023-11-20 17:05:19
<![CDATA[Physics of Living Systems (PoLS) Seminar - Prof. Andrea Giometto]]> 30957 Speaker: Prof. Andrea Giometto

Host: Prof. Peter Yunker

Title: Evolutionary dynamics of non-motile cells growing on surfaces

Abstract:

Surface-associated microbial populations are ubiquitous in nature and display evolutionary dynamics that are not yet well characterized, despite their importance to human health and technology. Dense populations of non-motile microbes expand on surfaces by cell growth and division, while interacting mechanically with neighboring ones. In this talk, I will show that mechanical forces among proliferating cells reduce the power of natural selection in microbial colonies, prolonging the survival of deleterious mutations and reducing the rate at which beneficial mutations expand in these populations. These mechanical interactions also favor the maintenance of genetic diversity in colonies growing in time-varying environments. Additionally, I will present evidence that evolutionary adaptation can change the way in which cells interact mechanically with each other. By repeatedly propagating cells from the periphery of Saccharomyces cerevisiae colonies and using them to initiate new colonies, we have observed significant changes in cell shape and budding polarity, with cells becoming progressively more elongated with time. These adaptations lead to altered mechanical interaction between cells and may promote faster colony expansion. The evolutionary insights from our research may have implications for our understanding of pathogenic yeast strains, many of which are characterized by an elongated cell shape that is presumed to enhance their ability to infiltrate host tissues.

]]> Shaun Ashley 1 1692830059 2023-08-23 22:34:19 1700494699 2023-11-20 15:38:19 0 0 event Surface-associated microbial populations are ubiquitous in nature and display evolutionary dynamics that are not yet well characterized, despite their importance to human health and technology. Dense populations of non-motile microbes expand on surfaces by cell growth and division, while interacting mechanically with neighboring ones. In this talk, I will show that mechanical forces among proliferating cells reduce the power of natural selection in microbial colonies, prolonging the survival of deleterious mutations and reducing the rate at which beneficial mutations expand in these populations. These mechanical interactions also favor the maintenance of genetic diversity in colonies growing in time-varying environments. Additionally, I will present evidence that evolutionary adaptation can change the way in which cells interact mechanically with each other. By repeatedly propagating cells from the periphery of Saccharomyces cerevisiae colonies and using them to initiate new colonies, we have observed significant changes in cell shape and budding polarity, with cells becoming progressively more elongated with time. These adaptations lead to altered mechanical interaction between cells and may promote faster colony expansion. The evolutionary insights from our research may have implications for our understanding of pathogenic yeast strains, many of which are characterized by an elongated cell shape that is presumed to enhance their ability to infiltrate host tissues.

]]>
2023-11-28T15:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28 20:00:00 2023-11-28 21:00:00 2023-11-28 21:00:00 2023-11-28T15:00:00-05:00 2023-11-28T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 03:00:00 2023-11-28 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> 672412 672412 image <![CDATA[Andrea Giometto]]> image/jpeg 1700494559 2023-11-20 15:35:59 1700494624 2023-11-20 15:37:04
<![CDATA[ISyE Seminar - Bahar Taskesen ]]> 34977 Title:

Reliable Data-driven Decision Making

Abstract:

We are witnessing a remarkable surge in data availability across various domains, including medicine, education, policy-making, marketing, civics, and many more. This data deluge has created opportunities for developing intelligent systems capable of implementing highly precise and personalized decisions at unprecedented scales. Simultaneously, the application of machine learning in areas such as criminal justice and health care, which carry significant consequences for individuals, has prompted inquiries into the appropriate design of these systems to ensure alignment with our societal values. In this talk, I will use optimal transport (OT), which seeks the most efficient way of morphing one distribution into another one, as a tool to model and audit data-driven decision-making systems. First, we will see how OT gives rise to a rich class of data-driven distributionally robust optimization (DRO) models, which study worst-case risk minimization problems under distributional ambiguity. We will then shift our focus to an auditing perspective and see how OT can naturally facilitate a statistical test for the algorithmic fairness of pre-trained machine learning models. A significant yet unexplored aspect of OT is its computational complexity. Addressing this gap, we will see the computational complexity of generic OT problems. Later, we will see that even though generic OT problems are computationally hard, we can develop reliable data-driven decision-making models that are tractable in static and dynamic environments and would bring out-of-sample guarantees. In particular, we will see the optimality of linear policies in OT-based robust linear-quadratic control problems with imperfect state observations, and we will show that these policies can be computed efficiently using dynamic programming, Kalman filtering, and automatic differentiation.

Bio:

Bahar Taşkesen is a 5th-year Ph.D. candidate in the Risk Analytics and Optimization Lab at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, under the supervision of Daniel Kuhn. She obtained her Bachelor's degree in Electrical and Electronics Engineering from Middle East Technical University in Ankara, Turkey, in 2018. Her research interests center around data-driven decision-making under uncertainty, large-scale stochastic optimization, and statistical inference. She is particularly interested in exploring algorithmic fairness and robustness and their applications in operations management, control, and machine learning. Her work has implications for the development and deployment of responsible AI systems.

]]> Julie Smith 1 1700485476 2023-11-20 13:04:36 1700485476 2023-11-20 13:04:36 0 0 event Abstract:

We are witnessing a remarkable surge in data availability across various domains, including medicine, education, policy-making, marketing, civics, and many more. This data deluge has created opportunities for developing intelligent systems capable of implementing highly precise and personalized decisions at unprecedented scales. Simultaneously, the application of machine learning in areas such as criminal justice and health care, which carry significant consequences for individuals, has prompted inquiries into the appropriate design of these systems to ensure alignment with our societal values. In this talk, I will use optimal transport (OT), which seeks the most efficient way of morphing one distribution into another one, as a tool to model and audit data-driven decision-making systems. First, we will see how OT gives rise to a rich class of data-driven distributionally robust optimization (DRO) models, which study worst-case risk minimization problems under distributional ambiguity. We will then shift our focus to an auditing perspective and see how OT can naturally facilitate a statistical test for the algorithmic fairness of pre-trained machine learning models. A significant yet unexplored aspect of OT is its computational complexity. Addressing this gap, we will see the computational complexity of generic OT problems. Later, we will see that even though generic OT problems are computationally hard, we can develop reliable data-driven decision-making models that are tractable in static and dynamic environments and would bring out-of-sample guarantees. In particular, we will see the optimality of linear policies in OT-based robust linear-quadratic control problems with imperfect state observations, and we will show that these policies can be computed efficiently using dynamic programming, Kalman filtering, and automatic differentiation.

 

]]>
2023-12-05T11:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05 16:00:00 2023-12-05 17:00:00 2023-12-05 17:00:00 2023-12-05T11:00:00-05:00 2023-12-05T12:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 11:00:00 2023-12-05 12:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Gradescope for Final Exams]]> 36478 This workshop will offer guidance of assignments that are paper-based.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for viewing feedback.

In this workshop you will learn how to: -Set up assignments where students can submit freeform work

Friday, December 1, 1:00 PM (EDT)

Register

 

 

 

 

 

 

]]> twagner35 1 1700258113 2023-11-17 21:55:13 1700258374 2023-11-17 21:59:34 0 0 event This workshop will offer guidance of assignments that are paper-based.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for viewing feedback.

In this workshop you will learn how to: -Set up assignments where students can submit freeform work

  • Grade your final exams on Gradescope
  • Make rubric changes as you grade - changes apply to previously graded work to maintain consistency
  • Write each comment only once - apply previously used comments with a click
  • Use ‘assignment analytics’ to gain insight into student learning

Friday, December 1, 1:00 PM (EDT)

Register

]]>
2023-12-01T13:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01T14:00:00-05:00 2023-12-01 18:00:00 2023-12-01 19:00:00 2023-12-01 19:00:00 2023-12-01T13:00:00-05:00 2023-12-01T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 01:00:00 2023-12-01 02:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> This workshop will offer guidance of assignments that are paper-based.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for viewing feedback.

In this workshop you will learn how to: -Set up assignments where students can submit freeform work

  • Grade your final exams on Gradescope
  • Make rubric changes as you grade - changes apply to previously graded work to maintain consistency
  • Write each comment only once - apply previously used comments with a click
  • Use ‘assignment analytics’ to gain insight into student learning

Friday, December 1, 1:00 PM (EDT)

Register

 

 

 

 

 

 

]]>
<![CDATA[Register Here]]>
<![CDATA[Getting Started with Gradescope]]> 36478 This one-hour workshop will focus on how you can use Gradescope to deliver and grade your assignments that are paper-based, fully online, and a combination of the two.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for submitting assignments and viewing feedback.

In this workshop, you will learn how to:

Tuesday, December 12, 3:00 PM (EDT)

Register

 

 

 

 

 

]]> twagner35 1 1700257844 2023-11-17 21:50:44 1700258052 2023-11-17 21:54:12 0 0 event This one-hour workshop will focus on how you can use Gradescope to deliver and grade your assignments that are paper-based, fully online, and a combination of the two.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for submitting assignments and viewing feedback.

In this workshop, you will learn how to:

  • Set up assignments where students can submit freeform work (no printers or templates needed)
  • Grade your existing exams and homework on Gradescope
  • Make rubric changes as you grade - changes apply to previously graded work to maintain consistency
  • Write each comment only once - apply previously used comments with a click
  • Use ‘assignment analytics’ to gain insight into student learning

Tuesday, December 12, 3:00 PM (EDT)

Register

]]>
2023-12-12T15:00:00-05:00 2023-12-12T16:00:00-05:00 2023-12-12T16:00:00-05:00 2023-12-12 20:00:00 2023-12-12 21:00:00 2023-12-12 21:00:00 2023-12-12T15:00:00-05:00 2023-12-12T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-12 03:00:00 2023-12-12 04:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> This one-hour workshop will focus on how you can use Gradescope to deliver and grade your assignments that are paper-based, fully online, and a combination of the two.

We will also cover the grading and rubric-building workflow on Gradescope and walk attendees through the instructor interface for creating an assignment and student interface for submitting assignments and viewing feedback.

In this workshop, you will learn how to:

  • Set up assignments where students can submit freeform work (no printers or templates needed)
  • Grade your existing exams and homework on Gradescope
  • Make rubric changes as you grade - changes apply to previously graded work to maintain consistency
  • Write each comment only once - apply previously used comments with a click
  • Use ‘assignment analytics’ to gain insight into student learning

Tuesday, December 12, 3:00 PM (EDT)

Register

 

 

 

 

 

]]>
<![CDATA[Register Here]]>
<![CDATA[New VoiceThread: simpler, more accessible, and more powerful]]> 36478 In this session, participants will see a tour of the New VoiceThread features and media player interface. There will be an open Q&A throughout the demo.

Tuesday, November 28, 1:00 pm (EDT)

REGISTER

 

 

 

 

]]> twagner35 1 1700257657 2023-11-17 21:47:37 1700257778 2023-11-17 21:49:38 0 0 event In this session, participants will see a tour of the New VoiceThread features and media player interface. There will be an open Q&A throughout the demo.

Tuesday, November 28, 1:00 pm (EDT)

REGISTER

]]>
2023-11-28T13:00:00-05:00 2023-11-28T14:00:00-05:00 2023-11-28T14:00:00-05:00 2023-11-28 18:00:00 2023-11-28 19:00:00 2023-11-28 19:00:00 2023-11-28T13:00:00-05:00 2023-11-28T14:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 01:00:00 2023-11-28 02:00:00 America/New_York America/New_York datetime <![CDATA[REGISTER]]> In this session, participants will see a tour of the New VoiceThread features and media player interface. There will be an open Q&A throughout the demo.

Tuesday, November 28, 1:00 pm (EDT)

REGISTER

 

 

 

 

]]>
<![CDATA[REGISTER]]>
<![CDATA[Gradescope Bubble Sheets]]> 36478 Join us for an online workshop and learn how instructors use Gradescope. The workshop will offer guidance on using Gradescope Bubble Sheets (as a scantron replacement). You will learn how to digitally create answer keys, easily edit bubbling mistakes electronically, provide students with feedback, and return graded work electronically.

Interested in learning more? Register today! If you can't attend live, register to receive a follow-up email with a recording.

*Please use your email associated with your Gradescope account, if you have one.

Monday, November 27, 11:00 am - 12:00 pm (EDT)

Register Here

 

 

]]> twagner35 1 1700257311 2023-11-17 21:41:51 1700257630 2023-11-17 21:47:10 0 0 event Join us for an online workshop and learn how instructors use Gradescope. The workshop will offer guidance on using Gradescope Bubble Sheets (as a scantron replacement). You will learn how to digitally create answer keys, easily edit bubbling mistakes electronically, provide students with feedback, and return graded work electronically.

Interested in learning more? Register today! If you can't attend live, register to receive a follow-up email with a recording.

*Please use your email associated with your Gradescope account, if you have one.

Monday, November 27, 11:00 am - 12:00 pm (EDT)

Register Here

]]>
2023-11-27T11:00:00-05:00 2023-11-27T12:00:00-05:00 2023-11-27T12:00:00-05:00 2023-11-27 16:00:00 2023-11-27 17:00:00 2023-11-27 17:00:00 2023-11-27T11:00:00-05:00 2023-11-27T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 11:00:00 2023-11-27 12:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> Join us for an online workshop and learn how instructors use Gradescope. The workshop will offer guidance on using Gradescope Bubble Sheets (as a scantron replacement). You will learn how to digitally create answer keys, easily edit bubbling mistakes electronically, provide students with feedback, and return graded work electronically.

Interested in learning more? Register today! If you can't attend live, register to receive a follow-up email with a recording.

*Please use your email associated with your Gradescope account, if you have one.

Monday, November 27, 11:00 am - 12:00 pm (EDT)

Register Here

 

 

]]>
<![CDATA[Register Here]]>
<![CDATA[Kaltura Essentials LMS Training]]> 36478 This webinar will combine all LMS Extension Essentials and intended for all users using the Moodle, Canvas, BB and D2L extensions. 

Tuesday, November 21, 10:00am –12:00pm (EDT) 

REGISTER

Name: Georgia Tech (If prompted for a passcode, please use 53217772)

]]> twagner35 1 1700257148 2023-11-17 21:39:08 1700257280 2023-11-17 21:41:20 0 0 event This webinar will combine all LMS Extension Essentials and intended for all users using the Moodle, Canvas, BB and D2L extensions. 

Tuesday, November 21, 10:00am –12:00pm (EDT) 

REGISTER

Name: Georgia Tech (If prompted for a passcode, please use 53217772)

]]>
2023-11-21T10:00:00-05:00 2023-11-21T12:00:00-05:00 2023-11-21T12:00:00-05:00 2023-11-21 15:00:00 2023-11-21 17:00:00 2023-11-21 17:00:00 2023-11-21T10:00:00-05:00 2023-11-21T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-21 10:00:00 2023-11-21 12:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> This webinar will combine all LMS Extension Essentials and intended for all users using the Moodle, Canvas, BB and D2L extensions. 

Tuesday, November 21, 10:00am –12:00pm (EDT) 

REGISTER

Name: Georgia Tech (If prompted for a passcode, please use 53217772)

]]>
<![CDATA[Register Here]]>
<![CDATA[Introduction to LabArchives - Research Edition]]> 36478
An introduction of the benefits that LabArchives offers researchers and how it can easily be integrated into your research workflow.
  • Thursday, November 30, 1:00 PM (EDT)
 
Register
]]> twagner35 1 1700256371 2023-11-17 21:26:11 1700257059 2023-11-17 21:37:39 0 0 event An introduction of the benefits that LabArchives offers researchers and how it can easily be integrated into your research workflow.
  • Thursday, November 30, 1:00 PM (EDT)
 
Register
]]>
2023-11-30T13:00:00-05:00 2023-11-30T14:00:00-05:00 2023-11-30T14:00:00-05:00 2023-11-30 18:00:00 2023-11-30 19:00:00 2023-11-30 19:00:00 2023-11-30T13:00:00-05:00 2023-11-30T14:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 01:00:00 2023-11-30 02:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]>
An introduction of the benefits that LabArchives offers researchers and how it can easily be integrated into your research workflow.
  • Thursday, November 30, 1:00 PM (EDT)
 
Register
]]>
<![CDATA[Register Here]]>
<![CDATA[Respondus 4 and the Test Bank Network: Quickly Create Online Exams]]> 36478 Find out how Respondus 4 allows you to create and manage exams that can be printed to paper or published directly to your LMS, and how the Test Bank Network enables instructors to create online tests from official publisher test banks.

Tuesday, December 5 at 1:00 pm (EDT)

Register

 

 

 

]]> twagner35 1 1700256904 2023-11-17 21:35:04 1700257028 2023-11-17 21:37:08 0 0 event Find out how Respondus 4 allows you to create and manage exams that can be printed to paper or published directly to your LMS, and how the Test Bank Network enables instructors to create online tests from official publisher test banks.

Tuesday, December 5 at 1:00 pm (EDT)

Register

 

]]>
2023-12-05T13:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05 18:00:00 2023-12-05 19:00:00 2023-12-05 19:00:00 2023-12-05T13:00:00-05:00 2023-12-05T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 01:00:00 2023-12-05 02:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> Find out how Respondus 4 allows you to create and manage exams that can be printed to paper or published directly to your LMS, and how the Test Bank Network enables instructors to create online tests from official publisher test banks.

Tuesday, December 5 at 1:00 pm (EDT)

Register

 

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<![CDATA[Register Here]]>
<![CDATA[HP Trees Atlanta Tree Planting Volunteer]]> 35695 The Georgia Tech Honors Program Leadership Council is partnering with Trees Atlanta, a local environmental nonprofit that “protects and improves Atlanta’s urban forest” to host a tree planting event in Mechanicsville on November 18th from 9 am to 12 pm. Space is limited to 20 Honors Program students. Come help to sustain Atlanta’s urban forest by planting trees, digging holes, untangling roots, and more. See the registration website for more event logistics.

Breakfast will be provided at 8am in the Honors Program office lounge, and then we will be leaving at 8:30am from West Village on a charter bus. We will be back on campus by 12:30pm.

Registration through the Trees Atlanta signup website is required to participate in this event. Go to https://shorturl.at/dfgR2 to register.

The food registration form is also required so we can order enough food. Go to https://shorturl.at/kKRW7 to register.

]]> aanderson75 1 1697833847 2023-10-20 20:30:47 1700249021 2023-11-17 19:23:41 0 0 event The Georgia Tech Honors Program Leadership Council is partnering with Trees Atlanta, a local environmental nonprofit that “protects and improves Atlanta’s urban forest” to host a tree planting event in Mechanicsville on November 18th from 9 am to 12 pm. Space is limited to 20 Honors Program students. Come help to sustain Atlanta’s urban forest by planting trees, digging holes, untangling roots, and more. See the registration website for more event logistics.

Breakfast will be provided at 8am in the Honors Program office lounge, and then we will be leaving at 8:30am from West Village on a charter bus. We will be back on campus by 12:30pm.

Registration through the Trees Atlanta signup website is required to participate in this event. Go to https://shorturl.at/dfgR2 to register.

The food registration form is also required so we can order enough food. Go to https://shorturl.at/kKRW7 to register.

]]>
2023-11-18T09:00:00-05:00 2023-11-18T12:00:00-05:00 2023-11-18T12:00:00-05:00 2023-11-18 14:00:00 2023-11-18 17:00:00 2023-11-18 17:00:00 2023-11-18T09:00:00-05:00 2023-11-18T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-18 09:00:00 2023-11-18 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> honorsprogram@gatech.edu

]]>
672195 672195 image <![CDATA[HP Tree Planting Wide Redo.png]]> A flyer for the Honors Program tree planting volunteer event on November 18th, 2023. 

]]> image/png 1698417331 2023-10-27 14:35:31 1698417331 2023-10-27 14:35:31
<![CDATA[Volleyball vs. Syracuse]]> 36418 Volleyball hosts Syracuse at noon. 

]]> sgagliano3 1 1691077696 2023-08-03 15:48:16 1700244658 2023-11-17 18:10:58 0 0 event Volleyball hosts Syracuse at noon. 

]]>
2023-11-19T12:00:00-05:00 2023-11-19T12:00:00-05:00 2023-11-19T12:00:00-05:00 2023-11-19 17:00:00 2023-11-19 17:00:00 2023-11-19 17:00:00 2023-11-19T12:00:00-05:00 2023-11-19T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-19 12:00:00 2023-11-19 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> 671311 671311 image <![CDATA[Georgia Tech Logo]]> image/jpeg 1691074899 2023-08-03 15:01:39 1691074899 2023-08-03 15:01:39 <![CDATA[2023 Volleyball Schedule]]>
<![CDATA[2023 IBB Holiday Party]]> 27195 The Institute for Bioengineering and Bioscience will hold its annual Holiday Party to celebrate another great year of interdisciplinary and collaborative research!

