How can students make the best use of their German language and intercultural communication skills? You can learn more about opportunities in the German program and hear from alumni and peers about study abroad programs and internships.

Join us to celebrate Atlanta’s thriving arts ecosystem — for venue details, ticketing, and full schedule information, visit theatlantaartfair.com/visit.

The event will include an artist’s talk, a film screening, and audience Q&A. Open to the campus community and general public. 

Paid or permitted parking is available at the Student Center Parking Deck, Visitor Area 3 / W02. RSVP by Oct. 5.

Abstract: Modern manufacturing generates increasingly rich in-situ sensing data, creating new opportunities for AI to enable automated and intelligent quality control decisions. However, conventional quality control using supervised learning relies on abundant labeled data and assumes that future product defects or process faults resemble those known during training. In practice, new defect types emerge, while abnormal conditions may be rarely observed or completely unknown. These challenges are particularly important for in-situ quality control, where defects must be detected or correctly classified for real-time decision-making, including newly emerging defects with limited or unavailable labels. Moreover, for latent defects that cannot be directly inspected online, defects must instead be predicted from indirect process-sensing signals. This requires mapping process-signal changes to possible defects despite scarce or unavailable defect training samples. This talk explores how advances in AI can address these challenges and enable more adaptive and intelligent in-situ quality control and decision-making for smart manufacturing.
 

Bio: Dr. Judy Jin is the A. Galip Ulsoy Collegiate Professor of Engineering and Professor of Industrial and Operations Engineering at the University of Michigan. Her research lies at the intersection of data science and quality engineering, with a focus on synergistically integrating engineering models, AI, and advanced quality control methods to improve system design and operational performance. She has served as PI/Co-PI on more than $20 million in federally and industry-funded research. Her work has received numerous honors, including 18 Best Paper Awards, the S.M. Wu Research Implementation Award from SME, the Forging Achievement Award from FIERF, the NSF CAREER Award, and the NSF PECASE Award.

Dr. Jin currently serves as Editor-in-Chief of IISE Transactions. She has also served as Vice President of INFORMS, Chair of the INFORMS Quality, Statistics and Reliability Section, and President of the IISE Quality Control and Reliability Engineering Division. She is a Fellow of ASME, IISE, and INFORMS.

Date: Sept 29th, 2026

Time: 2 pm EST

Location: Klaus 1212

Virtual Meeting: https://gatech.zoom.us/j/6342692876?omn=93309114089 

Nina Moorman

School of Interactive Computing

College of Computing

Georgia Institute of Technology

ninamoorman.com

Committee

Dr. Matthew Gombolay - Advisor, School of Interactive Computing

Dr. Sonia Chernova - School of Interactive Computing

Dr. Agata Rozga - School of Interactive Computing

Dr. Mykel Kochenderfer - Stanford University, Department of Aeronautics and Astronautics

Dr. Nakul Gopalan - Arizona State University, School of Computing and Augmented Intelligence

Abstract

To successfully deploy assistive in-home robots in human populated environments, robots will need to be able to perform supplemental on-site learning to adapt to aging users and changing environments. It is intractable for a roboticist to be contracted each time the robot policy needs to be updated. Instead, the robot should be able to learn from the end user directly. The field of learning from demonstration (LfD) enables non-roboticist end users to teach a robot novel skills via demonstrations of the desired behavior, without necessitating programming knowledge. While LfD aims to democratize robot learning, barriers still exist. Novice users require and request guidance to be able to successfully teach a robot via LfD. This is particularly the case when determining how to improve upon a demonstration set whose resulting learned behavior is not as desired or expected. In my thesis, I aim to increase the accessibility of LfD for novice users by developing LfD systems that provide novel forms of guidance to the demonstrator.

Advisors:    Dr. Lakshmi Prasad Dasi, PhD (Georgia Institute of Technology)
          Dr. Scott Hollister, PhD (Georgia Institute of Technology)

Committee: Dr. Rudolph Gleason
          Dr. Holly Bauser-Heaton, MD, PhD (UT Health Houston)
Dr. Susan James, PhD (Colorado State University)
Dr. Vinod Thourani, MD (Piedmont Healthcare)

Investigation of a Novel Transcatheter Bio-Inspired Polymeric Valve for Hemodynamic Performance and Durability
Transcatheter aortic valve replacement (TAVR) has transformed the treatment of aortic valve disease, but its expansion into younger patient populations places increasing demands on valve durability and lifetime performance. Polymeric transcatheter heart valves (THVs) offer an alternative to conventional bioprosthetic valves, but their successful translation introduces interconnected challenges in leaflet manufacturing, transcatheter delivery, hemodynamic performance, and durability. This dissertation presents the development and evaluation of a balloon-expandable polymeric THV incorporating a bio-inspired hyaluronan enhanced linear low-density polyethylene (LLDPE-HA) material platform designed to combine the mechanical properties of the polymer with the biological functionality of hyaluronan. First, vacuum thermoforming is established as a reproducible manufacturing approach for producing three-dimensional polymeric leaflets with consistent hemodynamic performance and favorable flow characteristics. Next, iterative valve design and durability studies evaluate leaflet material, attachment, and skirt and commissural design features while maintaining valve hemodynamic performance. Finally, leaflet crimping studies and finite element simulations characterize damage and mechanical deformation introduced during transcatheter crimping, balloon expansion, and patient-specific deployment. Collectively, these studies address key engineering challenges in translating a bio-inspired LLDPE-HA leaflet material into a functional THV system. By integrating investigations of leaflet manufacturing, material and valve design, hemodynamic performance, durability, and transcatheter deployment, this work provides an engineering framework for the continued development of polymeric THVs with favorable functional performance, improved durability and reproducible manufacturing.

Student Name: Anomitra De

Thesis Title: Processing–Structure–Function Relationships for High-Performance Porous Carbon Materials from Kraft Lignin

Thesis Advisor: Sankar Nair

Thesis Co-Advisor: Meisha Shofner

Committee Members: Nian Liu (CHBE), AJ Medford (CHBE), Matthew T McDowell (Department of Mechanical Engineering)

Date: 10/1/2026

Time: 10 AM

Location: Ford ES&T L1120

will defend a doctoral thesis entitled,

Assembling and Understanding Precursor-Polymer Couples for Vapor Phase Infiltration 

On

Tuesday, September 29 at 11:00 a.m.
J. Erskine Love Room 295

and

Virtually via Teams at https://teams.microsoft.com/meet/212996889118737?p=kSrPGsUv0UlCQZfuw

Committee

Prof. Mark Losego – School of Materials Science and Engineering (advisor)

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

Prof. Antonio Facchetti – School of Materials Science and Engineering

Prof. Shucong Li – School of Materials Science and Engineering

Prof. Ryan Lively – School of Chemical and Biomolecular Engineering

Abstract

Hybrid organic-inorganic materials present a new frontier of materials that show properties that are distinct from – and sometimes superior to – the properties of their individual components. These materials have far-reaching applications, from renewable energy to catalysis and electronics manufacturing. One process by which we can create these hybrid materials is through vapor phase infiltration (VPI) of polymers. In VPI, the inorganic exists as a vapor precursor that is diffused within the polymer bulk, embedding itself into the matrix and distributing itself evenly throughout the polymer. However, this process is still a fairly young process, and there is much to understand about this process.

With the rise of machine learning and computational methods to determine material properties and physical phenomena, it is possible to predict outcomes of any combination of precursor and polymer. However, to do so, experimental datasets are required to provide a foundation to build a predictive model. The first part of this work involves the creation of a survey that collects the empirical outcomes of the infiltration of 3 polymers into 12 polymers at 3 different temperatures, bringing a total of 108 precursor-polymer-temperature combinations. The degree of infiltration will be determined by SEM-EDX and XRF, creating a standardized semi-quantitative set of data to which future researchers in the VPI field can build upon and use as a reference guide.

Digging deeper into this survey, we then investigated the infiltration of diethylzinc, a zinc oxide precursor, into poly (methyl methacrylate) (PMMA). Prior studies have shown that DEZ does not form a hybrid material with PMMA, which was attributed to its weak binding to the polymer functional groups. With quartz crystalline microbalance (QCM) gravimetry, we have determined that this only occurs at elevated temperatures above PMMA’s glass transition temperature, and that below this temperature, the DEZ does not form a hybrid material with PMMA because it cannot dissolve into the polymer matrix.

Finally, the last part of this thesis explores a very unusual result discovered during the creation of the polymer survey. Though VPI is used to create hybrid materials from precursors and polymers, we observed that exposing polylactic acid (PLA) to diethylzinc results in the polymer disappearing, rather than forming a hybrid. The infiltration of trimethylaluminum (TMA) into PLA also shows a similar phenomenon, and we have proposed two competing chemical mechanisms to describe this process. The results of this experiment opens a new application space for VPI, beyond just hybrid formation and into selective etching and material replacement.

Free admission, tickets required.

RSVP on Engage: https://gatech.campuslabs.com/engage/event/12600101

The goal of Unidos is to increase awareness and appreciation of the diverse cultures represented within Hispanic and Latino communities. The program also seeks to create opportunities for students, faculty, staff, and alumni to build authentic relationships through shared learning and cultural exchange.  