RSVP Required by Dec. 3 (may close early if max capacity is reached) - Opening November 6 - space limited

Above & Beyond Faculty, Student and Staff Awards to be announced, so take a break from your offices and labs to come and celebrate the holiday season with the IBB community!

This event is open to all IBB faculty, staff, research staff, postdocs, graduate students, and Petit Scholars.

*name tags will be required

]]> Colly Mitchell 1 1694452136 2023-09-11 17:08:56 1700243804 2023-11-17 17:56:44 0 0 event Open to IBB faculty, staff, postdocs, graduate students, and Petit Scholars

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2023-12-14T16:30:00-05:00 2023-12-14T18:30:00-05:00 2023-12-14T18:30:00-05:00 2023-12-14 21:30:00 2023-12-14 23:30:00 2023-12-14 23:30:00 2023-12-14T16:30:00-05:00 2023-12-14T18:30:00-05:00 America/New_York America/New_York datetime 2023-12-14 04:30:00 2023-12-14 06:30:00 America/New_York America/New_York datetime <![CDATA[IBB website]]> Direct event inquiries to connect@ibb.gatech.edu

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<![CDATA[Convergence Innovation Competition Finalist Showcase]]> 27513 The finalist teams for the Convergence Innovation Competition (CIC) will highlight their projects, discuss their experience participating in the competition, and winners will be announced.


About the CIC
The Convergence Innovation Competition (CIC) is dedicated to helping students create and showcase innovative and viable products and experiences with the support of campus and industry resources and guidance. CIC categories are determined by community and industry partners. Winning entries will include a viable end-to-end prototype which operates on converged services, media, networks, and/or platforms. CIC entries can be based on class projects, student research projects, as well as personal hobbies and interests.

As part of the competition, one team is awarded a Golden Ticket to participate in the Create-X Startup Launch program during the summer! Winning team members and runner up team members receive a monetary prize for participating.

 

]]> Walter Rich 1 1700235005 2023-11-17 15:30:05 1700235041 2023-11-17 15:30:41 0 0 event The finalist teams for the Convergence Innovation Competition (CIC) will highlight their projects, discuss their experience participating in the competition, and winners will be announced.

]]>
2023-11-30T12:00:00-05:00 2023-11-30T13:30:00-05:00 2023-11-30T13:30:00-05:00 2023-11-30 17:00:00 2023-11-30 18:30:00 2023-11-30 18:30:00 2023-11-30T12:00:00-05:00 2023-11-30T13:30:00-05:00 America/New_York America/New_York datetime 2023-11-30 12:00:00 2023-11-30 01:30:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Fall 2023 Semester Pre-Finals Student Wellness Drop-In]]> 36172 Finals are right around the corner, and ECE is here to support our students! ECE's Student/Faculty Committee and Student Advisory Council are excited to host a build-your-own finals week care package drop-in!

We'll have everything you need to prep your backpack for crunch time — grab-and-go snacks, study supplies, and even ECE swag! Drop by the Van Leer Lobby (2nd floor atrium) anytime from 11 a.m. to 2 p.m on December 5. Undergraduate and graduate students welcome! ECE students ONLY. 

]]> dwatson71 1 1700234594 2023-11-17 15:23:14 1700234894 2023-11-17 15:28:14 0 0 event Finals are right around the corner, and ECE is here to support our students! ECE's Student/Faculty Committee and Student Advisory Council are excited to host a build-your-own finals week care package drop-in!

]]>
2023-12-05T11:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05T14:00:00-05:00 2023-12-05 16:00:00 2023-12-05 19:00:00 2023-12-05 19:00:00 2023-12-05T11:00:00-05:00 2023-12-05T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 11:00:00 2023-12-05 02:00:00 America/New_York America/New_York datetime <![CDATA[]]> Lakshmi Raju
lraju@gatech.edu

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<![CDATA[Blue Sky Group: LGBTQ+ Health]]> 27195 Join researchers and clinicians from across the Georgia CTSA for a session on LGBTQ+ Health.

Blue Sky Groups are unstructured meetings that provide a unique opportunity for attendees to drive the agenda and catalyze future collaborations and research opportunities.

The discussion will be opened by Don Operario, Ph.D., a leading researcher in this field. Discussion topics may include, but are not limited to:

Share your experience, learn from others, enjoy opportunities for interdisciplinary networking and find potential collaborators!
 

]]> Colly Mitchell 1 1700225854 2023-11-17 12:57:34 1700225940 2023-11-17 12:59:00 0 0 event Hosted by Georgia CTSA

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2023-12-06T13:00:00-05:00 2023-12-06T14:30:00-05:00 2023-12-06T14:30:00-05:00 2023-12-06 18:00:00 2023-12-06 19:30:00 2023-12-06 19:30:00 2023-12-06T13:00:00-05:00 2023-12-06T14:30:00-05:00 America/New_York America/New_York datetime 2023-12-06 01:00:00 2023-12-06 02:30:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Ph.D. Dissertation Defense - Lingjun Zhu]]> 28475 TitlePower Delivery and Thermal-Aware Electronic Design Automation Solutions for High-Performance 3D ICs

Committee:

Dr. Sung Kyu Lim, ECE, Chair, Advisor

Dr. Shimeng Yu, ECE

Dr. Saibal Mukhopadhyay, ECE

Dr. Madhavan Swaminathan, ECE

Dr. Hyesoon Kim, CoC

]]> Daniela Staiculescu 1 1700218993 2023-11-17 11:03:13 1700219038 2023-11-17 11:03:58 0 0 event The objective of this research is to explore 3D IC physical design methodologies and develop EDA solutions to evaluate and mitigate power delivery and thermal challenges in high-performance 3D ICs with emerging interconnects and advanced CMOS technology. Specifically, we implement tool flows to enable 3D IC physical design with various design and technology assumptions based on existing EDA software and customized algorithms. Using a novel 3D RTL-to-GDS design flow, we improve the performance of heterogeneous 3D ICs, investigate emerging computing systems such as logic-on-memory stacked 3D CPU, and explore the PPA, power delivery and thermal impacts of 3D integration.     
With a comprehensive analysis of 3D IC power delivery and thermal integrity, we propose EDA methods to quickly analyze thermal sustainability, explore design trade-offs, and generate floorplan and cooling solutions for large-scale 3D computing systems. In addition, we study the trend of power delivery issues in 3D ICs with technology scaling. We identify key power delivery challenges and bottlenecks considering various technology nodes and applications, propose robust 2D/3D PDN structures and design strategies, and evaluate the system-level impacts on PPA and power integrity.

]]>
2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30 19:00:00 2023-11-30 21:00:00 2023-11-30 21:00:00 2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 02:00:00 2023-11-30 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[Ph.D. Dissertation Defense - Meng-Che Chang]]> 28475 TitleOnline Decision-Making under Information-Theoretic Constraints

Committee:

Dr. Matthieu Bloch, ECE, Chair, Advisor

Dr. Justin Romberg, ECE

Dr. Siva Theja Maguluri, ISyE

Dr. Mark Davenport, ECE

Dr. Yao Xie, ISyE

]]> Daniela Staiculescu 1 1700218682 2023-11-17 10:58:02 1700218707 2023-11-17 10:58:27 0 0 event We consider the problems of online decision making under two categories of information-theoretical constraints, namely, security and communication constraints. There are several security related performance metrics that are considered in this thesis. When the decision maker aims to avoid the adversary from gaining accurate estimation about the unknown parameter, we formulate the problem of evasive hypothesis testing. This problem can be viewed as the counterpart of  secured communication in the context of hypothesis testing. The objective is to maximize the quantity which captures the ratio of error exponents between the decision maker and the adversary. When the goal is not to hide the parameter but to make the process of decision making algorithm undetectable, we formulate the problem of  covert decision making. We show the algorithm also need to obey the square-root law in order to hide the presence of the algorithm. The last security related performance metric we consider in this thesis is the robustness of the algorithm. We are interested in analyzing the performance of active hypothesis testing when actions are potentially corrupted by the adversary. 
Problems that involve jointly estimating the channel state and transmitting information are called joint communication and sensing. In the second half of this thesis, we analyze the tradeoff between the detection error exponent and the communication rate in the problems of joint communication and sensing in both mono-static and bi-static models.
Finally, we also make an extension to the case when the transmission window can be determined online, and we call it sequential joint communication and sensing.

]]>
2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27 14:00:00 2023-11-27 16:00:00 2023-11-27 16:00:00 2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 09:00:00 2023-11-27 11:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Ph.D. Dissertation Defense - Charles Lynch]]> 28475 TitleHigh Fidelity Localization of Energy Autonomous mmIDs for Future Cyberphysical Systems

Committee:

Dr. Emmanouil Tentzeris, ECE, Chair, Advisor

Dr. Gregory Durgin, ECE

Dr. Nima Ghalichechian, ECE

Dr. John Cressler, ECE

Dr. Suresh Sitaraman, ME

Dr. Jimmy Hester, Atheraxon

]]> Daniela Staiculescu 1 1700218149 2023-11-17 10:49:09 1700218297 2023-11-17 10:51:37 0 0 event The objective of the proposed research is to develop a novel 5G/mm-Wave-enabled mmID systems for next generation localized sensing systems building the framework for next-generation cyber-physical systems. In order to realize these future CPSs, the mmIDs used to form these systems need to be highly manufacturable, operate energy autonomously, have compact form factor, provide long-reading ranges with orientation-agnostic operation, and be able to be localized accurately to create a detailed CPS of an environment.Three specific topologies of backscatter tags operating in this 5G/mmWave bands are presented. The first technology presented is a chipless cross-polarized reflectarray wireless strain sensor presenting the first every off-axis structural health monitoring fully-passive sensor for local strain monitoring for both adhered or embedded form-factors. Along with the design and characterization of the wireless strain sensor, a multi-tag interrogation framework is presented for future ubiquitous structure health monitoring CPSs. The next technology is the first-ever retro-directive harmonic mmID comprised of dual Rotman lenses and a fully-passive frequency doubler circuit. The mmID is interrogated with a proof-of-concept harmonic frequency modulated continuous wave radar providing accurate long range ranging of the energy autonomous tag as well as sub-mm accuracy at medium range of the radar. The mmID is envisioned to provide ultra-long range operation future localized sensing and tracking applications up to multiple kilometers. The last technology builds on the previous two by combining a 3D lens with a backscattering RF ‘pixel’ array forming a camera-inspired semi-passive mmID. Two designs consisting of a single lens-based mmID and a multi-lens based mmID. The multi-lens mmID in particular combines both optical lens system design and mmWave antenna design to form a highly detectable mmID with a large solid angle of coverage in the top hemisphere of the mmID. The interrogation of the multi-lens-based mmID was conducted at long ranges and localized accurately even at highly oblique angles of interrogation. The work presented in this thesis present a step forward the creation of future 5G/mmWave-enabled mmID-based CPSs.

]]>
2023-11-21T13:00:00-05:00 2023-11-21T15:00:00-05:00 2023-11-21T15:00:00-05:00 2023-11-21 18:00:00 2023-11-21 20:00:00 2023-11-21 20:00:00 2023-11-21T13:00:00-05:00 2023-11-21T15:00:00-05:00 America/New_York America/New_York datetime 2023-11-21 01:00:00 2023-11-21 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Microsoft Teams Meeting link]]>
<![CDATA[Waffles and Wind Down]]> 27332 To help you de-stress before finals, the Honors Program and Explore living learning communities are providing a Waffle House food truck on December 1 from 7:00 - 9:00 PM. The truck will be parked on West Campus between the Explore and HP residence halls, with the final location TBD.

We don't want to waste food or Honors Program funds, so please make sure to RSVP if you plan to attend the event.  Get some waffles and fixins to help fuel your brain and body while you're studying for final exams!

]]> Amy D'Unger 1 1700161796 2023-11-16 19:09:56 1700164511 2023-11-16 19:55:11 0 0 event Come de-stress during the last week of classes with food from Waffle House!

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2023-12-01T19:00:00-05:00 2023-12-01T21:00:00-05:00 2023-12-01T21:00:00-05:00 2023-12-02 00:00:00 2023-12-02 02:00:00 2023-12-02 02:00:00 2023-12-01T19:00:00-05:00 2023-12-01T21:00:00-05:00 America/New_York America/New_York datetime 2023-12-01 07:00:00 2023-12-01 09:00:00 America/New_York America/New_York datetime <![CDATA[]]> Lauren Evans

]]>
672400 672400 image <![CDATA[waffle_wind_down.jpg]]> image/jpeg 1700164482 2023-11-16 19:54:42 1700164482 2023-11-16 19:54:42
<![CDATA[Georgia CTSA Grant Writing Workshop]]> 35486 Learn how to prepare supporting documents from two leading experts, Julie Hawk and Kim Cherewick.

This session will focus on:

*This session will not focus on human subjects or vertebrate animals. 

]]> Christina Wessels 1 1697209368 2023-10-13 15:02:48 1700161216 2023-11-16 19:00:16 0 0 event Learn how to prepare summary documents.

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2023-11-29T13:00:00-05:00 2023-11-29T15:00:00-05:00 2023-11-29T15:00:00-05:00 2023-11-29 18:00:00 2023-11-29 20:00:00 2023-11-29 20:00:00 2023-11-29T13:00:00-05:00 2023-11-29T15:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 01:00:00 2023-11-29 03:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]> Event contact Lauren James.

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<![CDATA[ International Day of Women and Girls in Science ]]> 35486 The International Day of Women and Girls in Science, celebrated on February 11th, is a global initiative aimed at recognizing and promoting the vital role that women and girls play in the field of science. This day serves as a powerful reminder of the importance of gender equality in the world of scientific research and innovation. It acknowledges the significant contributions made by female scientists and encourages the next generation of girls to pursue careers in science, technology, engineering, and mathematics (STEM). By breaking down barriers and addressing gender disparities, the International Day of Women and Girls in Science not only celebrates the achievements of women in science but also fosters a more inclusive and diverse scientific community, leading to enhanced creativity, innovation, and problem-solving for the benefit of all humanity.

Register Here

Agenda
Roundtable Speakers

Simone Douglas-Green, Ph.D.
Assistant Professor
Wallace H. Coulter Department of Biomedical Engineering
Georgia Tech and Emory University

Julie Champion, Ph.D.
Professor
School of Chemical and Biomolecular Engineering
Georgia Tech

Sybrina Atwaters, Ph.D.
Director, OMED Educational Services
Ivan Allen College of Liberal Arts
Georgia Tech

Roundtable moderated by Ana Mora-Boza, Postdoctoral Fellow, Georgia Tech.
]]> Christina Wessels 1 1699651432 2023-11-10 21:23:52 1700160722 2023-11-16 18:52:02 0 0 event Fostering a more inclusive and diverse scientific community.

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2024-02-08T16:00:00-05:00 2024-02-08T18:00:00-05:00 2024-02-08T18:00:00-05:00 2024-02-08 21:00:00 2024-02-08 23:00:00 2024-02-08 23:00:00 2024-02-08T16:00:00-05:00 2024-02-08T18:00:00-05:00 America/New_York America/New_York datetime 2024-02-08 04:00:00 2024-02-08 06:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[ISyE Seminar - Moïse Blanchard ]]> 34977 Title: 

Universal Learning for Decision-Making

Abstract:

We provide general-use decision-making algorithms under provably minimal assumptions on the data, using the universal learning framework. Classically, learning guarantees typically require two types of assumptions: (1) restrictions on target policies to be learned and (2) assumptions on the data-generating process. Instead, we show that we can provide consistent algorithms with vanishing regret compared to the best policy in hindsight, (1) irrespective of the optimal policy, known as universal consistency, and (2) well beyond standard i.i.d. or stationary assumptions on the data. We present our results for the contextual bandit problem, where the learner's rewards depend on their selected actions and an observable context. This generalizes the standard multi-armed bandit to the case where side information is available, e.g., patients' records or customers' history, which allows for personalized treatment. Precisely, we give necessary and sufficient conditions on the context-generating process for universal consistency to be possible. Surprisingly, for finite action spaces, universally learnable processes are the same for contextual bandits as for the supervised learning setting, suggesting that going from full feedback (supervised learning) to partial feedback (contextual bandits) came at no extra cost in terms of learnability.  We then show that there always exists an algorithm that guarantees universal consistency whenever this is achievable. In particular, such an algorithm is universally consistent under provably minimal assumptions: if it fails to be universally consistent for some context-generating process, then no other algorithm would succeed either. In the case of finite action spaces, this algorithm balances a fine trade-off between generalization (similar to structural risk minimization) and personalization (tailoring actions to specific contexts).

Bio:

Moïse Blanchard is a final year PhD student at MIT, working with Prof. Patrick Jaillet. He obtained his MSc in applied mathematics as valedictorian of Ecole Polytechnique. His research focuses on algorithms for decision-making and statistical learning. His work has been recognized with a best-student paper runner-up award at COLT and a best student paper award from the Informs TSL society.

]]> Julie Smith 1 1700159531 2023-11-16 18:32:11 1700159779 2023-11-16 18:36:19 0 0 event Abstract:

We provide general-use decision-making algorithms under provably minimal assumptions on the data, using the universal learning framework. Classically, learning guarantees typically require two types of assumptions: (1) restrictions on target policies to be learned and (2) assumptions on the data-generating process. Instead, we show that we can provide consistent algorithms with vanishing regret compared to the best policy in hindsight, (1) irrespective of the optimal policy, known as universal consistency, and (2) well beyond standard i.i.d. or stationary assumptions on the data. We present our results for the contextual bandit problem, where the learner's rewards depend on their selected actions and an observable context. This generalizes the standard multi-armed bandit to the case where side information is available, e.g., patients' records or customers' history, which allows for personalized treatment. Precisely, we give necessary and sufficient conditions on the context-generating process for universal consistency to be possible. Surprisingly, for finite action spaces, universally learnable processes are the same for contextual bandits as for the supervised learning setting, suggesting that going from full feedback (supervised learning) to partial feedback (contextual bandits) came at no extra cost in terms of learnability.  We then show that there always exists an algorithm that guarantees universal consistency whenever this is achievable. In particular, such an algorithm is universally consistent under provably minimal assumptions: if it fails to be universally consistent for some context-generating process, then no other algorithm would succeed either. In the case of finite action spaces, this algorithm balances a fine trade-off between generalization (similar to structural risk minimization) and personalization (tailoring actions to specific contexts).

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2023-12-07T11:00:00-05:00 2023-12-07T12:00:00-05:00 2023-12-07T12:00:00-05:00 2023-12-07 16:00:00 2023-12-07 17:00:00 2023-12-07 17:00:00 2023-12-07T11:00:00-05:00 2023-12-07T12:00:00-05:00 America/New_York America/New_York datetime 2023-12-07 11:00:00 2023-12-07 12:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Kwantae Kim]]> 27707 In partial fulfillment of the requirements for the degree of

 

Doctor of Philosophy in Biology

In the

School of Biological Sciences

 

Kwantae Kim

 

Will defend his dissertation

 

CHORDATE-SPECIFIC GENE REGULATORY NETWORK OF NEURON DEVELOPMENT IN CIONA.

 

21st, November, 2023

1PM

 

Engineered Biosystems Building (EBB) CHOA Seminar Room (1005)

https://gatech.zoom.us/j/5210520969?pwd=UHhDVGlkVmJSMXFDK0wvQ1NSSGpHQT09

 

 Thesis Advisor:

Alberto Stolfi, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Committee Members:

Liang Han, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Shuyi Nie, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Farzaneh Najafi, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

 

Christina Cota, Ph.D.

Department of Biology

Colby College

 

ABSTRACT: In this research, I investigated the complex gene regulatory networks underlying neurogenesis, taking advantage of the unique neurons of the Ciona model system. I revealed that Fgf signaling is crucial for the neurogenesis of Bipolar Tail Neurons (BTNs) by controlling the expression of Neurogenin, the fate-determining transcription factor in these neurons. Then I also characterized multiple effector genes functioning in the development of BTNs. Additionally, I determined the vital role of the Pax3/7 transcription factor in the neural plate border to induce the neural tube closure. Finally, I demonstrated how the Pax3/7 also orchestrates an intricate gene regulatory network upstream of multiple transcription factors and functional effectors during the neurogenesis of Descending Decussating Neurons (ddNs). I found that the majority of this network’s regulatory branches are shared with other neurons in Ciona or even other organisms including vertebrates. Moreover, I revealed the role of key putative effector genes during the neurogenesis of ddNs. These findings will provide profound insights into developmental mechanisms in the central nervous system of chordates.