RSVP on Engage: https://gatech.campuslabs.com/engage/event/12598101

Second, I introduce the TRIDENT model (Tides and Rivers Influencing the Dynamic Evolution of Nearshore Tsunamis), a modeling framework designed to simulate the coupling between tsunamis, tides, and river flows. The coupled model is designed for estuaries, tidal channels, and fjords, and it addresses key challenges when simulating these interactions.

Finally, I will present results from a study that links dispersive tsunami wave trains visible in satellite imagery to near-trench earthquake rupture. By analyzing tsunami dispersion in the near-source wave field, this approach provides a new observational footprint for constraining source processes that improves resolving power near the trench compared with traditional seismic, geodetic, and tsunami sensing technologies.

Collectively, these studies demonstrate complementary advances, from field deployment to coupled modeling for hazard prediction to remote-sensing-based discovery, that expand the toolkit for understanding and assessing tsunami hazards and risks.

*Refreshments: 12-12:30 PM, ES&T Atrium

Abstract: Many of today's most important applications rely on high-performance manipulation of matrices, tensors, and general arrays of data.  The neural networks at the heart of AI language models are a prime example.  The AI software stack relies on kernels (e.g., for matrix-matrix product) that are specifically designed to deliver throughput close to the hardware's theoretical peak.  However, writing kernels that can deliver maximum performance is extremely challenging.  In this talk, I will discuss some of the work we have done to simplify the task of authoring such kernels.  This includes new abstractions to allow for algebraic manipulation of array layouts and new programming models for more easily expressing the kernels themselves.

Bio: Michael Garland has been a researcher at NVIDIA since 2006.  He joined the company as one of the founding members of NVIDIA Research and is currently Senior Director of Programming Systems Research.  He leads a research group focused on developing technologies that will help programmers take advantage of modern high-performance machines.  Their work spans the software stack with a particular focus on parallel algorithms, programming languages, compilers and runtime systems, and low-level hardware/software interfaces.  He and his team have both published numerous academic articles and contributed to many software packages in broad use by CUDA developers.

Thesis Title: "Bimetallic Nanocrystals with New Structural Features for Electrocatalytic Applications"

Monday, September 28th, 2026 at 10:00 AM

Location: MoSE 3201A

Or Join via Teams: https://teams.microsoft.com/meet/262888176023697?p=nsvUZmZVfryvei33cW

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. Henry La Pierre - School of Chemistry and Biochemistry 

Prof. Miaofang Chi - Department of Mechanical Engineering and Materials Science at Duke University; Oak Ridge National Laboratory

Summary: This seminar examines why exponential quantum advantages for NP-hard discrete optimization remain elusive and explores potential explanations and workarounds through the Maximum Cut problem.

Abstract: Quantum computing offers hope for realizing exponential advantages over classical computing. Despite over two decades of work studying quantum approaches for discrete optimization, rigorously provable exponential advantages for approximating optimal solutions to NP-hard problems remain scarce. Why? We will discuss a potential explanation and workarounds, using the Maximum Cut problem as a running example.

Speaker Bio: Ojas Parekh is a theoretical computer scientist who enjoys applying mathematical techniques to practically motivated interdisciplinary problems. He has worked in a variety of fields including discrete optimization, combinatorics, combinatorial scientific computing, and most recently, quantum and neuromorphic computing. A recent passion is helping shape the emerging fields of quantum approximation algorithms and quantum discrete optimization. He co-directs the Quantum Algorithms and Applications Collaboratory (QuAAC) at Sandia National Laboratories and directs the Department of Energy Fundamental Algorithmic Research toward Quantum Utility project (far-qu.sandia.gov), a multi-institutional effort tasked with designing novel quantum algorithms to realize advantages over classical computation, especially for optimization, simulation, and machine learning. Ojas believes the universe loves us because pizza exists.

Abstract: Quantum computing promises to transform how we solve optimization problems—but currently available Noisy Intermediate Scale Quantum (NISQ era) devices alone cannot get us there. A promising path forward lies in hybrid approaches that combine the strengths of classical algorithms with the emerging capabilities of quantum hardware, opening the door to scalable and high-performance solutions. In this talk, I will present recent advances in quantum optimization that bring this vision to life. I will discuss how warm-starting the Quantum Approximate Optimization Algorithm (QAOA) with classical relaxations can dramatically improve performance, how hybrid pipelines leverage combinatorial structure to achieve stronger approximations and noise resilience, and how benchmark families—such as strongly regular graphs and low-degree graphs—help us probe the boundary of quantum advantage. These results connect classical approximation algorithms, convex optimization, and quantum circuit design. Looking ahead, I will outline a research vision for hybrid intelligence, where classical and quantum algorithms operate in synergy rather than competition—rethinking optimization for the next era of computing.