 

]]> Tatianna Richardson 1 1700159285 2023-11-16 18:28:05 1700159285 2023-11-16 18:28:05 0 0 event  

CHORDATE-SPECIFIC GENE REGULATORY NETWORK OF NEURON DEVELOPMENT IN CIONA.

]]>
2023-11-21T13:00:00-05:00 2023-11-21T15:00:00-05:00 2023-11-21T15:00:00-05:00 2023-11-21 18:00:00 2023-11-21 20:00:00 2023-11-21 20:00:00 2023-11-21T13:00:00-05:00 2023-11-21T15:00:00-05:00 America/New_York America/New_York datetime 2023-11-21 01:00:00 2023-11-21 03:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by David Kartchner]]> 27707 Title: Automated extraction and synthesis of biomedical data for AI-driven systematic review and meta-analysis

 

David Kartchner

CSE PhD Candidate

School of Computational Science and Engineering

College of Computing

Georgia Institute of Technology

https://davidkartchner.com 

 

 

Date: Friday, November 17, 2023

Time: 11:00am–1:00pm EST

In-Person Location: Coda C1115 Midtown

Zoom Link: https://gatech.zoom.us/j/91549305198

 

 

Committee:

Dr. Cassie Mitchell (Advisor), School of Biomedical Engineering, Georgia Institute of Technology

Dr. Chao Zhang, School of Computational Science and Engineering Georgia Institute of Technology

Dr. Duen Horng "Polo" Chau, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Jon Duke, Georgia Tech Research Institute, Georgia Institute of Technology

Dr. Daniel Domingo-Fernández, Enveda Biosciences

 

Abstract:

Biomedical literature is not simply a record of scientific discovery; it also provides a platform for research exploration and optimized clinical practice. The purpose of this thesis is to utilize and develop natural language processing methods to enhance and automate biomedical literature-based research inquiry.  Specifically, we develop datasets, methods, and systems to enable AI-assisted systematic review and meta-analysis of clinical literature.  We further validate its efficacy via several clinical case studies that demonstrate its value in identifying potential treatments for emerging diseases and elucidating the mechanisms by which diseases affect patients.

 

Qualitative systematic reviews perform a thorough survey of a particular medical topic to highlight relevant relationships and highlight promising directions for future research.  To enable faster systematic review of biomedical relationships, we build a knowledge graph of relationships between biomedical entities extracted from 33+ million research articles on PubMed.  We pair this with an unsupervised graph ranking algorithm that identifies related concepts and their relationships from literature.  This graph and accompanying software package form a literature-based discovery system that can comprehensively identify and rank disease risks, mechanisms, and repurposed drugs for future clinical or experimental research prioritization.

 

Similarly, quantitative meta-analysis of clinical studies forms the gold standard for establishing clinical guidelines and best practice by calculating an aggregate effect size from a collection of smaller cohorts.  Meta-analysis begins with a specific research question and then extracts study-specific data elements to form a large, synthetic statistical cohort.  Currently, the process of selecting research articles and extracting relevant data is done manually, taking a year on average for each clinical meta-analysis.  This thesis presents data and methodological resources that dramatically accelerate the process of qualitatively and quantitatively aggregating evidence from biomedical research.   In doing so, we provide the following contributions:

 

]]> Tatianna Richardson 1 1700159182 2023-11-16 18:26:22 1700159182 2023-11-16 18:26:22 0 0 event Automated extraction and synthesis of biomedical data for AI-driven systematic review and meta-analysis

 

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<![CDATA[PhD Defense by Han Huang]]> 27707 Title: Incorporating interactivity into product design with printed tactile interactive elements

Date/Time: Nov. 29th 12pm-1pm

Location: East Architecture 214 (Conference Room)


Committee members:

Dr. HyunJoo Oh, Advisor

Assistant Professor, School of Industrial

Design & School of Interactive Comput-

ing Georgia Institute of Technology

 

Tim Purdy

College of Design

Georgia Institute of Technology

 

Jim Budd

College of Design

Georgia Institute of Technology

 

Abstract: 

The rising prevalence of smart products accentuates the importance of embedding interactivity into industrial design. Currently, designers use mechanical electronic components like buttons and sliders and program them using a micro-controller such as Arduino board for prototyping. However, those conventional electronic components with fixed shapes and interaction methods are limited in terms of both the aesthetic and functional possibilities of prototypes. As a way to address the issue of the rigidity of the form and function of the prototypes, printed electronics, which are thin and flexible, offers an opportunity to develop interactive prototypes seamlessly integrating form and function. However, a drawback of printed electronics has been the absence of tactile feedback, restricting their application in tactile-dependent environments like eyes-free interactions. 

 

This project investigated a novel fabrication method to create printed electronics with tactile feedback and explored the usability and design space for visible and eyes-free environments. By comparing the usability of tactile electronic components with traditional flat printed electronic components, we collected design insights from users for utilizing and optimizing tactile electronic components. After that, a co-design workshop was conducted with eight designers to learn and explore potential design space of the proposed fabrication methods and summarize the design recommendations for applying tactile printed electronic components in visible and eyes-free environments. Through the study, I draw four main findings. First, tactile features enhance the usability of printed electronic components in visible environments by improving access, recognition, and utilization. Second, electronic components can be categorized into two groups based on their interactive methods and the intensity of the haptic feedback outcome. Third, in eyes-free environments, sliding elements benefit from a touchpad-like pattern with a clear starting point, direction, and boundary without detailed tick marks. Lastly, pressing elements benefit from confirmation spots, and a concave shape aids in verifying precise presses.

]]> Tatianna Richardson 1 1700159079 2023-11-16 18:24:39 1700159079 2023-11-16 18:24:39 0 0 event Incorporating interactivity into product design with printed tactile interactive elements

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2023-11-29T12:00:00-05:00 2023-11-29T13:00:00-05:00 2023-11-29T13:00:00-05:00 2023-11-29 17:00:00 2023-11-29 18:00:00 2023-11-29 18:00:00 2023-11-29T12:00:00-05:00 2023-11-29T13:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 12:00:00 2023-11-29 01:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[IRIM Spring 2024 Seminar Featuring TBA]]> 27863 Abstract: TBA
 

Bio: TBA

]]> Christa Ernst 1 1700159029 2023-11-16 18:23:49 1700159029 2023-11-16 18:23:49 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-04-10T12:15:00-04:00 2024-04-10T13:15:00-04:00 2024-04-10T13:15:00-04:00 2024-04-10 16:15:00 2024-04-10 17:15:00 2024-04-10 17:15:00 2024-04-10T12:15:00-04:00 2024-04-10T13:15:00-04:00 America/New_York America/New_York datetime 2024-04-10 12:15:00 2024-04-10 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[PhD Defense by Neil Dodd]]> 27707 Mr. Neil Dodd

 

Thesis Title: SYNTHESIS AND ANALYSIS OF LOW-VALENT NHC SUPPORTED NICKEL COMPLEXES

 

Monday, Dec 4th, 2023 at 2:00pm 

Location: Mose 3201A , or Join via Zoom Meeting

https://gatech.zoom.us/j/97512010525?pwd=T3hKY25wdHdCSVFZY0o5RWpOSi83Zz09

 

Committee Members:

 

Prof. Joseph Sadighi (Advisor) - School of Chemistry and Biochemistry

Prof. Stefan France - School of Chemistry and Biochemistry

Prof. Jake Soper - School of Chemistry and Biochemistry

Prof. Henry La Pierre - School of Chemistry and Biochemistry

Prof. Krista Walton -  School of Chemical and Bimolecular Engineering 

 

]]> Tatianna Richardson 1 1700158936 2023-11-16 18:22:16 1700158936 2023-11-16 18:22:16 0 0 event SYNTHESIS AND ANALYSIS OF LOW-VALENT NHC SUPPORTED NICKEL COMPLEXES

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2023-12-04T14:00:00-05:00 2023-12-04T16:00:00-05:00 2023-12-04T16:00:00-05:00 2023-12-04 19:00:00 2023-12-04 21:00:00 2023-12-04 21:00:00 2023-12-04T14:00:00-05:00 2023-12-04T16:00:00-05:00 America/New_York America/New_York datetime 2023-12-04 02:00:00 2023-12-04 04:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[IRIM Spring 2024 Seminar Featuring Talia Moore, U. Michigan Robotics]]> 27863 Abstract: TBA

 

Bio: TBA

]]> Christa Ernst 1 1700158221 2023-11-16 18:10:21 1700158221 2023-11-16 18:10:21 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-03-27T12:15:00-04:00 2024-03-27T13:15:00-04:00 2024-03-27T13:15:00-04:00 2024-03-27 16:15:00 2024-03-27 17:15:00 2024-03-27 17:15:00 2024-03-27T12:15:00-04:00 2024-03-27T13:15:00-04:00 America/New_York America/New_York datetime 2024-03-27 12:15:00 2024-03-27 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[IRIM Spring 2024 Seminar Featuring TBA]]> 27863 Abstract: TBA

 

Bio: TBA

]]> Christa Ernst 1 1700157643 2023-11-16 18:00:43 1700157643 2023-11-16 18:00:43 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-03-06T12:15:00-05:00 2024-03-06T13:15:00-05:00 2024-03-06T13:15:00-05:00 2024-03-06 17:15:00 2024-03-06 18:15:00 2024-03-06 18:15:00 2024-03-06T12:15:00-05:00 2024-03-06T13:15:00-05:00 America/New_York America/New_York datetime 2024-03-06 12:15:00 2024-03-06 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[Get Media Event ]]> 27909 Ut enim ad minim veniam, quis nostrud exercitation ullamco

]]> Kennard McGill 1 1700151490 2023-11-16 16:18:10 1700157050 2023-11-16 17:50:50 0 0 event Ut enim ad minim veniam, quis nostrud exercitation ullamco

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2023-11-23T11:18:10-05:00 2023-11-23T12:18:10-05:00 2023-11-23T12:18:10-05:00 2023-11-23 16:18:10 2023-11-23 17:18:10 2023-11-23 17:18:10 2023-11-23T11:18:10-05:00 2023-11-23T12:18:10-05:00 America/New_York America/New_York datetime 2023-11-23 11:18:10 2023-11-23 12:18:10 America/New_York America/New_York datetime <![CDATA[]]> 672208 672380 672208 video <![CDATA[Janelle Dunlap Turns Beekeeping Into Art]]> The Urban Honey Bee Project’s new beekeeper in residence is creating art and educating the public with her practice.

]]> 1698676668 2023-10-30 14:37:48 1698676668 2023-10-30 14:37:48
672380 image <![CDATA[Students in the GTDC: Pathways to Policy program pose for a photo with the Washington Monument in the backgroumd.]]> Students in the GTDC: Pathways to Policy program pose for a photo with the Washington Monument in the backgroumd.

]]> image/jpeg 1699995477 2023-11-14 20:57:57 1699995477 2023-11-14 20:57:57
<![CDATA[IRIM Spring 2024 Seminar Featuring Dora Sadigh, Stanford Robotics Center]]> 27863 Abstract: TBA

 

Bio: Dora Sadigh is Assistant Professor in the Computer Science Department and Electrical Engineering Department at Stanford University and Director of Intelligent and interactive Autonomous Systems Group. Her research interests lie at the intersection of robotics, machine learning, and control theory. Specifically, her group is interested in developing efficient algorithms for safe, reliable, and adaptive human-robot and generally multi-agent interactions.

]]> Christa Ernst 1 1700156613 2023-11-16 17:43:33 1700156613 2023-11-16 17:43:33 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-02-21T12:15:00-05:00 2024-02-21T13:15:00-05:00 2024-02-21T13:15:00-05:00 2024-02-21 17:15:00 2024-02-21 18:15:00 2024-02-21 18:15:00 2024-02-21T12:15:00-05:00 2024-02-21T13:15:00-05:00 America/New_York America/New_York datetime 2024-02-21 12:15:00 2024-02-21 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[IRIM Spring 2024 Seminar Todd Murphey, Northwestern Center for Robotics & Biosystems]]> 27863 Abstract: TBA

 

Bio: Professor Murphey's research focuses on computational methods in dynamics and control, with applications in neuroscience, health science, robotics, and automation. The group focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control.  The mathematical approaches used by the group lead to many orders of magnitude improvement in computational efficiency for reliable real-time implementation. Applications include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation.

]]> Christa Ernst 1 1700156329 2023-11-16 17:38:49 1700156329 2023-11-16 17:38:49 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-02-07T12:15:00-05:00 2024-02-07T13:15:00-05:00 2024-02-07T13:15:00-05:00 2024-02-07 17:15:00 2024-02-07 18:15:00 2024-02-07 18:15:00 2024-02-07T12:15:00-05:00 2024-02-07T13:15:00-05:00 America/New_York America/New_York datetime 2024-02-07 12:15:00 2024-02-07 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[IRIM Spring 2024 Seminar Featuring TBA]]> 27863 Abstract: TBA

 

Bio: TBA

]]> Christa Ernst 1 1700156066 2023-11-16 17:34:26 1700156066 2023-11-16 17:34:26 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-01-24T12:15:00-05:00 2024-01-24T13:15:00-05:00 2024-01-24T13:15:00-05:00 2024-01-24 17:15:00 2024-01-24 18:15:00 2024-01-24 18:15:00 2024-01-24T12:15:00-05:00 2024-01-24T13:15:00-05:00 America/New_York America/New_York datetime 2024-01-24 12:15:00 2024-01-24 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[IRIM Spring 2024 Seminar Featuring Kevin Lynch, Northwestern Center for Robotics & Biosystems ]]> 27863 Abstract: TBA

 

Bio: Kevin Lynch's research interests are in robotic manipulation, robot locomotion, physical human-robot interaction, and distributed control of robot swarms.

]]> Christa Ernst 1 1700155424 2023-11-16 17:23:44 1700155424 2023-11-16 17:23:44 0 0 event All Seminars Held on Wednesdays 12:15 - 1:15pm in Marcus Nanotechnology

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2024-01-10T12:15:00-05:00 2024-01-10T13:15:00-05:00 2024-01-10T13:15:00-05:00 2024-01-10 17:15:00 2024-01-10 18:15:00 2024-01-10 18:15:00 2024-01-10T12:15:00-05:00 2024-01-10T13:15:00-05:00 America/New_York America/New_York datetime 2024-01-10 12:15:00 2024-01-10 01:15:00 America/New_York America/New_York datetime <![CDATA[]]> christa.ernst@research.gatech.edu

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<![CDATA[Series Schedule]]>
<![CDATA[Finibus Bonorum ]]> 27909 Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. 

]]> Kennard McGill 1 1700152140 2023-11-16 16:29:00 1700152399 2023-11-16 16:33:19 0 0 event Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum."

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2023-11-16T11:29:00-05:00 2023-11-23T12:29:00-05:00 2023-11-23T12:29:00-05:00 2023-11-16 16:29:00 2023-11-23 17:29:00 2023-11-23 17:29:00 2023-11-16T11:29:00-05:00 2023-11-23T12:29:00-05:00 America/New_York America/New_York datetime 2023-11-16 11:29:00 2023-11-23 12:29:00 America/New_York America/New_York datetime <![CDATA[]]> 672396 672257 672396 image <![CDATA[ORNL AI Workshop.jpg]]> image/jpeg 1700145904 2023-11-16 14:45:04 1700145904 2023-11-16 14:45:04 672257 video <![CDATA[Digital Media Students Showcase Sustainability Artwork]]> Graduate students Jordan Graves, Sylvia Janicki, and Hudson Treu in the School of Literature, Media, and Communication were among artists whose work was featured in the Extension of Community exhibit on campus. Take a look at their work and hear their perspectives on how art can drive community, connection, and collaboration for sustainability.

]]> 1699026330 2023-11-03 15:45:30 1699026330 2023-11-03 15:45:30
<![CDATA[Analytics Practicum Employer Info Session #2]]> 27764 The Georgia Tech MS Analytics Program is currently accepting Analytics Practicum Project Proposals for the Summer and Fall 2024 semesters.

We are seeking real-world data science and advanced analytics projects of significant interest to your organization, along with the corresponding data and a liaison to communicate with the students throughout the project. Students in GT’s MS Analytics Program would work in small groups on your project throughout an entire semester. The students have completed a rigorous set of courses in machine learning, statistics, data mining, business analytics, and computational tools. There is no cost to sponsor a project, and all intellectual property belongs to your organization at the end of the project. You can find more information on the analytics practicum HERE.

If your organization is interested in learning more about sponsoring a project, please join us for an upcoming Analytics Practicum Employer Info Session:

 

]]> Scott Jacobson 1 1700147365 2023-11-16 15:09:25 1700147429 2023-11-16 15:10:29 0 0 event Analytics Practicum Employer Info Session #2

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2024-02-15T14:00:00-05:00 2024-02-15T15:00:00-05:00 2024-02-15T15:00:00-05:00 2024-02-15 19:00:00 2024-02-15 20:00:00 2024-02-15 20:00:00 2024-02-15T14:00:00-05:00 2024-02-15T15:00:00-05:00 America/New_York America/New_York datetime 2024-02-15 02:00:00 2024-02-15 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[GT MS Analytics Practicum Webpage]]> <![CDATA[Session #1 Meeting Link]]> <![CDATA[Session #2 Meeting Link]]>
<![CDATA[Analytics Practicum Employer Info Session #1]]> 27764 The Georgia Tech MS Analytics Program is currently accepting Analytics Practicum Project Proposals for the Summer and Fall 2024 semesters.

We are seeking real-world data science and advanced analytics projects of significant interest to your organization, along with the corresponding data and a liaison to communicate with the students throughout the project. Students in GT’s MS Analytics Program would work in small groups on your project throughout an entire semester. The students have completed a rigorous set of courses in machine learning, statistics, data mining, business analytics, and computational tools. There is no cost to sponsor a project, and all intellectual property belongs to your organization at the end of the project. You can find more information on the analytics practicum HERE.

If your organization is interested in learning more about sponsoring a project, please join us for an upcoming Analytics Practicum Employer Info Session:

 

]]> Scott Jacobson 1 1700147205 2023-11-16 15:06:45 1700147269 2023-11-16 15:07:49 0 0 event Analytics Practicum Employer Info Session #1

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2024-02-14T11:00:00-05:00 2024-02-14T12:00:00-05:00 2024-02-14T12:00:00-05:00 2024-02-14 16:00:00 2024-02-14 17:00:00 2024-02-14 17:00:00 2024-02-14T11:00:00-05:00 2024-02-14T12:00:00-05:00 America/New_York America/New_York datetime 2024-02-14 11:00:00 2024-02-14 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[GT MS Analytics Practicum Webpage]]> <![CDATA[Session #1 Meeting Link]]> <![CDATA[Session #2 Meeting Link]]>
<![CDATA[Football vs. Syracuse]]> 36418 Football hosts Syracuse.

]]> sgagliano3 1 1691168530 2023-08-04 17:02:10 1700099815 2023-11-16 01:56:55 0 0 event Football hosts Syracuse.

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2023-11-18T20:00:00-05:00 2023-11-18T23:00:00-05:00 2023-11-18T23:00:00-05:00 2023-11-19 01:00:00 2023-11-19 04:00:00 2023-11-19 04:00:00 2023-11-18T20:00:00-05:00 2023-11-18T23:00:00-05:00 America/New_York America/New_York datetime 2023-11-18 08:00:00 2023-11-18 11:00:00 America/New_York America/New_York datetime <![CDATA[]]> 671311 671311 image <![CDATA[Georgia Tech Logo]]> image/jpeg 1691074899 2023-08-03 15:01:39 1691074899 2023-08-03 15:01:39 <![CDATA[2023 Football Schedule]]>
<![CDATA[CSA General Body Meeting]]> 36418 Come out to our monthly general body meeting for updates, food, and calligraphy!

]]> sgagliano3 1 1700085773 2023-11-15 22:02:53 1700085848 2023-11-15 22:04:08 0 0 event Come out to our monthly general body meeting for updates, food, and calligraphy!

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2023-11-28T18:30:00-05:00 2023-11-28T19:30:00-05:00 2023-11-28T19:30:00-05:00 2023-11-28 23:30:00 2023-11-29 00:30:00 2023-11-29 00:30:00 2023-11-28T18:30:00-05:00 2023-11-28T19:30:00-05:00 America/New_York America/New_York datetime 2023-11-28 06:30:00 2023-11-28 07:30:00 America/New_York America/New_York datetime <![CDATA[]]> Steven Li

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<![CDATA[DramaTech Announces Auditions for ANIMALS OUT OF PAPER]]> 36418 Auditions for Animals Out of Paper will be held on Tuesday, 11/28 at 7 pm in the Black Box.  The audition will be warm readings. You don't need to prepare anything but read through the script and the sides in advance of the audition.

ABOUT THE SHOW: 
Animals Out of Paper is an uncommon love story from acclaimed playwright Rajiv Joseph, Pulitzer Prize Finalist for Bengal Tiger at the Baghdad Zoo. Andy, a calculus teacher and avid fan, pressures a reclusive Ilana, a world-famous origami artist, into becoming an unwitting mentor to a troubled teenage prodigy, Suresh. These three intriguingly flawed characters begin to reshape and mold each other’s lives in much the same way they fold and crease their origami art.

ABOUT THE CHARACTERS: 
Ilana - 30s, female-presenting, any ethnicity - Ilana, a world-renowned origami artist, has become a bit of a recluse after her marriage ended and her dog ran away.

Andy - 30s, male presenting, any ethnicity - Andy is a high school calculus teacher and an avid fan of Ilana's work and origami in general. He is also an advocate for his student, Suresh.

Suresh - 17, male presenting, Of Indian/Pakistani descent - Suresh is a troubled student who recently lost his mother. He has natural abilities in math (and therefore origami).

]]> sgagliano3 1 1700085677 2023-11-15 22:01:17 1700085758 2023-11-15 22:02:38 0 0 event The audition will be warm readings. You don't need to prepare anything but read through the script and the sides in advance of the audition.

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2023-11-28T19:00:00-05:00 2023-11-28T22:00:00-05:00 2023-11-28T22:00:00-05:00 2023-11-29 00:00:00 2023-11-29 03:00:00 2023-11-29 03:00:00 2023-11-28T19:00:00-05:00 2023-11-28T22:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 07:00:00 2023-11-28 10:00:00 America/New_York America/New_York datetime <![CDATA[]]> Melissa Foulger

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<![CDATA[Asha For Education Fall '23 Run]]> 36418 :man-running:Lace up those running shoes and join us for the Asha Fall Run! :maple_leaf: Choose your challenge - 5k, 10k, or Half Marathon. We'll be starting at Tech Green on Dec 2. Stay hydrated with water stops along the route and fuel up post-run with a FREE breakfast! :pancakes::cup_with_straw: Let's run for the cause and make a difference together. :star2: Register now and don't forget to invite your friends. :sports_medal:Register at https://bit.ly/AshaRun23

]]> sgagliano3 1 1700085505 2023-11-15 21:58:25 1700085654 2023-11-15 22:00:54 0 0 event  Lace up those running shoes and join us for the Asha Fall Run! 

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2023-12-02T07:45:00-05:00 2023-12-02T11:00:00-05:00 2023-12-02T11:00:00-05:00 2023-12-02 12:45:00 2023-12-02 16:00:00 2023-12-02 16:00:00 2023-12-02T07:45:00-05:00 2023-12-02T11:00:00-05:00 America/New_York America/New_York datetime 2023-12-02 07:45:00 2023-12-02 11:00:00 America/New_York America/New_York datetime <![CDATA[]]> Shubham Jamdade

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<![CDATA[Registration Link]]>
<![CDATA[SCPC Presents: Midnight Breakfast Down the Rabbit Hole]]> 36418 SCPC cordially invites you to step into a world of enchantment at Midnight Breakfast (and Relaxation Fest): Down the Rabbit Hole! As exams approach and stress levels rise, we invite you to escape down the rabbit hole and join us for a whimsical evening of relaxation, free food, and incredible fun. On December 11th, from 9 PM till the clock strikes midnight, we'll be transforming our campus into a wonderland of merriment like no other. At Midnight Breakfast, you'll be treated to an assortment of delectable, free food options that would make the Queen of Hearts herself jealous. Sip on your favorite morning drink and munch down on some delectable snacks! We also have some amazingly cathartic activities! Immerse yourself in the soothing world of relaxation with free massages that will transport you to a state of bliss. Channel your inner frustration as you join in on the plate-smashing fun. Bring out your inner artist to paint your very own teacup to take home! 

Tickets will be released at gatech.universitytickets.com and are FREE and open to all Georgia Tech students! Note that there will be vegetarian/vegan options at Midnight Breakfast. For any inquiries or special accommodation requests, please contact SCPC. We can't wait for you to join us!

]]> sgagliano3 1 1699641417 2023-11-10 18:36:57 1700085424 2023-11-15 21:57:04 0 0 event SCPC cordially invites you to step into a world of enchantment at Midnight Breakfast (and Relaxation Fest): Down the Rabbit Hole! 

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2023-12-11T21:00:00-05:00 2023-12-12T00:00:00-05:00 2023-12-12T00:00:00-05:00 2023-12-12 02:00:00 2023-12-12 05:00:00 2023-12-12 05:00:00 2023-12-11T21:00:00-05:00 2023-12-12T00:00:00-05:00 America/New_York America/New_York datetime 2023-12-11 09:00:00 2023-12-12 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> Shreya Jayaswal

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<![CDATA[End of Semester Celebration]]> 36418 Come join us to celebrate a wonderful semester with Birdwatchers and relax before finals. We will be decorating bird-shaped cookies, playing Wingspan, and watching a bird-related movie! All are welcome. Stay for a while or just drop in; we look forward to seeing you!

]]> sgagliano3 1 1700085162 2023-11-15 21:52:42 1700085270 2023-11-15 21:54:30 0 0 event Come join us to celebrate a wonderful semester with Birdwatchers and relax before finals. 

]]>
2023-12-05T19:00:00-05:00 2023-12-05T22:00:00-05:00 2023-12-05T22:00:00-05:00 2023-12-06 00:00:00 2023-12-06 03:00:00 2023-12-06 03:00:00 2023-12-05T19:00:00-05:00 2023-12-05T22:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 07:00:00 2023-12-05 10:00:00 America/New_York America/New_York datetime <![CDATA[]]> Iris Smith

]]>
<![CDATA[Birdwatchers with Lauren Wilson from Wild Nest Bird Rehab & Zoo Atlanta]]> 36418 General Meeting for Birdwatchers @ GT! We will be hosting speaker Lauren Wilson.

]]> sgagliano3 1 1700084425 2023-11-15 21:40:25 1700084503 2023-11-15 21:41:43 0 0 event General Meeting for Birdwatchers @ GT! We will be hosting speaker Lauren Wilson.

]]>
2023-11-30T19:00:00-05:00 2023-11-30T20:00:00-05:00 2023-11-30T20:00:00-05:00 2023-12-01 00:00:00 2023-12-01 01:00:00 2023-12-01 01:00:00 2023-11-30T19:00:00-05:00 2023-11-30T20:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 07:00:00 2023-11-30 08:00:00 America/New_York America/New_York datetime <![CDATA[]]> Amanda Janusz

]]>
<![CDATA[ECE Holiday Party]]> 36418 WECE invites you to the Holiday Party organized jointly by WECE, HKN, and IEEE. The Holiday Party is on November 29th Wednesday from 6 p.m. to 8 p.m. in the Exhibition Hall’s Centennial Room. Come over for fun activities like gingerbread houses and cookie decorating. We will have catered dinner. Don’t forget to wear your ugly winter sweater :)

]]> sgagliano3 1 1700084280 2023-11-15 21:38:00 1700084389 2023-11-15 21:39:49 0 0 event Come over for fun activities like gingerbread houses and cookie decorating. We will have catered dinner. Don’t forget to wear your ugly winter sweater :)

]]>
2023-11-29T18:00:00-05:00 2023-11-29T20:00:00-05:00 2023-11-29T20:00:00-05:00 2023-11-29 23:00:00 2023-11-30 01:00:00 2023-11-30 01:00:00 2023-11-29T18:00:00-05:00 2023-11-29T20:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 06:00:00 2023-11-29 08:00:00 America/New_York America/New_York datetime <![CDATA[]]> Ziyu Liu

]]>
<![CDATA[Bring a Man to WECE]]> 36418 This week, bring a male friend to WECE for an extra-fun meeting!

Join us at our weekly meeting on Thursday, November 16th, from 11AM - 12PM in Van Leer C341. Free lunch will be provided.

]]> sgagliano3 1 1700084174 2023-11-15 21:36:14 1700084260 2023-11-15 21:37:40 0 0 event This week, bring a male friend to WECE for an extra-fun meeting!

]]>
2023-11-16T11:00:00-05:00 2023-11-16T12:00:00-05:00 2023-11-16T12:00:00-05:00 2023-11-16 16:00:00 2023-11-16 17:00:00 2023-11-16 17:00:00 2023-11-16T11:00:00-05:00 2023-11-16T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-16 11:00:00 2023-11-16 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> Ziyu Liu

]]>
<![CDATA[Best Buddies Meeting]]> 36418 Join us every other Saturday to socialize with participants from Gigi's Playhouse and students from the EXCEL program! These meetings will be focused on developing social skills and creating a safe space for adults with and without disabilities to come together. There will be activities and free food!

]]> sgagliano3 1 1700084135 2023-11-15 21:35:35 1700084160 2023-11-15 21:36:00 0 0 event Join us every other Saturday to socialize with participants from Gigi's Playhouse and students from the EXCEL program! 

]]>
2023-12-02T13:00:00-05:00 2023-12-02T15:00:00-05:00 2023-12-02T15:00:00-05:00 2023-12-02 18:00:00 2023-12-02 20:00:00 2023-12-02 20:00:00 2023-12-02T13:00:00-05:00 2023-12-02T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-02 01:00:00 2023-12-02 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> Nitya Jani

]]>
<![CDATA[Best Buddies Meeting]]> 36418 Join us every other Saturday to socialize with participants from Gigi's Playhouse and students from the EXCEL program! These meetings will be focused on developing social skills and creating a safe space for adults with and without disabilities to come together. There will be activities and free food!

]]> sgagliano3 1 1700084014 2023-11-15 21:33:34 1700084116 2023-11-15 21:35:16 0 0 event Join us every other Saturday to socialize with participants from Gigi's Playhouse and students from the EXCEL program! 

]]>
2023-11-18T13:00:00-05:00 2023-11-18T15:00:00-05:00 2023-11-18T15:00:00-05:00 2023-11-18 18:00:00 2023-11-18 20:00:00 2023-11-18 20:00:00 2023-11-18T13:00:00-05:00 2023-11-18T15:00:00-05:00 America/New_York America/New_York datetime 2023-11-18 01:00:00 2023-11-18 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> Nitya Jani

]]>
<![CDATA[Manager Self-Service Transactions]]> 36516 This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]> dlee994 1 1700083232 2023-11-15 21:20:32 1700083437 2023-11-15 21:23:57 0 0 event This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.

 

]]>
2023-12-05T10:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05 15:00:00 2023-12-05 17:00:00 2023-12-05 17:00:00 2023-12-05T10:00:00-05:00 2023-12-05T12:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 10:00:00 2023-12-05 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Register Here]]>
<![CDATA[Manager Self-Service Transactions]]> 36516 This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]> dlee994 1 1700083034 2023-11-15 21:17:14 1700083372 2023-11-15 21:22:52 0 0 event This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.

 

]]>
2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30T16:00:00-05:00 2023-11-30 19:00:00 2023-11-30 21:00:00 2023-11-30 21:00:00 2023-11-30T14:00:00-05:00 2023-11-30T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-30 02:00:00 2023-11-30 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Register Here]]>
<![CDATA[Manager Self-Service Transactions]]> 36516 This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]> dlee994 1 1700082882 2023-11-15 21:14:42 1700082882 2023-11-15 21:14:42 0 0 event This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]>
2023-12-07T13:00:00-05:00 2023-12-07T15:00:00-05:00 2023-12-07T15:00:00-05:00 2023-12-07 18:00:00 2023-12-07 20:00:00 2023-12-07 20:00:00 2023-12-07T13:00:00-05:00 2023-12-07T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-07 01:00:00 2023-12-07 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Register Here]]>
<![CDATA[Manager Self-Service Transactions]]> 36516 This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]> dlee994 1 1700082705 2023-11-15 21:11:45 1700082705 2023-11-15 21:11:45 0 0 event This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]>
2023-11-28T14:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28T16:00:00-05:00 2023-11-28 19:00:00 2023-11-28 21:00:00 2023-11-28 21:00:00 2023-11-28T14:00:00-05:00 2023-11-28T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 02:00:00 2023-11-28 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Register Here]]>
<![CDATA[Manager Self-Service Transactions]]> 36516 This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.
]]> dlee994 1 1700081145 2023-11-15 20:45:45 1700081145 2023-11-15 20:45:45 0 0 event This session has been designed to prepare our practitioners, HR professionals, managers, and anyone engaged in HR operations with the knowledge and skills necessary to effectively handle these critical HR transactions in support of our students. 

We will review the following important Manager Self-Service (MSS) transactions that will assist you in your spring hiring efforts:

  1. Manager Self-Service Request Forms (Miscellaneous): Understand how to navigate to the MSS Request Forms and review how to enter short work breaks (used only for Graduate students) and start date changes.
  2. Terminate Employee: Review the process for handling employee terminations, including term extensions in OneUSG Connect.
  3. Ad Hoc Salary Change: Learn how to efficiently manage and process salary changes for employees, ensuring accuracy and compliance.
  4. Employee Transfer: Learn best practices for seamlessly transferring employees between departments or locations, understand the transfer action reasons, when to transfer employees and review the transfer process.

 

]]>
2023-11-20T10:00:00-05:00 2023-11-20T12:00:00-05:00 2023-11-20T12:00:00-05:00 2023-11-20 15:00:00 2023-11-20 17:00:00 2023-11-20 17:00:00 2023-11-20T10:00:00-05:00 2023-11-20T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-20 10:00:00 2023-11-20 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Register Here]]>
<![CDATA[Using Interstride to Optimize your Job and Internship Search for International Students (presented by Interstride)]]> 27247 During this session, you'll learn how to best utilize Interstride mobile and web applications and apply the learnings in your job search process. For any questions, please reach out to contact@interstride.com

Register to Attend at https://us02web.zoom.us/webinar/register/WN__W-TfYIFQ7yUz4BdeXLS2Q#/registration

]]> Terrence Green 1 1700079122 2023-11-15 20:12:02 1700079214 2023-11-15 20:13:34 0 0 event

During this session, you'll learn how to best utilize Interstride mobile and web applications and apply the learnings in your job search process. For any questions, please reach out to contact@interstride.com

]]>
2023-12-20T14:00:00-05:00 2023-12-20T15:00:00-05:00 2023-12-20T15:00:00-05:00 2023-12-20 19:00:00 2023-12-20 20:00:00 2023-12-20 20:00:00 2023-12-20T14:00:00-05:00 2023-12-20T15:00:00-05:00 America/New_York America/New_York datetime 2023-12-20 02:00:00 2023-12-20 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> Career Center
Georgia Institute of Technology
Atlanta, GA  30332-0105
Phone:  404-894-3320
Fax:  404-894-7308
Email: careercenter@gatech.edu
Website:  http://www.career.gatech.edu
Follow us on LinkedIn
]]>
<![CDATA[Using Interstride to Optimize your Job and Internship Search for International Students (presented by Interstride) ]]> 27247 During this session, you'll learn how to best utilize Interstride mobile and web applications and apply the learnings in your job search process. For any questions, please reach out to contact@interstride.com

Register to Attend at https://us02web.zoom.us/webinar/register/WN_Pl1msDKwR9WAubu1RPCBlQ#/registration

]]> Terrence Green 1 1700079043 2023-11-15 20:10:43 1700079043 2023-11-15 20:10:43 0 0 event

During this session, you'll learn how to best utilize Interstride mobile and web applications and apply the learnings in your job search process. For any questions, please reach out to contact@interstride.com

]]>
2023-11-28T16:00:00-05:00 2023-11-28T17:00:00-05:00 2023-11-28T17:00:00-05:00 2023-11-28 21:00:00 2023-11-28 22:00:00 2023-11-28 22:00:00 2023-11-28T16:00:00-05:00 2023-11-28T17:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 04:00:00 2023-11-28 05:00:00 America/New_York America/New_York datetime <![CDATA[]]> Career Center
Georgia Institute of Technology
Atlanta, GA  30332-0105
Phone:  404-894-3320
Fax:  404-894-7308
Email: careercenter@gatech.edu
Website:  http://www.career.gatech.edu
Follow us on LinkedIn
]]>
<![CDATA[PhD Defense by Katie M. Kuo]]> 27707 Ms. Katie M. Kuo

 

Thesis Title: The hybrid barrel mechanism of outer membrane protein folding by the BAM complex and its inhibition

 

Tuesday, November 28th at 12:00 PM 

Location: Howey N201/N202 

Zoom: https://gatech.zoom.us/j/96263597838?pwd=aUhWT2QxWENTQVFLckNRcXFLOEpWdz09

Zoom Passcode: 049012

 

Committee Members: 

Prof. JC Gumbart (Advisor) - School of Physics

Prof. Raquel Lieberman - School of Chemistry and Biochemistry 

Prof. Jesse McDaniel - School of Chemistry and Biochemistry 

Prof. Loren Williams - School of Chemistry and Biochemistry 

Prof. Andreas Bommarius - School of Chemical and Biomolecular Engineering 

 

]]> Tatianna Richardson 1 1700078267 2023-11-15 19:57:47 1700078267 2023-11-15 19:57:47 0 0 event The hybrid barrel mechanism of outer membrane protein folding by the BAM complex and its inhibition

]]>
2023-11-28T12:00:00-05:00 2023-11-28T14:00:00-05:00 2023-11-28T14:00:00-05:00 2023-11-28 17:00:00 2023-11-28 19:00:00 2023-11-28 19:00:00 2023-11-28T12:00:00-05:00 2023-11-28T14:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 12:00:00 2023-11-28 02:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Modi Zhu]]> 27707 School of Civil and Environmental Engineering

Ph.D. Thesis Defense Announcement

by: Modi Zhu

AN OBSERVATIONAL AND MODELING STUDY ON ENERGY, WATER, AND CARBON TRANSPORT IN ECO-HYDRO-METEOROLOGICAL SYSTEMSBy STUDENT

Advisor:

Dr. Jingfeng Wang (CEE)

Committee Members:   Dr. Aris P Georgakakos (CEE), Dr. Jian Luo (CEE), Dr. Yi Deng (EAS), Dr. Heping Liu (Washington State University)

Date and Time:  Wednesday, November 29th, 2023, 2:00 PM - 5:00 PM EST

Location: (Hybrid) Mason 2119 and Zoom

]]> Tatianna Richardson 1 1700078168 2023-11-15 19:56:08 1700078168 2023-11-15 19:56:08 0 0 event AN OBSERVATIONAL AND MODELING STUDY ON ENERGY, WATER, AND CARBON TRANSPORT IN ECO-HYDRO-METEOROLOGICAL SYSTEMS

]]>
2023-11-29T14:00:00-05:00 2023-11-29T17:00:00-05:00 2023-11-29T17:00:00-05:00 2023-11-29 19:00:00 2023-11-29 22:00:00 2023-11-29 22:00:00 2023-11-29T14:00:00-05:00 2023-11-29T17:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 02:00:00 2023-11-29 05:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Kejun Yin]]> 27707 Mr. Kejun Yin

 

Thesis Title: "Monitoring drug- and glycosylation-induced protein interaction and structure changes using quantitative structural proteomics"

 

Thursday, Dec 7th, 2023 at 1:00 PM
Location: 4029 EBB

 

Committee Members:

 

Prof. Ronghu Wu (advisor) - School of Chemistry and Biochemistry

Prof. Facundo M. Fernández - School of Chemistry and Biochemistry

Prof. Neha Garg - School of Chemistry and Biochemistry

Prof. Amanda Stockton - School of Chemistry and Biochemistry

Prof. Mark Styczynski - School of Chemical & Biomolecular Engineering

 

]]> Tatianna Richardson 1 1700077801 2023-11-15 19:50:01 1700077801 2023-11-15 19:50:01 0 0 event Monitoring drug- and glycosylation-induced protein interaction and structure changes using quantitative structural proteomics

]]>
2023-12-07T13:00:00-05:00 2023-12-07T14:00:00-05:00 2023-12-07T14:00:00-05:00 2023-12-07 18:00:00 2023-12-07 19:00:00 2023-12-07 19:00:00 2023-12-07T13:00:00-05:00 2023-12-07T14:00:00-05:00 America/New_York America/New_York datetime 2023-12-07 01:00:00 2023-12-07 02:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[PhD Defense by Alex Beach]]> 27707 Alex Beach

BioE PhD Defense Presentation

November 27th, 2023, 9:00 AM

Location: Suddath Seminar Room 1128

Zoom Link: https://gatech.zoom.us/j/92051473720?pwd=THhYTVp2NTU3cVMvbW1FSURWSVdNQT09

 

Advisor:

Dr. Krishnendu Roy (Engineering, Vanderbilt University)

 

Committee Members:

Dr. Andres García (ME, Georgia Institute of Technology)

Dr. Erik Dreaden (BME, Georgia Institute of Technology)

Dr. Valeria Milam (MSE, Georgia Institute of Technology)

Dr. Susan M. Thomas (ME, Georgia Institute of Technology)

 

Utilizing Combinatory Adjuvant-Loaded Chitosan-Derived Nanoparticles for a Joint SARS-CoV-2/Influenza Vaccine

In the wake of the SARS-CoV-2 pandemic and the need for yearly vaccination for flu, there is an ever-growing demand for a single vaccine formulation that can target and immunize against both pathogens. While investigation is ongoing for joint vaccine candidates, the current focus has been mainly on the simultaneous administration of separate vaccines rather than a new hybrid vaccine design. In this work, we have designed and synthesized chitosan and chitosan-IAA-based nanoparticles to use as a platform for combinatorial delivery of multiple vaccine-adjuvants together with soluble delivery of flu and SARS-CoV-2 antigens. Specifically, we have used a combination of the TLR9 agonist CpG and the RLR agonist pUUC. In vitro testing in two distinct primary bone-marrow-derived antigen-presenting cell (APC) cultures demonstrated a strong cell-phenotype-dependent cytokine response to these nanoparticle systems. After administering these with SARS-CoV-2 and H5N1 influenza antigens in a dual-vaccine formulation, we confirmed high pathogen-specific antibody titers in serum and BAL fluid. Our results provide further insights into the impact of immune cell phenotype on vaccine responses and show promise for creating a novel joint subunit vaccine for two prevalent pathogens.

 

]]> Tatianna Richardson 1 1700077663 2023-11-15 19:47:43 1700077663 2023-11-15 19:47:43 0 0 event Utilizing Combinatory Adjuvant-Loaded Chitosan-Derived Nanoparticles for a Joint SARS-CoV-2/Influenza Vaccine

]]>
2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27T11:00:00-05:00 2023-11-27 14:00:00 2023-11-27 16:00:00 2023-11-27 16:00:00 2023-11-27T09:00:00-05:00 2023-11-27T11:00:00-05:00 America/New_York America/New_York datetime 2023-11-27 09:00:00 2023-11-27 11:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Invited Lecture | Semiconductor Innovation – New Frontiers in the Semiconductor Universe]]> 36172 Date: Monday, November 20, 2023

Time: 1:30 p.m. - 2:30 p.m.

Location: Van Leer 218

Speaker: Dr. Jack Sun

Speaker’s Title: Dean and Chair Professor

Speaker’s Affiliation: Industry Academia Innovation School (IAIS), NYCU

Abstract:
Semiconductor is synonymous with innovation. The transistor invention more than 75 years ago was the Big Bang of the semiconductor universe. Semiconductor is pervasive now and indispensable in sustainable future societies. The semiconductor universe continues to expand, and we are well into a “Super Moore” era with 3Dx3D System Scaling which enabled powerful generative AI models such as ChatGPT to transform human societies. The parameter count of ChatGPT-4 LLM is more than 1 trillion and doubling every 4 months, escalating workload and power consumption exponentially. This pace far exceeds the what CMOS and 3Dx3D system scaling can support. We need a paradigm shift with new AI/Compute architectures and energy efficient semiconductor technologies with more than 100X -1000X energy efficiency towards POPS/W and EOPS/W ubiquitous AI compute across data center, edge, and end devices. In this talk, we’ll provide some perspectives and our research efforts on these new frontiers and grand challenges/opportunities for energy-efficient compute/AI, communication, and energy conversion, e.g., emerging memories with in-memory-compute (non-Von-Neumann), materials and devices for non-charge-based logic, new semiconductor channel materials for 3Dx3D, and new AI architectures/circuits such as Green AI and quantum computing. We’ll also give an overview of our new school, i.e., IAIS for semiconductor talent cultivation. An innovative, vibrant, efficient, and secure global semiconductor supply chain and a symbiotic semiconductor ecosystem among academia, industry, and governments will benefit the whole world.

Biographical Sketch of the Speaker:
Dean and Chair Professor Jack Sun, Industry Academia Innovation School (IAIS), NYCU. Dr. Jack Sun is an IEEE Life Fellow. He received his PhD degree from University of Illinois, Urbana-Champaign. He devoted his career to the advancement of semiconductor technology with outstanding contributions to the semiconductor industry globally and in Taiwan. He and co-workers did pioneering work on deep-sub-micron n+/p+-poly CMOS, cryo-CMOS, high-performance Bipolar, SiGe HBT, and BiCMOS at IBM T.J. Watson Research Center from 1983 to 1997. Prior to his latest endeavor in leading the new school at NYCU for semiconductor and AI systems talent development and research, Dr. Sun served as VP of R&D and CTO at TSMC before retiring in 2018. He and coworkers helped establish TSMC as the foundry technology leader with energy efficient CMOS, RF-CMOS, and 3Dx3D system scaling for smartphones, WIFI, mobile computing, GPU, FPGA, AI, HPC, etc., and enabled the innovation and growth of fabless design and product companies that transformed the semiconductor industry. Dr. Sun received many awards, including J.J. Ebers Award in 2015 ( IEEE Electron Devices Society), TSMC Medal of Honor, National Taiwan University Distinguished Alumni Award(2020), ECE Distinguished Alumni Award from University of Illinois, National Management Excellence Award (ROC, 2004), Outstanding Technology Worker Award (ROC, 2003), Ten Most Outstanding Engineer Award of the Chinese Institute of Engineers (2000), and two IBM Outstanding Technical Achievement Awards (0.25um CMOS; 0.5um CMOS). He was a plenary keynote speaker for 2017 IEDM, 2014 A-SSCC, and 2013 VLSI Technology Symposium, besides many invited talks, over 200 journal/conference papers, and 18 US patents. He had served as a Board Member for SRC, Sematech, and National Research Labs (NARL, Taiwan); and as VLSI Technology Symposia / JSAP Executive Committee member, IEEE A-SSCC Steering Committee member and Conference.

 

]]> dwatson71 1 1700074950 2023-11-15 19:02:30 1700076018 2023-11-15 19:20:18 0 0 event Dr. Jack Sun, Dean and Chair Professor at the Industry Academia Innovation School (IAIS), NYCU, will present the seminar, "New Frontiers in the Semiconductor Universe" on November 20, 2023.

]]>
2023-11-20T13:30:00-05:00 2023-11-20T14:30:00-05:00 2023-11-20T14:30:00-05:00 2023-11-20 18:30:00 2023-11-20 19:30:00 2023-11-20 19:30:00 2023-11-20T13:30:00-05:00 2023-11-20T14:30:00-05:00 America/New_York America/New_York datetime 2023-11-20 01:30:00 2023-11-20 02:30:00 America/New_York America/New_York datetime <![CDATA[]]> Shimeng Yu
Professor
shimeng.yu@ece.gatech.edu


 

]]>
<![CDATA[MS Defense by Yijing Wang]]> 27707 THE SCHOOL OF INDUSTRIAL DESIGN 

GEORGIA INSTITUTE OF TECHNOLOGY 

Under the provisions of the regulations for the degree 

 

MASTER OF INDUSTRIAL DESIGN

on

Monday, November 27, 2023

11:00 a.m. –12:30 a.m. EST

online

 

Yijing Wang

will present a thesis defense entitled,

Empowering Breast Self-Awareness: Integrating Augmented Reality for Comprehensive Breast Self-Examination

 

Advisor:

Dr. Leila Aflatoony, Assistant Professor, School of Industrial Design

Committee:

Timothy Purdy, Senior Lecturer, School of Industrial Design

Santiago Arconada Alvarez, Co-Director of Apps and Digital Platforms, Emory University

 

Faculty and students are invited to attend this presentation. 

 

 

 

Abstract 

In recent years, Augmented Reality (AR) has seen a growing application in the healthcare industry, revolutionizing patient care, medical training, and diagnostics. In alignment with this technological trend, this thesis explores the development and evaluation of an innovative mobile application that harnesses the power of AR to enhance breast self-examinations. This application offers real-time, step-by-step instructions projected onto the user's body to ensure precise self-examinations, supplemented by personalized feedback and guidance for follow-up actions. Through this research, we have gained valuable insights into the fundamental pain points users encounter in breast self-examination, user attitudes toward the application of AR technology in this domain, and their reactions to the newly designed experience. These findings provide a wealth of information and assistance in shaping the future of breast self-examination, offering a more informed and enhanced user experience.

]]> Tatianna Richardson 1 1699887751 2023-11-13 15:02:31 1700072456 2023-11-15 18:20:56 0 0 event Empowering Breast Self-Awareness: Integrating Augmented Reality for Comprehensive Breast Self-Examination

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2023-11-27T11:00:43-05:00 2023-11-27T12:30:00-05:00 2023-11-27T12:30:00-05:00 2023-11-27 16:00:43 2023-11-27 17:30:00 2023-11-27 17:30:00 2023-11-27T11:00:43-05:00 2023-11-27T12:30:00-05:00 America/New_York America/New_York datetime 2023-11-27 11:00:43 2023-11-27 12:30:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[DramaTech announces Auditions for Animals Out of Paper]]> 27738 Auditions for Animals Out of Paper will be held on Tuesday, 11/28 at 7pm in the Black Box.  The audition will be warm readings. You don't need to prepare anything, but read through the script and the sides in advance of the audition.

ABOUT THE SHOW:
Animals Out of Paper is an uncommon love story from acclaimed playwright Rajiv Joseph, Pulitzer Prize Finalist for Bengal Tiger at the Baghdad Zoo. Andy, a calculus teacher and avid fan, pressures a reclusive Ilana, a world famous origami artist, into becoming an unwitting mentor to a troubled teenage prodigy, Suresh. These three intriguingly flawed characters begin to reshape and mold each other’s lives in much the same way they fold and crease their origami art.

ABOUT THE CHARACTERS:
Ilana - 30s, female presenting, any ethnicity - Ilana, a world-renowned origami artist, has become a bit of recluse after her marriage ended and her dog ran away.

Andy - 30s, male presenting, any ethnicity - Andy is a high school calculus teacher and avid fan of Ilana's work and origami in general. He is also an advocate for his student, Suresh.

Suresh - 17, male presenting, Of Indian/Pakistani descent - Suresh is a troubled student who recently lost his mother. He has natural abilities in math (and therefore origami).

]]> Melissa Foulger 1 1700071366 2023-11-15 18:02:46 1700071424 2023-11-15 18:03:44 0 0 event Auditions are being held 11/28 at 7pm at DramaTech

]]>
2023-11-28T19:00:00-05:00 2023-11-28T22:00:00-05:00 2023-11-28T22:00:00-05:00 2023-11-29 00:00:00 2023-11-29 03:00:00 2023-11-29 03:00:00 2023-11-28T19:00:00-05:00 2023-11-28T22:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 07:00:00 2023-11-28 10:00:00 America/New_York America/New_York datetime <![CDATA[DramaTech Auditions]]> DramaTech Theatre

info@dramatech.org

404-892-3481

www.dramatech.org

]]>
<![CDATA[MS Defense by Chaeeun Park]]> 27707 THE SCHOOL OF INDUSTRIAL DESIGN 

GEORGIA INSTITUTE OF TECHNOLOGY 

Under the provisions of the regulations for the degree 

 

MASTER OF INDUSTRIAL DESIGN

on

Monday, November 27, 2023

4:00 p.m. – 5:30 p.m. EST

Hybrid-College of Design -West Architecture -Room 155

Join Zoom Meeting

https://gatech.zoom.us/j/3871127587?pwd=S1pyU3NDRllFSnZROG9rVVJEemduQT09                                                             Meeting ID: 387 112 7587                                                                           Passcode: 393107

Chaeeun Park

will present a thesis defense entitled,

"Designing an Interactive Experience for Local Elections Information to Increase Civic  Participation Amongst Young Adults"

Advisor:

Dr. EunSook Kwon – Chair and Professor, Georgia Tech School of Industrial Design

Committee:

Florian Vollmer, Lecturer – Georgia Tech School of Industrial Design

Eric Chiu – UX Researcher/Strategist

 

Faculty and students are invited to attend this presentation. 

Abstract

            

Americans are uniquely situated in that they have more opportunities than people in other countries to vote due to the combination of municipal, state, and national elections. However out of these elections, local elections suffer from the lowest voter turnout despite the fact that these elections hold major influence in the daily lives of local residents. Paired with this, young, voting-aged adults (aged 18-29) have different frameworks for understanding and engaging with politics from previous generations. This divergence is rooted in their reliance on trusted personal networks in a vast sea of political information as well as their interest in specific social causes as opposed to the mechanisms of traditional political institutions. This study examines how young, voting-aged adults (ages 18-29) are both motivated and demoralized from civic engagement. Through design intervention, it explores how interactive games can help motivate young adults to become more civically engaged in their local elections through demystifying the perceived complex hostility of politics by utilizing roleplaying and gamification, helping young adults learn more about what is happening in their local environment, and fostering a cooperative model of civic engagement based on guided discussion.  


 

]]> Tatianna Richardson 1 1700071029 2023-11-15 17:57:09 1700071029 2023-11-15 17:57:09 0 0 event Designing an Interactive Experience for Local Elections Information to Increase Civic  Participation Amongst Young Adults

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<![CDATA[TASP Alumni Event]]> 36009 A reunion for alumni who graduated between 1983-93 featuring a keynote speech by a distinguished alumnus.

]]> cwhittle9 1 1694718734 2023-09-14 19:12:14 1700069395 2023-11-15 17:29:55 0 0 event An alumni reunion for the Master of Science in Technology and Science Policy program.

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2023-12-13T18:00:00-05:00 2023-12-13T21:00:00-05:00 2023-12-13T21:00:00-05:00 2023-12-13 23:00:00 2023-12-14 02:00:00 2023-12-14 02:00:00 2023-12-13T18:00:00-05:00 2023-12-13T21:00:00-05:00 America/New_York America/New_York datetime 2023-12-13 06:00:00 2023-12-13 09:00:00 America/New_York America/New_York datetime <![CDATA[]]> Meenu Mukherji
mmukherji3@gatech.edu

]]>
<![CDATA[PhD Defense by Faris Almatouq]]> 27707 Faris Almatouq

(Advisor: Prof. Zhigang Jiang]

Will defend a doctoral thesis entitled,

Synthesis and Characterization of Hexagonal Boron Nitride for Neutron Radiation Detection

On

[date & time] Tuesday, December 5, 2023 at 12:00 p.m.

[building & room] Howey, Room N110

Abstract

The assessment of radiation impact on astronauts during extravehicular activities is limited to post-mission analysis, using data collected and reported by dosimeter badges. This highlights the necessity for advancements in dosimeter technology, such as the development of systems capable of real-time radiation detection, to enhance the safety of astronauts from radiation exposure. This research focuses on developing such a technology by incorporating graphene field-effect transistors (gFETs) with monoisotopic hexagonal boron nitride (hBN).

The monoisotopic hBN studied in this work was synthesized in-house through a metal flux method using nickel and chromium. The hBN was characterized through various spectroscopic techniques, including Raman, photoluminescence, ultraviolet-visible absorbance, and X-ray diffraction, before and after exposure to neutron irradiation. The study used two types of neutron sources, a deuterium-deuterium neutron generator, and an Americium-Beryllium isotopic source, to observe the effects of neutron irradiation on hBN. It was found that neutron irradiation could induce specific defects in hBN, particularly the VB- defect. Then, monoisotopic hBN was transferred to a gFET to fabricate the proposed device. The resistance of the device was observed to increase in correlation with the total thermal neutron flux. This change in resistance can be attributed to the interaction between the device and alpha particles generated from thermal neutron capture by Boron-10. The ability of this device to detect changes in resistance under neutron irradiation in real time may offer a significant advancement in ensuring astronaut safety by providing real-time monitoring of neutron exposure, which is a critical aspect of cosmic radiation.

Committee

• Dr. Sharmistha Mukhopadhyay– School of Nuclear and Radiological Engineering

• Prof. Phillip N. First– School of Physics

• Prof. Thomas Orlando– School of Chemistry and Biochemistry

• Prof. Walter de Heer – School of Physics

]]> Tatianna Richardson 1 1700065535 2023-11-15 16:25:35 1700065535 2023-11-15 16:25:35 0 0 event Synthesis and Characterization of Hexagonal Boron Nitride for Neutron Radiation Detection

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2023-12-03T12:00:00-05:00 2023-12-03T13:00:00-05:00 2023-12-03T13:00:00-05:00 2023-12-03 17:00:00 2023-12-03 18:00:00 2023-12-03 18:00:00 2023-12-03T12:00:00-05:00 2023-12-03T13:00:00-05:00 America/New_York America/New_York datetime 2023-12-03 12:00:00 2023-12-03 01:00:00 America/New_York America/New_York datetime <![CDATA[]]>
<![CDATA[Solving the Policy Puzzle of Generative AI]]> 36009 Much has been made of the threats associated with emerging generative AI technologies. The range of anxieties includes job loss, biased decision-making, and even physical harm to human beings. A more bullish view, that these new technologies will unleash productivity on a scale similar to the telephone or the automobile, has also emerged. But which view is right? Join our esteemed speakers from Carnegie Mellon, Georgia Tech, and Stanford to debate and discuss the AI Revolution and its implications for our society. Moderated by Wall Street Journal’s Christopher Mims.

 

Register by Sunday, Nov 19. You will receive a Zoom login link in a confirmation email. To help shape the conversation, we encourage you to pre-submit questions for the panelists. Submit questions by emailing Jorjette Hatfield at jhatfiel@andrew.cmu.edu.

If you require accessibility accommodations for this event or have general questions, contact Jorjette Hatfield at
jhatfiel@andrew.cmu.edu.

Panelists

]]> cwhittle9 1 1700063366 2023-11-15 15:49:26 1700063366 2023-11-15 15:49:26 0 0 event Much has been made of the threats associated with emerging generative AI technologies. The range of anxieties includes job loss, biased decision-making, and even physical harm to human beings. A more bullish view, that these new technologies will unleash productivity on a scale similar to the telephone or the automobile, has also emerged. But which view is right? Join our esteemed speakers from Carnegie Mellon, Georgia Tech, and Stanford to debate and discuss the AI Revolution and its implications for our society. 

 

]]>
2023-11-20T12:30:00-05:00 2023-11-20T13:30:00-05:00 2023-11-20T13:30:00-05:00 2023-11-20 17:30:00 2023-11-20 18:30:00 2023-11-20 18:30:00 2023-11-20T12:30:00-05:00 2023-11-20T13:30:00-05:00 America/New_York America/New_York datetime 2023-11-20 12:30:00 2023-11-20 01:30:00 America/New_York America/New_York datetime <![CDATA[]]> Jorjette Hatfield
jhatfiel@andrew.cmu.edu

]]>
<![CDATA[ISyE Summer Programs in Europe & Asia: Information Session]]> 35787 Information session for Industrial Systems and Engineering students who are interested in a Summer abroad program. Come learn about the ISyE Summer Programs in Europe and Asia. Still accepting applications for summer 2024.

]]> tduong45 1 1700053703 2023-11-15 13:08:23 1700053952 2023-11-15 13:12:32 0 0 event Join us to learn about a 12-credit study abroad opportunity this summer for ISyE students!

]]>
2023-12-05T11:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05T12:00:00-05:00 2023-12-05 16:00:00 2023-12-05 17:00:00 2023-12-05 17:00:00 2023-12-05T11:00:00-05:00 2023-12-05T12:00:00-05:00 America/New_York America/New_York datetime 2023-12-05 11:00:00 2023-12-05 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> Kayla Cooper

kayla.cooper@oie.gatech.edu

]]>
672381 672381 image <![CDATA[ISyE Summer Programs Applications Open for Summer 2024]]> image/jpeg 1700053804 2023-11-15 13:10:04 1700053854 2023-11-15 13:10:54
<![CDATA[PhD Defense by Thomas Pho]]> 27707  

Thomas Pho

BioE PhD Defense Presentation

 

Time and Date: 10 AM, Wednesday, November 29th, 2023

Location: Krone Engineered Biosystems Building Krone room 5029

Virtual Link: https://gatech.zoom.us/j/94794740132

 

Advisor: Julie Champion, Ph.D. (Chemical and Biomolecular Engineering)

 

Committee Members:

Jennifer E. Curtis, Ph.D. (Physics)

James E. Dahlman, Ph.D. (Biomedical Engineering)

Ravi S. Kane, Ph.D. (Chemical and Biomolecular Engineering)

Mark Prausnitz, Ph.D. (Chemical and Biomolecular Engineering) 

 

 

 

Surface Engineering of Protein Nanoparticles for Intranasal Vaccination

 

Intranasal delivery of vaccines offers a promising alternative approach to invasive intramuscular injection, with additional benefits such as inducing mucosal antibodies and cellular responses to neutralize pathogens before entering systemic circulation. However, nasal secretions and mucosa are biological barriers that have been shown to inhibit the delivery of antigens and nanoparticles to nasal-associated lymphoid tissue (NALT) and lungs. Protein nanoparticles are composed of proteins at high mass-to-carrier ratio, while allowing for biocompatibility and tunable physiochemical properties. They have been demonstrated to be effective vaccines and drug delivery carriers. The surfaces of these carriers can be decorated with coatings and chemical modifications, which can alter transport and immune responses due to their interaction with biological barriers and cells. In this work, we evaluate intranasal localization of engineered surface-coated protein nanoparticles and assess their immune response following vaccination in murine models. To understand the principles behind modifying nanoparticle surface formulations will assist in improving accessibility to the NALT and delivery of protein-based nanocarriers for non-vaccine intranasal delivery. We screened ovalbumin nanoparticles coated with polyethylene glycol (PEG) and layer-by-layer coating of trimethyl chitosan and CpG oligodeoxynucleotide adjuvants delivered intranasally in murine models and compared to unmodified protein nanoparticles. The localization and biodistribution were observed using non-invasive in vivo imaging and for regional localization and tissues using both flow cytometry and immunohistochemistry. Surface-coated nanoparticles were used for intranasal vaccination in a murine model and characterized for the mucosal antigen-specific response, as well as systemic humoral and cellular responses through antibody titers and T-cell activation. The findings and designs from screening coatings with model ovalbumin nanoparticles were incorporated into influenza antigen nanoparticle formulations.  Two influenza antigens (hemagglutinin and matrix protein 2 - (A/California/07/2009(H1N1)) were used to construct a subunit protein nanoparticle vaccine with surface structure control using bioconjugation. A layer-by-layer (LBL) coating approach was used to survey specific formulation based on their administration route. Overall, our findings indicated that LBL surface formulation improved nasal biodistribution and immune response upon intranasal delivery, highlighting a new nanoparticle formulation for nasal vaccines. 

 

 

 

]]> Tatianna Richardson 1 1700053305 2023-11-15 13:01:45 1700053305 2023-11-15 13:01:45 0 0 event Surface Engineering of Protein Nanoparticles for Intranasal Vaccination

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<![CDATA[NEH Grants Workshop]]> 36009 Please join us for an IAC-sponsored NEH Grants Workshop.

This event will be led by Beauty Bragg, a program officer in NEH’s Division of Research Programs. Bragg will provide an overview of NEH funding opportunities, lead a mock NEH review session, and be available to meet 1:1 with faculty to discuss their specific proposals or proposal ideas. Registration requested.

]]> cwhittle9 1 1699372141 2023-11-07 15:49:01 1699996830 2023-11-14 21:20:30 0 0 event Please join us for an overview of NEH grant programs and insight into how to craft strong NEH applications.

]]>
2024-01-26T09:45:00-05:00 2024-01-26T13:30:00-05:00 2024-01-26T13:30:00-05:00 2024-01-26 14:45:00 2024-01-26 18:30:00 2024-01-26 18:30:00 2024-01-26T09:45:00-05:00 2024-01-26T13:30:00-05:00 America/New_York America/New_York datetime 2024-01-26 09:45:00 2024-01-26 01:30:00 America/New_York America/New_York datetime <![CDATA[]]> Aaron Levine
adlevine@gatech.edu

]]>
672311 672311 image <![CDATA[NEH Grants Workshop.png]]> image/png 1699468788 2023-11-08 18:39:48 1699468788 2023-11-08 18:39:48 <![CDATA[Register Now]]>
<![CDATA[School of Physics Colloquium]]> 36489 Speaker: Walt A. de Heer (Georgia Tech)

Host: Colin Parker

Title: Breakthroughs in epitaxial graphene electronics: semiconducting graphene and the spectacular edge state.

Abstract: Graphene electronics was conceived at Georgia Tech 22 years ago when the first graphene, devices were produced using graphene grown on silicon carbide substrates (so called epigraphene) [1], and the worlds’ first graphene electronics patent was filed[2]. The GT team has made steady progress since. Several years ago we noted that narrow graphene ribbons exhibited resistances that are always close to 26 k Ohms, which corresponds to the resistance quantum h/e2 where h is Planck’s constant an e is the charge of the electron, that turned out to be caused by a unique state at the edge of the ribbon. We have recently shown that this edge state does not involve an electron or a hole, which are the usual carriers of currents in graphene, but the carrier appears to be a combination of the two to form a zero-energy mode [3]. Moreover, several of its properties resemble those of a Majorana fermion which was predicted in 1937. Very recently we have also discovered that the first graphene layer to grow on the silicon terminated silicon carbide crystal face, which has long been considered to an insulator, is in fact an excellent semiconductor when it is properly annealed. It is found to have a band gap of 0.6 eV and a room temperature mobility that exceeds 5000 cm2/Vs, which is greater than that of silicon and exceeds all other 2D semiconductors by a factor of 20 or more (Nature, in press). These two breakthrough discoveries put epigraphene on the path to become an important new 2D electronic material.

1. Berger, C., et al., Ultrathin Epitaxial Graphite:  2D Electron Gas Properties and a Route toward Graphene-based Nanoelectronics. The Journal of Physical Chemistry B, 2004. 108(52): p. 19912

2. de Heer, W.A., Berger,C, First,P.N, Patterned thin film graphite devices and method for making same. US patent US7015142B2 (Provisional filed Jun. 12, 2003).

3. Prudkovskiy, V.S., et al., An epitaxial graphene platform for zero-energy edge state nanoelectronics. Nature Communications, 2022. 13(1): p. 7814.

Bio: Walt A. de Heer is a Georgia Tech Regents’ Professor of Physics. His pioneering epitaxial graphene program, initiated in 2001, was inspired by his discovery of the room temperature ballistic transport properties of carbon nanotubes in 1998 and focuses on developing a viable silicon carbide platform for graphene-based nanoelectronics, which is currently his main interest. He has published more than 400 papers on epigraphene, carbon nanotubes and metallic clusters. He has an h-index of 97, and he has received the Web of Science Group’s Highly Cited Researcher Award yearly from 2010-2019.

]]> jminniefie3 1 1699993365 2023-11-14 20:22:45 1699993927 2023-11-14 20:32:07 0 0 event Abstract: Graphene electronics was conceived at Georgia Tech 22 years ago when the first graphene, devices were produced using graphene grown on silicon carbide substrates (so called epigraphene) [1], and the worlds’ first graphene electronics patent was filed[2]. The GT team has made steady progress since. Several years ago we noted that narrow graphene ribbons exhibited resistances that are always close to 26 k Ohms, which corresponds to the resistance quantum h/e2 where h is Planck’s constant an e is the charge of the electron, that turned out to be caused by a unique state at the edge of the ribbon. We have recently shown that this edge state does not involve an electron or a hole, which are the usual carriers of currents in graphene, but the carrier appears to be a combination of the two to form a zero-energy mode [3]. Moreover, several of its properties resemble those of a Majorana fermion which was predicted in 1937. Very recently we have also discovered that the first graphene layer to grow on the silicon terminated silicon carbide crystal face, which has long been considered to an insulator, is in fact an excellent semiconductor when it is properly annealed. It is found to have a band gap of 0.6 eV and a room temperature mobility that exceeds 5000 cm2/Vs, which is greater than that of silicon and exceeds all other 2D semiconductors by a factor of 20 or more (Nature, in press). These two breakthrough discoveries put epigraphene on the path to become an important new 2D electronic material.

1. Berger, C., et al., Ultrathin Epitaxial Graphite:  2D Electron Gas Properties and a Route toward Graphene-based Nanoelectronics. The Journal of Physical Chemistry B, 2004. 108(52): p. 19912

2. de Heer, W.A., Berger,C, First,P.N, Patterned thin film graphite devices and method for making same. US patent US7015142B2 (Provisional filed Jun. 12, 2003).

3. Prudkovskiy, V.S., et al., An epitaxial graphene platform for zero-energy edge state nanoelectronics. Nature Communications, 2022. 13(1): p. 7814.

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<![CDATA[PhD Defense by Patrick Grady]]> 27707 Title: Sensing Touch from Vision for Humans and Robots

 

Date: Tuesday, November 28, 2023

Time: 2:00pm-4:00pm EST

Location: Klaus 1116
Zoom: https://gatech.zoom.us/j/96467976963?pwd=MkxSUDFnaFJ6eFp0dXBkMHNQU3BtZz09

 

Patrick Grady

Robotics PhD Student

School of Electrical and Computer Engineering

Georgia Institute of Technology

Committee:

Dr. James Hays (Advisor) – School of Interactive Computing, Georgia Tech

Dr. Charlie Kemp (Advisor) – CTO, Hello Robot

Dr. Seth Hutchinson – School of Interactive Computing, Georgia Tech

Dr. Animesh Garg – School of Interactive Computing, Georgia Tech

Dr. Chengcheng Tang – Meta Reality Labs

 

Abstract:

To affect their environment, humans and robots use their hands and grippers to push, pick up, and manipulate the world around them. At the core of this interaction is physical contact which determines the underlying mechanics of the grasp. While contact is useful in understanding manipulation, it is difficult to measure. In this thesis, we explore methods to estimate contact between humans, robots, and objects using easy-to-collect imagery. First, we demonstrate a method which leverages subtle visual changes to infer the pressure between a human hand and surface using RGB images. We initially explore this work in a constrained laboratory setting, but also develop a weakly-supervised data collection technique to estimate hand pressure in less constrained settings. A parallel approach allows us to estimate the pressure and force that soft robotic grippers apply to their environments, allowing for precise closed-loop control of a robot. Finally, we develop a joint pose and contact estimator which may generalize to internet-scale images. Our model leverages multiple heterogeneously labeled datasets and images with contact labeled by human annotators. Overall, this thesis makes progress towards understanding human and robot manipulation from only visual sensing.

]]> Tatianna Richardson 1 1699991608 2023-11-14 19:53:28 1699991608 2023-11-14 19:53:28 0 0 event Sensing Touch from Vision for Humans and Robots

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<![CDATA[ISyE Seminar - Yeganeh Alimohammadi]]> 34977 Title:

Epidemic Forecasting on Networks: Bridging Local Samples with Global Outcomes

Abstract:

Epidemics of all kinds, from infectious diseases to technologies and ideas, spread through the hidden network of our social interactions. The structure of this underlying network determines the patterns of the epidemic spread, but mapping this network is expensive, and modeling it accurately is difficult.

In this talk, I will introduce a data-driven and model-free approach to predict the time evolution of epidemics that requires surprisingly few local network samples to forecast epidemic spread accurately. I will establish theoretical guarantees for the precision of our local estimator for a general class of networks, supporting these claims with concrete empirical evidence. The technical tools discussed in the talk can provide new perspectives on various applications of network data, beyond the scope of epidemics.

Bio:

Yeganeh is a final-year Ph.D. candidate in Management Science and Engineering at Stanford University, where she is advised by Amin Saberi. During her PhD, she was also a research fellow at UC Berkeley's Simons Institute for the Theory of Computing. Her research focuses on analyzing large-scale networks and stochastic systems, employing tools from applied probability and algorithm design to address operations challenges.

]]> Julie Smith 1 1699986002 2023-11-14 18:20:02 1699991089 2023-11-14 19:44:49 0 0 event Abstract:

Epidemics of all kinds, from infectious diseases to technologies and ideas, spread through the hidden network of our social interactions. The structure of this underlying network determines the patterns of the epidemic spread, but mapping this network is expensive, and modeling it accurately is difficult.

In this talk, I will introduce a data-driven and model-free approach to predict the time evolution of epidemics that requires surprisingly few local network samples to forecast epidemic spread accurately. I will establish theoretical guarantees for the precision of our local estimator for a general class of networks, supporting these claims with concrete empirical evidence. The technical tools discussed in the talk can provide new perspectives on various applications of network data, beyond the scope of epidemics.

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<![CDATA[PhD Defense by Lauren Liebman]]> 27707 Lauren Liebman

BME PhD Defense Presentation

Date: 2023-11-30
Time: 3pm
Location / Meeting Link: IBB Suddath Room (1128) / https://emory.zoom.us/j/96655461798?pwd=Skp6bUxnVm12a0ZZQmxPbVNxbmtZUT09

Committee Members:
J. Brandon Dixon, PhD (Advisor); Edward Botchwey, PhD; Zachary Buchwald, MD/PhD; Andres Garcia, PhD; Johnna Temenoff, PhD


Title: Targeting the Draining Lymphatic Network as a Regulator of Melanoma Growth

Abstract:
The lymphatic system is a complex network of lymph nodes and lymphatic vessels that performs crucial functions in human health and disease. In the context of cancers, including melanoma, the lymphatic system plays established roles in metastasis and immune suppression. However, recent work has demonstrated involvement of the tumor-draining lymph node (TDLN) in generating antitumor immunity. We hypothesize that, like the TDLN, tumor-draining lymphatic vessels may have key contributions to tumor control. While many targeted platforms exist to deliver therapies to lymph nodes, strategies to specifically modulate lymphangiogenesis or lymphatic vessel pumping function remain understudied. Therefore, in this work we investigate the role of tumor-draining lymphatic vessels and identify therapeutic strategies to improve their function. In Aim 1, we utilized a novel murine melanoma model in which we surgically disrupted the lymphatic vessel network draining from the tumor to the TDLN while leaving the TDLN intact. Via noninvasive imaging of lymphatic transport, measurements of tumor growth kinetics, and histological analyses, we investigated the effects of lymphatic vessel excision surgery on tumor progression and pathology. We also identified resulting changes in tumor-infiltrating immune cell populations after disruption of the lymphatic vessel network. Then, in Aim 2, we evaluated the efficacy of multiple therapeutic strategies, namely lymphangiogenic protein VEGF-C, mesenchymal stem cells engineered to overexpress VEGF-C, lymphatic endothelial cell-specific lipid nanoparticles loaded with VEGF-C mRNA, and a drug-loaded lymphatic-targeted hydrogel, to improve lymphatic vessel pumping function and reduce hallmarks of lymphatic injury in vivo. Overall, our findings indicate a critical role for tumor-draining lymphatic vessels in melanoma control, and support the use of lymphatic-targeted therapeutic strategies to enhance lymphatic function.

]]> Tatianna Richardson 1 1699989319 2023-11-14 19:15:19 1699989319 2023-11-14 19:15:19 0 0 event Targeting the Draining Lymphatic Network as a Regulator of Melanoma Growth

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<![CDATA[PhD Defense by Veronica Pawlik]]> 27707 Ms. Veronica Pawlik


Thesis Title: "SEED-MEDIATED SYNTHESIS OF GOLD NANOCRYSTALS: THE EFFECTS OF LATTICE MISMATCH ON GROWTH PATTERNS”

 

Monday, December 4th, 2023 at 12:00 PM

Location: MoSE 2222B or through zoom: https://gatech.zoom.us/j/94147474122

 

Committee Members:

 

Prof. Younan Xia (Advisor)- School of Chemistry and Biochemistry

Prof. Angus P. Wilkinson- School of Chemistry and Biochemistry

Prof. Joseph Sadighi- School of Chemistry and Biochemistry

Prof. Jesse McDaniel- School of Chemistry and Biochemistry

Prof. Hailong Chen- School of Mechanical Engineering

]]> Tatianna Richardson 1 1699988775 2023-11-14 19:06:15 1699988775 2023-11-14 19:06:15 0 0 event SEED-MEDIATED SYNTHESIS OF GOLD NANOCRYSTALS: THE EFFECTS OF LATTICE MISMATCH ON GROWTH PATTERNS

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<![CDATA[PhD Defense by Viraj Prabhu]]> 27707 Title: Towards Reliable Computer Vision Systems

 

Date: Monday, November 20, 2023

Time: 4:00-6:00pm (ET)

Location: CODA C1115 (Druid Hills) & Zoom

 

Viraj Prabhu

PhD student in Computer Science

School of Interactive Computing

Georgia Institute of Technology

 

Committee

Dr. Judy Hoffman (advisor), School of Interactive Computing, Georgia Institute of Technology

Dr. Dhruv Batra, School of Interactive Computing, Georgia Institute of Technology & Meta

Dr. James Hays, School of Interactive Computing, Georgia Institute of Technology

Dr. Zsolt Kira, School of Interactive Computing, Georgia Institute of Technology

Dr. Sanja Fidler, University of Toronto & NVIDIA

 

Abstract

The real world has infinite visual variation – across viewpoints, time, space, and curation. As deep visual models become ubiquitous in high-stakes applications, their ability to generalize across such variation becomes increasingly important. Such generalization will alleviate the need to label a large corpus for every new deployment, which may be infeasible due to data volume (e.g., autonomous driving) or labeling cost (e.g., medical diagnosis). Further, it is necessary to overcome the natural spatiotemporal distribution shifts that a deployed model will invariably face (e.g., changing geographies and seasons). Finally, such generalization will unlock the possibility of knowledge transfer from inexpensive sources of data (e.g., transferring models trained in simulation to reality). 


In this thesis, I will present opportunities to improve such generalization at different stages of the ML lifecycle. First, I will discuss proactive strategies for training robust models by leveraging simulation to augment the long tail of real training data. Next, I will present reactive strategies to recover from unforeseen distribution shifts via self-supervised domain adaptation. Finally, I will present a framework to stress-test the robustness of vision models by leveraging foundation models for text and image synthesis to generate challenging counterfactual test cases.

]]> Tatianna Richardson 1 1699302882 2023-11-06 20:34:42 1699987868 2023-11-14 18:51:08 0 0 event  Towards Reliable Computer Vision Systems

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<![CDATA[Ph.D. Dissertation Defense - Dayu Zhu]]> 28475 TitleGenerative Deep Learning for Inverse Design: Photonics and Beyond

Committee:

Dr. Azad Naeemi, ECE

Dr. Ali Adibi, ECE

Dr. Andrew Peterson, ECE

Dr. Zhuomin Zhang, ME

]]> Daniela Staiculescu 1 1699985096 2023-11-14 18:04:56 1699985132 2023-11-14 18:05:32 0 0 event The capacity to manipulate the light waves is largely governed by the availability of photonic materials and structures at our disposal. Over the past two decades, the exploration of artificially structured photonic media, notably metamaterials and metasurfaces, represents a central theme in optical science. However, the intricate nature of light-matter interaction at the subwavelength scale results in the design of meta-structures, to date, still largely relying on tedious trial-and-error process with iterative parametric sweeping. This conventional practice, along with existing optimization schemes in the current stage, falls short when it comes to the discovery and design of highly complicated meta-structures or multiplexed optical functionalities.
Addressing this limitation, we introduce a generative deep learning methodology that revolutionizes the inverse design paradigm in photonics. Machine learning, especially deep learning burgeons into an essential asset for the scientific community, fostering the integration of artificial intelligence (AI) into cross-disciplinary research. Very recently, generative deep learning stands out in the inverse design topics, for its capability to produce counterintuitive and high degree-of-freedom candidates, which has the potential to surpass the capacity of human-centric design and traditional optimization process. 
In this work, with a state-of-the-art generative model, we are able to achieve on-demand design of the unit cells of metasurface, i.e. meta-atoms, with free-form patterns and unconventional functionality. Further, incorporating evolutionary strategies enhances our ability to efficiently architect meta-molecules composed of distinct meta-atoms, as well as a new opportunity to explore the fundamentals of light-matter interaction. Moreover, we have developed a versatile deep learning framework for the comprehensive inverse design of multi-layer, multifunctional meta-systems, which is hardly reachable by alternative methodologies. Besides, our comprehensive machine learning framework is also extendable to a breadth of inverse problems across diverse fields, such as non-line-of sight imaging, and the inverse retrieval of the onset time of acute stroke, showcasing its potential as a transformative tool in optical imaging, medical science, and beyond.

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2023-11-17T15:00:00-05:00 2023-11-17T17:00:00-05:00 2023-11-17T17:00:00-05:00 2023-11-17 20:00:00 2023-11-17 22:00:00 2023-11-17 22:00:00 2023-11-17T15:00:00-05:00 2023-11-17T17:00:00-05:00 America/New_York America/New_York datetime 2023-11-17 03:00:00 2023-11-17 05:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom link]]>
<![CDATA[2024 Focus Program]]> 36289 Focus is one of the nation’s premier programs for raising awareness of graduate education. It is designed to attract the brightest underrepresented minority students and encourage them to pursue graduate degrees at Georgia Tech. For more information about the Focus Program, please visit focus.gatech.edu/.

]]> jcao335 1 1699972904 2023-11-14 14:41:44 1699973159 2023-11-14 14:45:59 0 0 event The Focus Program is designed to attract the brightest underrepresented minority students and encourage them to pursue graduate degrees at Georgia Tech.

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2024-01-11T00:00:00-05:00 2024-01-14T23:59:59-05:00 2024-01-14T23:59:59-05:00 2024-01-11 05:00:00 2024-01-15 04:59:59 2024-01-15 04:59:59 2024-01-11T00:00:00-05:00 2024-01-14T23:59:59-05:00 America/New_York America/New_York datetime 2024-01-11 12:00:00 2024-01-14 11:59:59 America/New_York America/New_York datetime <![CDATA[Related Link]]> Sybrina Atwaters, Ph.D.
Focus Program Director
sybrina.atwaters@omed.gatech.edu.

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<![CDATA[Focus Program]]>
<![CDATA[MS Defense by Sidney Scott-Sharoni ]]> 27707 Name: Sidney Scott-Sharoni 

Master’s Thesis Defense Meeting 

Date: Monday, November 27th, 2023 

Time: 2:15 PM

Room location/number: Georgia Tech Library - Price Gilbert 4222 

Optional Zoom Meeting Link: click here 

Password: 281270

  

Advisor: Bruce Walker, Ph.D. (Georgia Tech)  

  

Thesis Committee Members:
Richard Catrambone, Ph.D. (Georgia Tech) 

Scott Moffat, Ph.D. (Georgia Tech) 

Jamie Gorman, Ph.D. (Arizona State University) 

  

Title: Directability through AI Customization: The Effect of Choice on Trust and Acceptance in Highly Automated Vehicles

  

Abstract:  People feel apprehensive about using or relying on highly automated vehicles (American Automotive Association, 2019). One method of assuaging fears involves providing explanations for the system’s behaviors using a Human-Machine Interface (HMI).  However, understanding the amount of information for optimal human-automation interaction can prove difficult due to differences in individuals’ preferences, experiences, and needs. An underexplored method that may account for these discrepancies involves providing users with choices or customization. The Coactive Design Approach suggests that including directability, or the power to influence a system’s actions, may improve how users interact with systems (Johnson et al., 2014). The following study investigated how customization affordances and modified vehicle aspect of a Level 4 automated vehicle affected trust and acceptance. One hundred twenty participants experienced one highly automated simulator drive, during which they engaged in a visually demanding game. A MANOVA assessed the interaction of and main effects of customization availability and modified vehicle aspect on trust and acceptance. While participants who customized had higher average trust and acceptance in the automated vehicle than participants who did not customize, only the main effect of vehicle aspect significantly impacted the multivariate dimension of trust and acceptance in the automated vehicle. That is, modifications to the vehicle impacted users regardless of whether they chose the modification. The game score and subjective trust did significantly correlate to a small, positive extent, indicating that higher trust in a system may improve non-driving related task performance. Future research should continue to investigate the role of choice in the interaction between individuals and highly automated systems to understand the psychological impacts of directability.

]]> Tatianna Richardson 1 1699972375 2023-11-14 14:32:55 1699972375 2023-11-14 14:32:55 0 0 event Directability through AI Customization: The Effect of Choice on Trust and Acceptance in Highly Automated Vehicles

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<![CDATA[Football vs. Georgia]]> 36418 Football hosts Georgia.

]]> sgagliano3 1 1691168652 2023-08-04 17:04:12 1699929282 2023-11-14 02:34:42 0 0 event Football hosts Georgia.

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2023-11-25T19:30:00-05:00 2023-11-25T19:30:00-05:00 2023-11-25T19:30:00-05:00 2023-11-26 00:30:00 2023-11-26 00:30:00 2023-11-26 00:30:00 2023-11-25T19:30:00-05:00 2023-11-25T19:30:00-05:00 America/New_York America/New_York datetime 2023-11-25 07:30:00 2023-11-25 07:30:00 America/New_York America/New_York datetime <![CDATA[]]> 671311 671311 image <![CDATA[Georgia Tech Logo]]> image/jpeg 1691074899 2023-08-03 15:01:39 1691074899 2023-08-03 15:01:39 <![CDATA[2023 Football Schedule]]>
<![CDATA[Exploratory Advising Drop-Ins (Virtual)]]> 36490 Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]> jreid67 1 1699908586 2023-11-13 20:49:46 1699908608 2023-11-13 20:50:08 0 0 event Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

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2023-11-16T14:00:00-05:00 2023-11-16T16:00:00-05:00 2023-11-16T16:00:00-05:00 2023-11-16 19:00:00 2023-11-16 21:00:00 2023-11-16 21:00:00 2023-11-16T14:00:00-05:00 2023-11-16T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-16 02:00:00 2023-11-16 04:00:00 America/New_York America/New_York datetime <![CDATA[Join the Meeting]]> <![CDATA[Exploratory Advising]]>
<![CDATA[Exploratory Advising Drop-Ins (Virtual)]]> 36490 Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

]]> jreid67 1 1699908401 2023-11-13 20:46:41 1699908532 2023-11-13 20:48:52 0 0 event Meet with Exploratory Advisors!

Exploratory Advising is a process that focuses on cross-curricular academic advising, career assessment, and guided exploration of majors and careers to allow students opportunities to interact with advisors, faculty, upper-class students and professionals from different fields. Exploratory Advising allows students to discover their passions and make an informed decision on their major.

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2023-11-16T09:00:00-05:00 2023-11-16T10:30:00-05:00 2023-11-16T10:30:00-05:00 2023-11-16 14:00:00 2023-11-16 15:30:00 2023-11-16 15:30:00 2023-11-16T09:00:00-05:00 2023-11-16T10:30:00-05:00 America/New_York America/New_York datetime 2023-11-16 09:00:00 2023-11-16 10:30:00 America/New_York America/New_York datetime <![CDATA[Join the Meeting]]> <![CDATA[Exploratory Advising]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1699907116 2023-11-13 20:25:16 1699907130 2023-11-13 20:25:30 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

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2023-11-17T15:00:00-05:00 2023-11-17T16:00:00-05:00 2023-11-17T16:00:00-05:00 2023-11-17 20:00:00 2023-11-17 21:00:00 2023-11-17 21:00:00 2023-11-17T15:00:00-05:00 2023-11-17T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-17 03:00:00 2023-11-17 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1699907096 2023-11-13 20:24:56 1699907110 2023-11-13 20:25:10 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

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2023-11-16T15:00:00-05:00 2023-11-16T16:00:00-05:00 2023-11-16T16:00:00-05:00 2023-11-16 20:00:00 2023-11-16 21:00:00 2023-11-16 21:00:00 2023-11-16T15:00:00-05:00 2023-11-16T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-16 03:00:00 2023-11-16 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1699907056 2023-11-13 20:24:16 1699907070 2023-11-13 20:24:30 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

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2023-11-14T15:00:00-05:00 2023-11-14T16:00:00-05:00 2023-11-14T16:00:00-05:00 2023-11-14 20:00:00 2023-11-14 21:00:00 2023-11-14 21:00:00 2023-11-14T15:00:00-05:00 2023-11-14T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-14 03:00:00 2023-11-14 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Pre-Health Virtual Drop-Ins]]> 36490 Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

]]> jreid67 1 1699906414 2023-11-13 20:13:34 1699906972 2023-11-13 20:22:52 0 0 event Meet virtually with Pre-Health Staff to discuss questions about the program and your pre-health path at Georgia Tech and after.

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2023-11-13T15:00:00-05:00 2023-11-13T16:00:00-05:00 2023-11-13T16:00:00-05:00 2023-11-13 20:00:00 2023-11-13 21:00:00 2023-11-13 21:00:00 2023-11-13T15:00:00-05:00 2023-11-13T16:00:00-05:00 America/New_York America/New_York datetime 2023-11-13 03:00:00 2023-11-13 04:00:00 America/New_York America/New_York datetime <![CDATA[]]> <![CDATA[Zoom Link]]>
<![CDATA[Georgia Tech Authors Celebration 2024]]> 27615 Georgia Tech faculty and staff are invited to join the Office of the Executive Vice President for Research and the Library for the annual Georgia Tech Authors Celebration. 

This event celebrates Georgia Tech book publications, showcasing the range and depth of scholarship on our campus. The 2024 event honors authors and editors who have published books between January 2022 and December 2023. 

]]> Serena Wallace 1 1699887328 2023-11-13 14:55:28 1699898608 2023-11-13 18:03:28 0 0 event Georgia Tech faculty and staff are invited to join the Office of the Executive Vice President for Research and the Library for the annual Georgia Tech Authors Celebration. 

This event celebrates Georgia Tech book publications, showcasing the range and depth of scholarship on our campus. The 2024 event honors authors and editors who have published books between January 2022 and December 2023. 

 

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2024-04-11T16:30:00-04:00 2024-04-11T18:30:00-04:00 2024-04-11T18:30:00-04:00 2024-04-11 20:30:00 2024-04-11 22:30:00 2024-04-11 22:30:00 2024-04-11T16:30:00-04:00 2024-04-11T18:30:00-04:00 America/New_York America/New_York datetime 2024-04-11 04:30:00 2024-04-11 06:30:00 America/New_York America/New_York datetime <![CDATA[Scholars Event Network]]> 672363 672363 image <![CDATA[Georgia Tech Authors Celebration 2024]]> image/jpeg 1699888099 2023-11-13 15:08:19 1699888099 2023-11-13 15:08:19
<![CDATA[Fostering an Environment of Belonging Through Formal and Informal Routines: Best Practice and Lessons Learned]]> 36009 Join us for a safe and open conversation with Betsey Stevenson about how she amplifies her advocacy for diversity in economics through formal and informal routines, her best practices, lessons learned, and her experience of what worked, and what didn’t in and outside of classrooms. Stevenson is a professor at the University of Michigan in public policy and economics, contributes as a faculty research associate at the National Bureau of Economic Research, and serves on the executive committee of the American Economic Association. Her research centers on women's labor market experiences, modern family dynamics, and the relationship between labor market and family dynamics. Stevenson is a passionate advocate for diversity in economics and promotes this cause through various platforms and news outlets.

]]> cwhittle9 1 1698677383 2023-10-30 14:49:43 1699895220 2023-11-13 17:07:00 0 0 event Join us for an insightful conversation with Betsey Stevenson as she shares her experience in fostering a sense of belonging and promoting diversity in economics inside and outside the classroom.

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2023-11-16T11:00:00-05:00 2023-11-16T12:00:00-05:00 2023-11-16T12:00:00-05:00 2023-11-16 16:00:00 2023-11-16 17:00:00 2023-11-16 17:00:00 2023-11-16T11:00:00-05:00 2023-11-16T12:00:00-05:00 America/New_York America/New_York datetime 2023-11-16 11:00:00 2023-11-16 12:00:00 America/New_York America/New_York datetime <![CDATA[]]> Aselia Urmanbetova
aselia@gatech.edu

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<![CDATA[Join Online]]>
<![CDATA[School of CSE Seminar Series: Ryan F. Johnson]]> 36319 Speaker: Research Engineer Ryan F. Johnson, U.S. Naval Research Laboratory
Date and Time: November 17, 2:00-3:00 p.m.
Location: Coda 114
Host: School of CSE Assistant Professor Spencer Bryngelson

Title: Towards Simulations of Complex Physics in High-speed Propulsion Devices Using High-Order Methods

Abstract: High-speed combustion devices involve intricate and interrelated physical phenomena that present significant challenges for system design analyses. These systems center around compressible turbulent airflows, often at supersonic velocities, interacting with fuel at time scales comparable to the chemical reactions driving combustion. In practical systems, various factors, including heat transfer to the combustor walls and the fuel source's thermochemistry, can markedly influence this process, leading to operational envelopes highly sensitive to system design. These complexities are challenging to replicate and study experimentally, underscoring the importance of numerical simulations in comprehending high-speed combustion environments. However, employing these tools for design purposes remains problematic. First-principles simulations can be cost-prohibitive, while designing and calibrating reduced-order models can be intricate. Moreover, the required level of fidelity to model such intricate flows can vary from case to case, often not known until the investigation begins. Consequently, there is an ongoing imperative to gain a profound understanding of the fundamental physics in these complex combustion settings.

This presentation will spotlight the continuous efforts of the Naval Research Laboratory to advance numerical simulation methods for a more comprehensive grasp of the intricate physics within high-speed combustion devices. Particular emphasis will be placed on the utilization of the discontinuous Galerkin methodology in conjunction with realistic physical models for combustion processes. The discussion will also offer a brief historical perspective to provide context regarding the current state of the art, identify existing scientific challenges, and outline future research opportunities.

Bio: Dr. Ryan Johnson's joined NRL in 2015 as Karles' Fellow, dedicating himself to advancing the JENRE® Multiphysics Framework by embedding intricate combustion models. His responsibilities included overseeing the integration of gas-phase reactions with finite rate kinetics for modeling efforts involving solid, liquid, and gaseous fuels. Dr. Johnson's current focus centers on the practical application and validation of the JENRE® Multiphysics Framework in Navy-relevant combustors, including diverse applications such as solid fueled ramjets, scramjets, and rotating detonation engines. Before his tenure at NRL, Dr. Johnson earned his PhD at the University of Virginia under the guidance of Professor Harsha Chelliah. His doctoral research explored the coupling of computational fluid dynamics (CFD) with theoretical chemically reacting flow, covering a broad spectrum from carbon surface reactions to hypersonics. His academic journey was supported by several fellowships, including the National Defense Science and Engineering Graduate (NDSEG) Fellowship, the Farrah Fellowship, and the Paul Voight Teaching Fellowship.

Dr. Johnson is interested and devoted to introducing high-fidelity models and innovative numerical techniques as alternatives to conventional methods for simulating chemically reacting flows. His dedication to advancing the field has been acknowledged with two prestigious NRL ARPAD research publication awards.

]]> Bryant Wine 1 1695923518 2023-09-28 17:51:58 1699893958 2023-11-13 16:45:58 0 0 event Speaker: Research Engineer Ryan F. Johnson, U.S. Naval Research Laboratory
Date and Time: November 17, 2:00-3:00 p.m.
Location: Coda 114
Host: School of CSE Assistant Professor Spencer Bryngelson

Title: Towards Simulations of Complex Physics in High-speed Propulsion Devices Using High-Order Methods

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2023-11-17T14:00:00-05:00 2023-11-17T15:00:00-05:00 2023-11-17T15:00:00-05:00 2023-11-17 19:00:00 2023-11-17 20:00:00 2023-11-17 20:00:00 2023-11-17T14:00:00-05:00 2023-11-17T15:00:00-05:00 America/New_York America/New_York datetime 2023-11-17 02:00:00 2023-11-17 03:00:00 America/New_York America/New_York datetime <![CDATA[]]> Host: Spencer Bryngelson (shb@gatech.edu)

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671885 671885 image <![CDATA[Ryan Johnson.jpeg]]> image/jpeg 1695923524 2023-09-28 17:52:04 1695923524 2023-09-28 17:52:04
<![CDATA[School of CSE Seminar Series: Eva Dyer]]> 36319 Speaker: Associate Professor Eva Dyer, Wallace H. Coulter Department of Biomedical Engineering
Date and Time: November 14, 12:00-1:00 p.m.
Location: Coda, Room 230
Host: School of CSE Assistant Professor Spencer Bryngelson

Title: Toward Multi-Modal, Multi-Source Foundation Models to Advance Large-Scale Neural Data Analysis

Abstract: Despite the rapid growth of datasets in neuroscience, models of brain function often struggle to harness this expansive scale due to variability across experiments and shifts in our measurements of the brain's state. In this talk, I will outline our efforts to consolidate diverse datasets from various brain regions and experimental conditions into a cohesive "neurofoundation" model. By leveraging extensive pretraining on this neural data, we aim to enable robust generalization across different modalities and species. Further, I will delve into how this foundational model promises to improve data efficiency, expand the capabilities of brain-machine interfaces and neural decoders, and provide advanced, user-friendly tools to the wider neuroscience community, setting the trajectory for a more integrated approach to neural data analysis.

Bio: Eva Dyer (she/they) is an Associate Professor in the Coulter Department of Biomedical Engineering at the Georgia Institute of Technology. Dr. Dyer’s research combines artificial intelligence (AI) and neuroscience to understand brain function (AI for Neuro) and to build abstractions of biological organization and function that can be used to create more flexible AI systems (Neuro for AI). Eva completed all of her degrees in Electrical & Computer Engineering, obtaining her Ph.D. and M.S. from Rice University and a B.S. from the University of Miami. Eva is the recipient of a number of awards, including a Sloan Fellowship in Neuroscience, NSF CAREER Award, Next Generation Leader Award from the Allen Institute, a McKnight Foundation Technological Innovations in Neuroscience Award, and a CIFAR Azrieli Global Scholar Award.

]]> Bryant Wine 1 1695995664 2023-09-29 13:54:24 1699893906 2023-11-13 16:45:06 0 0 event Speaker: Associate Professor Eva Dyer, Wallace H. Coulter Department of Biomedical Engineering
Date and Time: November 14, 12:00-1:00 p.m.
Location: Coda, Room 230
Host: School of CSE Assistant Professor Spencer Bryngelson

Title: Toward Multi-Modal, Multi-Source Foundation Models to Advance Large-Scale Neural Data Analysis

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2023-11-14T12:00:00-05:00 2023-11-14T13:00:00-05:00 2023-11-14T13:00:00-05:00 2023-11-14 17:00:00 2023-11-14 18:00:00 2023-11-14 18:00:00 2023-11-14T12:00:00-05:00 2023-11-14T13:00:00-05:00 America/New_York America/New_York datetime 2023-11-14 12:00:00 2023-11-14 01:00:00 America/New_York America/New_York datetime <![CDATA[]]> Host: Spencer Bryngelson (shb@gatech.edu)

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598576 598576 image <![CDATA[Eva Dyer]]> image/jpeg 1510232966 2017-11-09 13:09:26 1510232966 2017-11-09 13:09:26
<![CDATA[MS Defense by Abhishek Shankar]]> 27707 THE SCHOOL OF INDUSTRIAL DESIGN 

GEORGIA INSTITUTE OF TECHNOLOGY 

Under the provisions of the regulations for the degree 

 

MASTER OF INDUSTRIAL DESIGN

on

Tuesday, November 28, 2023

11:00 a.m. – 12:30 p.m. EST

    West Architecture -Room 155

                                                                                          

Abhishek Shankar

will present a thesis defense entitled,

"UX GUIDE TO MICROINTERACTIONS : ESTABLISHING A CLASSFICATION SYSTEM TO ENABLE MICROINTERACTION DESIGN LITERACY AMONG NOVICE UX DESIGNERS"

Advisor:

Kevin Shankwiler, Georgia Tech School of Industrial Design

Committee:

Courtney Gavin, Georgia Tech School of Industrial Design

Jess Drake, GE Appliances 

 

Faculty and students are invited to attend this presentation. 

Abstract

            

In this thesis project, the focus is on the importance of microinteractions in enhancing the user experience (UX) and user interface (UI) design. The study explores how identifying and classifying various animated microinteractions can help improve design literacy among UX/UI designers by integrating motion design elements. Microinteractions are small, task-specific actions that a user can trigger or experience within a user interface, such as liking a post, setting a status, or receiving a notification. They play a crucial role in providing feedback, guiding users, and adding an element of delight to the user experience. To better understand how designers work with motion in product design, subject matter experts (SMEs) were interviewed who revealed that non-motion designers often need help understanding microinteraction design language. To address this, a classification system was developed and hosted online, which permits UX/UI designers to access microinteraction design language. Microinteractions are classified into a visual design system based on triggers, functions, and principles of motion. This classification system was validated by UX/UI designers using interviews and questionnaires. The results showed that the system promotes cross-disciplinary communication and collaboration among design team members by introducing motion design language and terminologies through an organized classification system.


 

 

]]> Tatianna Richardson 1 1699891745 2023-11-13 16:09:05 1699891745 2023-11-13 16:09:05 0 0 event "UX GUIDE TO MICROINTERACTIONS : ESTABLISHING A CLASSFICATION SYSTEM TO ENABLE MICROINTERACTION DESIGN LITERACY AMONG NOVICE UX DESIGNERS

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<![CDATA[PhD Proposal by Noel Dudeck]]> 27707  

School of Physics Thesis Proposal

 

Presenter:        Noel Dudeck

Title:                  Towards Epigraphene Edge State Optoelectronics
Date:                  Thursday, November 16, 2023

Time:                 12:00 p.m.    

Place:                 Howey N110

 

Committee:     Dr. Walt de Heer, School of Physics, Georgia Institute of Technology (Advisor)

Dr. Claire Berger, School of Physics, Georgia Institute of Technology (Advisor)

Dr. Dr. David Citrin, School of Electrical and Computer Engineering, Georgia Institute of Technology

Dr. John Hankinson, Georgia Tech Research Institute

Dr. Zhigang Jiang, School of Physics, Georgia Institute of Technology

]]> Tatianna Richardson 1 1699888617 2023-11-13 15:16:57 1699888617 2023-11-13 15:16:57 0 0 event  Towards Epigraphene Edge State Optoelectronics

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<![CDATA[Genocides and Memories: Russia’s War Against Ukraine in Comparative Perspective]]> 36009 The war in Ukraine is the most serious armed conflict in Europe since the Yugoslav wars of the 1990s. The groundwork for this war was laid by memory wars between Russia and its former satellites in the 2000s and 2010s. These memory wars were mainly focused on the legacy of WWII and crimes against humanity committed by the fascist, communist, and nationalist regimes and movements. Thus, the language of the Russian anti-Ukraine propaganda is based entirely on the Soviet myth of WWII, according to which all anti-Russian forces are Nazi allies.

The dynamics of violence in the region seem to follow a vicious circle: genocides – memory wars – new genocides. Indeed, according to many observers, Russian atrocities on Ukraine’s occupied territories seem to fall under the concept of genocide as defined in the 1948 UN Convention. Similar dynamics were also characteristic of the Yugoslav wars.  

The return of violence, largely stimulated by populist history politics, came as a surprise to many observers, convinced as they were in the 1980s and even 1990s that the rise of memory, including the memories of past tragedies, promised peace and mutual understanding between different racial, national, ethnic, and religious communities rather than the renewal of hostilities. This is, however, not what we see today. Memory wars are currently raging from East Asia and Australia through Europe and the Near East to the Americas. The war in Ukraine has shown that a memory war can trigger a shooting war. This conference will focus on the ways in which populist movements and neo-authoritarian regimes weaponize the historical past as a major instrument of their propaganda, as well as on the long-term evolution of modern culture and historical consciousness, which has made possible such manipulations through collective memory.

Co-hosted by Georgia Tech School of Modern Languages and School of History and Sociology; Emory University Department of Russian and East Asian Languages and Cultures; Emory University Center for Human Rights and Democracy and the Department of Political Science; Georgia State University Department of Political Science, Criminology, and International Studies; and Georgia Gwinnett College.

Conference Schedule

Monday, Nov. 13

Panel 1, 12:30 – 1:45 p.m., hosted by Georgia Tech, online

https://gatech.zoom.us/j/94957099028

Panelists:

Moderator: Nikolay Koposov (Georgia Tech)

Tuesday, Nov. 14

Panel 2, 11 a.m. – 12:15 p.m., hosted by Georgia Gwinnett College, hybrid

1000 University Center Lane, Lawrenceville, GA 30043, B-1600, https://ggc-edu.zoom.us/j/89730558695

Panelists:

Moderator: Laura Young (Georgia Gwinnett College, Department of Political Science, Criminology, and International Studies, Associate Professor and Chair)

Panel 3, 3:30 – 4:45 p.m., hosted by Georgia State University, online

https://us02web.zoom.us/j/87035394026?pwd=NnZ3OFl4alYyN2VrTDMzZytsK21XUT09

Panelists:

Moderator: Ryan E. Carlin (Georgia State University, Center for Human Rights and Democracy, Director)

Panel 4, 5 – 6:15 p.m., hosted by Emory University, online

https://emory.zoom.us/j/98075246052

Panelists:

Moderator: Juliette Stapanian Apkarian (Emory University, Department of Russian and East Asian Languages and Cultures, Associate Professor and Chair)

Wednesday, Nov. 15

Keynote Event, 11 a.m. – 12:15 p.m., hosted by Georgia Tech, hybrid

Georgia Tech Library, Scholars Event Network, Room 1280, 686-704 Cherry St NW, Atlanta, GA 30332, https://gatech.zoom.us/j/92978357920

Welcoming remarks: Richard Utz (Georgia Tech, Ivan Allen College of Liberal Arts, Senior Associate Dean and Professor, School of Literature, Media, and Communication)

Keynote speaker: Anne Applebaum (The Atlantic and the Johns Hopkins University, Agora Institute)

Moderator: Dina Khapaeva (Georgia Tech)

Book presentations followed by a reception, 12:30 – 1:45 p.m., hosted by Georgia Tech, hybrid

Georgia Tech Library, Scholars Event Network, Room 1280, 686-704 Cherry St NW, Atlanta, GA 30332, https://gatech.zoom.us/j/92369945947

Moderator: John Lyon (Georgia Tech, School Chair, Charles Smithgall Jr. Institute Chair, and Professor, School of Modern Languages)      

Keynote Lecture, 2 p.m. - 3:15 p.m., hosted by Georgia Tech, hybrid

Georgia Tech Library, Scholars Event Network, Room 1280, 686-704 Cherry St NW, Atlanta, GA 30332, https://gatech.zoom.us/j/97378611490

Keynote speaker: Elazar Barkan (Columbia University) - The Guilt of Nations: Twenty-Five Years After

Moderator: Nikolay Koposov (Georgia Tech)

Panel 5, 3:30 – 4:45, hosted by Georgia Tech, hybrid

Georgia Tech Library, Scholars Event Network, Room 1280, 686-704 Cherry St NW, Atlanta, GA 30332, https://gatech.zoom.us/j/98520358199

Panelists:

Moderator: Victoria E. Thompson (Georgia Tech, School of History and Sociology, Professor and Chair)

]]> cwhittle9 1 1699284278 2023-11-06 15:24:38 1699888453 2023-11-13 15:14:13 0 0 event This conference will focus on the ways in which populist movements and neo-authoritarian regimes weaponize the historical past as a major instrument of their propaganda, as well as on the long-term evolution of modern culture and historical consciousness, which has made possible such manipulations through collective memory.

]]>
2023-11-13T12:30:00-05:00 2023-11-15T16:45:00-05:00 2023-11-15T16:45:00-05:00 2023-11-13 17:30:00 2023-11-15 21:45:00 2023-11-15 21:45:00 2023-11-13T12:30:00-05:00 2023-11-15T16:45:00-05:00 America/New_York America/New_York datetime 2023-11-13 12:30:00 2023-11-15 04:45:00 America/New_York America/New_York datetime <![CDATA[]]> Amanda Weiss
amanda.weiss@modlangs.gatech.edu

]]>
672267 672267 image <![CDATA[Genocides IG.png]]> image/png 1699284288 2023-11-06 15:24:48 1699284288 2023-11-06 15:24:48 <![CDATA[Join Keynote Event Online]]> <![CDATA[Conference Program]]>
<![CDATA[PhD Defense by Yen-Cheng Liu]]> 27707 Title: Efficient Visual Learning for Scene Understanding

 

Date: Tuesday, November 21, 2023

Time: 12:00 - 1:30 pm EST / 9:00 - 10:30 am PST

Location: https://gatech.zoom.us/j/7745230525

 

Yen-Cheng Liu

Machine Learning PhD Candidate

School of Electrical and Computer Engineering

Georgia Institute of Technology

 

Committee

  1. Dr. Zsolt Kira (Advisor), School of Interactive Computing, Georgia Tech
  2. Dr. Judy Hoffman, School of Interactive Computing, Georgia Tech
  3. Dr. Larry Heck, School of Electrical and Computer Engineering and the School of Interactive Computing, Georgia Tech
  4. Dr. Mark Davenport, School of Electrical and Computer Engineering, Georgia Tech
  5. Dr. Diyi Yang, Computer Science Department, Stanford University

 

Abstract

Significant advancements in scene understanding have been driven by deep neural networks. These learning-based frameworks enhance performance through extensive training datasets and a large number of trainable parameters. However, they are less scalable and require substantial computational and financial resources. This dissertation investigates two aspects of efficient visual learning for scene understanding: label-efficient learning and parameter-efficient learning. To reduce label supervision in instance-level scene understanding tasks, we develop a series of semi-supervised learning frameworks. These frameworks improve the label efficiency under various detector architectures and unconstrained data settings. To reduce parameter usage in multi-task training, we re-evaluate parameter-efficient methods from NLP for scene understanding and then propose a more parameter-efficient method for vision architectures. These advancements demonstrate the practicality and adaptability of efficient learning frameworks in diverse, resource-constrained environments.

]]> Tatianna Richardson 1 1699887899 2023-11-13 15:04:59 1699887899 2023-11-13 15:04:59 0 0 event  Efficient Visual Learning for Scene Understanding

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<![CDATA[PhD Proposal by Jiaao Chen ]]> 27707 Title: Efficient and Adaptive Machine Learning for Natural Language Processing

Date/Time: Nov 20, 2023, 12:00 PM to 2:00 PM Eastern Time (US)

Location: Zoom Link

Meeting ID: 915 0053 1039

Passcode: 077482

 

Jiaao Chen 

Ph.D. Candidate in Computer Science

School of Interactive Computing

Georgia Institute of Technology

 

Committee:

Dr. Diyi Yang (advisor), Computer Science Department, Stanford University

Dr. Mark Riedl (co-advisor), School of Interactive Computing, Georgia Tech

Dr. Alan Ritter, School of Interactive Computing, Georgia Tech

Dr. Zsolt Kira, School of Interactive Computing, Georgia Tech

Dr. Colin Raffle, Department of Computer Science, University of Toronto

 

 

Abstract:

In this thesis, we advocate for efficient and adaptive machine learning for NLP, endeavoring to make NLP models benefit real-world applications. While current NLP has recently undergone a transformational shift towards the development and application of Large Language Models (LLMs), which represent a significant leap in performance, the extensive computational resources and vast textual datasets they rely on create key challenges in environments with limited resources such as limited data, computational power, memory, and specialized expertise. We argue that developing machine learning methods that could efficiently adapt with limited resources is particularly vital in the era of LLMs to make the benefits of the technology sustainable, accessible, and generalizable.

 

We explore this perspective by diving into three components of the learning process of NLP models: (a) improving data efficiency via data augmentation and semi-supervised learning, through which we could greatly alleviate the dependence on the need of labeled data to adapt NLP models to data-limited scenarios; (b) incorporating structures when learning NLP models, through which we could explicitly utilize rich hidden structures beyond just text to enhance the learning efficiency, making the NLP models more generalizable to novel settings; (c) improving training efficiency via parameter-efficient fine-tuning and continual learning, through which we can adapt large language models efficiently to emerging data and tasks with limited computation and memory requirements. Building on these three dimensions, we further propose the efficient and adaptive framework that could efficiently adapt LLMs to novel settings with minimal human efforts. Throughout this thesis, the ultimate goal is to democratize NLP functionalities, making them more accessible and adaptable for languages with scarce resources, specialized fields with unique needs, and nascent applications that conventional NLP methodologies fail to accommodate.

 

]]> Tatianna Richardson 1 1699887585 2023-11-13 14:59:45 1699887585 2023-11-13 14:59:45 0 0 event Efficient and Adaptive Machine Learning for Natural Language Processing

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<![CDATA[GT Jazz Ensemble II & Concert Band]]> 36511 A special night with music performed by the GT Jazz Ensemble II and Concert Band. 

 

Admission is free and open to the public.

___________________________________

View the concert program.

Watch the live stream on the School of Music's YouTube channel.

Visit the School of Music's website to view the schedule of concerts for this semester. 

Follow the School of Music on Facebook and Instagram to keep up with our news and events.

]]> tma98 1 1697850999 2023-10-21 01:16:39 1699885777 2023-11-13 14:29:37 0 0 event A special night with music performed by the GT Jazz Ensemble II and Concert Band. 

 

Admission is free and open to the public.

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<![CDATA[Georgia CTSA Informatics Lunch and Learn]]> 35486 Audio Diaries - Product development story of a platform to conduct daily diary research.

Santiago Arconada Alvarez
Co-Director of Apps & Digital Platforms 
 

Santiago co-directs an NIH-funded web and mobile app design and development group focused on developing digital health tools to support clinical translational research and health equity projects. He has developed over seven publicly available software programs and co-authored five peer-reviewed papers including one clinical trial on digital tools for patient and provider education. Santiago was the recipient of the Emory School of Medicine Staff Spotlight on 2023 and has won several software development product competitions. In addition to his academic work, Santiago is passionate about bridging the gap between industry-level design and academic research. He runs a summer internship program for design students and exposes them to challenges in the healthcare space. 

]]> Christina Wessels 1 1697209817 2023-10-13 15:10:17 1699878940 2023-11-13 12:35:40 0 0 event Providing free informatics guidance to the university research community.

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2023-11-29T12:00:00-05:00 2023-11-29T13:00:00-05:00 2023-11-29T13:00:00-05:00 2023-11-29 17:00:00 2023-11-29 18:00:00 2023-11-29 18:00:00 2023-11-29T12:00:00-05:00 2023-11-29T13:00:00-05:00 America/New_York America/New_York datetime 2023-11-29 12:00:00 2023-11-29 01:00:00 America/New_York America/New_York datetime <![CDATA[Register Here]]>
<![CDATA[BGSA Cultural Bake Off]]> 27469

Don't miss out on our upcoming BGSA Bake-Off happening Tuesday, November 14th, from 5-7pm in the Northside room of the Student Center! Get ready to taste delicious treats from our talented vendors and cast your vote for the best one. The winner will receive a fantastic prize!

For those interested in participating as an attendee or vendor, please fill out the form linked here: https://forms.office.com/pages/responsepage.aspx?id=u5ghSHuuJUuLem1_Mvqgg3nTr3lK1v9Bh3Pi-3WvuthUNDZSS0w3UEUxRFpITjk2WjdKOEk1UVoxTC4u.

The event is free for dues-paid BGSA members and $5 for everyone else. We look forward to a sweet and exciting event!

 

]]> Kristen Bailey 1 1699845996 2023-11-13 03:26:36 1699846075 2023-11-13 03:27:55 0 0 event Get ready to taste delicious treats from our talented vendors and cast your vote for the best one. The winner will receive a fantastic prize!

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2023-11-13T17:00:00-05:00 2023-11-13T19:00:00-05:00 2023-11-13T19:00:00-05:00 2023-11-13 22:00:00 2023-11-14 00:00:00 2023-11-14 00:00:00 2023-11-13T17:00:00-05:00 2023-11-13T19:00:00-05:00 America/New_York America/New_York datetime 2023-11-13 05:00:00 2023-11-13 07:00:00 America/New_York America/New_York datetime <![CDATA[]]> Christian Douglas

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<![CDATA[Accessible Prosthetics Initiative November GBM]]> 27469 Come join API as we discuss and look at media representation of amputees and prosthetics!

]]> Kristen Bailey 1 1699845798 2023-11-13 03:23:18 1699845903 2023-11-13 03:25:03 0 0 event Come join API as we discuss and look at media representation of amputees and prosthetics!

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2023-11-28T18:30:00-05:00 2023-11-28T20:00:00-05:00 2023-11-28T20:00:00-05:00 2023-11-28 23:30:00 2023-11-29 01:00:00 2023-11-29 01:00:00 2023-11-28T18:30:00-05:00 2023-11-28T20:00:00-05:00 America/New_York America/New_York datetime 2023-11-28 06:30:00 2023-11-28 08:00:00 America/New_York America/New_York datetime <![CDATA[]]> Sophia Tran

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<![CDATA[API on Engage]]>
<![CDATA[Taste of Africa 2023 : United in Spirit ]]> 27469 Taste of Africa is a Georgia Tech tradition that showcases the beauty and culture of the continent through dance, fashion, and drama.

We are thrilled to announce the upcoming spectacle that promises to be an unforgettable cultural journey, the annual showcase hosted by the African Student Association: Taste of Africa 2023. On November 17th, 2023, from 4 pm to 10 pm, we invite you to embark on an exploration of Africa's vibrant tapestry, a continent often misunderstood and overlooked in its true diversity.

In keeping with our mission to shatter stereotypes and showcase the myriad cultures that call Africa home, this year's theme is nothing short of profound: "United in Spirit." Beyond a mere celebration, Taste of Africa 2023 aspires to affirm the identities of black people and the African Diaspora, highlighting how their literature, art, and creativity have indelibly shaped global culture. Food service will begin at 4:00pm and the show will start at 6:30pm. Tickets are required for this event, and are available for purchase using the link below.

Purchase Tickets

]]> Kristen Bailey 1 1699845537 2023-11-13 03:18:57 1699845646 2023-11-13 03:20:46 0 0 event Taste of Africa is a Georgia Tech tradition that showcases the beauty and culture of the continent through dance, fashion, and drama.

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2023-11-17T16:00:00-05:00 2023-11-17T22:00:00-05:00 2023-11-17T22:00:00-05:00 2023-11-17 21:00:00 2023-11-18 03:00:00 2023-11-18 03:00:00 2023-11-17T16:00:00-05:00 2023-11-17T22:00:00-05:00 America/New_York America/New_York datetime 2023-11-17 04:00:00 2023-11-17 10:00:00 America/New_York America/New_York datetime <![CDATA[]]> Ogechukwu Onyeachonam

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<![CDATA[Purchase Tickets]]>
<![CDATA[PhD Proposal by Yang Chen ]]> 27707 Title: Benchmarking Multilingual and Multimodal Intelligent Systems

Date/Time: Nov 17, 2023, 3:00 PM to 5:00 PM Eastern Time (US)

Location: Zoom Link

Meeting ID: 987 6029 3352

Passcode: 443653

 

Yang Chen (Homepage)

Ph.D. Candidate in Computer Science

School of Interactive Computing

Georgia Institute of Technology

 

Committee:

Dr. Alan Ritter (advisor), School of Interactive Computing, Georgia Tech

Dr. Wei Xu (co-advisor), School of Interactive Computing, Georgia Tech

Dr. Kartik Goyal, School of Interactive Computing, Georgia Tech

Dr. Hexiang (Frank) Hu, Google Deepmind

Dr. Ming-Wei Chang, Google Deepmind

 

Abstract:

Language serves as the cornerstone and medium to transfer human intellect across communities worldwide. Recent developments of large language models that consume vast amounts of human knowledge from large-scale online text corpora have revolutionized the field of natural language processing (NLP) and serve as the building blocks to build intelligent systems that benefit humanity.

However, two primary challenges are present: 1) the significant resource imbalance among languages, influenced by the disparities in the wealth of resources across different countries, cultures, and geographic regions, diminishes the efficacy of language models in understanding and serving speakers of low-resource languages; 2) the language-only modality may limit the model to acquire knowledge and how it could broaden the domain of applications to help human with visual inefficiency or facility people to interact with the visual environment.

 

This thesis proposal aims to benchmark the two challenges in the pursuit of building reliable multilingual and multimodal intelligent systems that benefit humanity.

In the first part of the presentation, I present methods that I developed to improve language model understanding on low-resource languages, including a synthetic data generation model and a novel algorithm that translates and fusion annotations from high-resource languages. In the second part of the presentation, I introduce the InfoSeek benchmark (1M+), which assesses the capabilities of vision-language models to answer visual information-seeking questions about entities present in an image. By benchmarking multimodal large language models and retrieval-augmented generation models on InfoSeek, we show insights that benefit the future development of multimodal intelligent systems.

 

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