Bio: Swati Gupta is an Associate Professor and the Class of 1947 Career Development Professor at the MIT Sloan School of Management in the Operations Research and Statistics Group. Prior to this, she held a Fouts Family Early Career Professorship as an Assistant Professor at the Stewart School of Industrial & Systems Engineering at Georgia Tech from 2018-2023, where she served as the lead of Ethical AI in the NSF AI Institute on Advances in Optimization from 2021-2023. She received a Ph.D. in Operations Research from MIT in 2017, following a joint Masters and B.Tech in Computer Science from IIT Delhi. Her research bridges optimization, machine learning, and algorithmic fairness, to design algorithms that are both theoretically rigorous and socially impactful, with applications in healthcare, hiring, energy, quantum computing, and beyond. Her work has been recognized by the 2023 NSF CAREER Award, INFORMS Doing Good with OR 2022 (finalist), the JP Morgan Early Career Faculty Recognition in 2021, the NSF CISE Research Initiation Initiative Award in 2019, INFORMS Computing Society 2016 (special recognition), and the INFORMS Service Science Section 2016 (finalist).

Abstract: In this talk, we discuss possible paths toward demonstrating quantum advantage in optimization, focusing primarily on quantum approximate multi-objective optimization. Multi-objective optimization seeks to understand optimal trade-offs between competing objectives by identifying sets of solutions that balance these trade-offs, a task that can be challenging for classical methods. This makes it a natural candidate for exploring potential benefits of quantum computing. We present a quantum algorithm for approximating such trade-offs in combinatorial optimization problems and illustrate its performance using both experiments on IBM quantum hardware and classical simulations. We conclude by discussing complementary paths toward quantum advantage in optimization, highlighting the role of systematic benchmarking efforts such as the Quantum Optimization Benchmarking Library (QOBLIB).
 

Bio: Dr. Stefan Woerner is a Principal Research Scientist, Global Technical Lead for Quantum Optimization, and Manager of the Applied Quantum Science group of IBM Quantum at IBM Research Europe - Zurich. He holds a Master of Science in Applied Mathematics and a Doctor of Sciences in Operations Management from ETH Zurich and is renowned for his work in quantum optimization, quantum finance, and quantum machine learning.

Abstract: This talk surveys the quantum computing stack—from applications and algorithms to hardware controls—highlighting the complexity at each layer and the interdisciplinary skills required to build and operate quantum computers.
 

Bio: Amara Katabarwa earned his Ph.D. from the University of Georgia in 2019 and has since led industry and government-funded efforts in quantum software, benchmarking, error mitigation, and fault-tolerant algorithms, currently serving as a Senior Research Scientist for GTRI.

Abstract: The problem of discriminating among non-orthogonal quantum states arises throughout quantum information processing. For example, in quantum communications, a message is encoded as a quantum state and transmitted over a quantum channel to a receiver that decodes the message. In quantum sensing, a photon in a known state is emitted to gather information about the environment from its reflections. Underlying state discrimination are the design of the quantum measurement device used for measurement and the design of the hypotheses used to encode information or probe the environment. These are the core degrees of freedom in quantum information processing system design. This talk will present the design of three quantum detection tasks, including quantum state and channel discrimination over uncertain channels, sequential unambiguous quantum state and channel discrimination, and quickest quantum change-point detection. These designs make use of a range of classical non-convex optimization methods, including stochastic, bi-level, and multi-objective optimization.
 

Bio: Xiaodong Wang received his Ph.D. in Electrical Engineering from Princeton University. He is a Professor of Electrical Engineering at Columbia University. His research interests span wireless communications, signal processing, machine learning, and quantum information processing. He received the 1999 NSF CAREER Award, the 2001 IEEE Communications Society and Information Theory Society Joint Paper Award, and the 2011 IEEE Communications Society Award for Outstanding Paper on New Communication Topics. He has served as an Associate Editor for the IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Signal Processing, and IEEE Transactions on Information Theory.

Abstract: It is an exciting time for quantum science and technology research. While the promise of quantum computers continues to motivate billions of dollars of investment by the U.S. government and private sector, quantum sensors have already revolutionized aspects of our daily life. Established technologies like atomic clocks in space underlie GPS and nearly all communication systems that rely on precise time and frequency synchronization. Related technologies like magnetometers are opening up new research frontiers in biomagnetism. At the same time, there remains a cutting edge achieved in research labs but not yet fielded. In this talk, Robert will give a brief overview of quantum sensors and some of their applications. He will discuss the broad topic of magnetic imaging, and the numerous applications that fall within that category. Throughout the talk, he will highlight the interplay between sensor development and signal processing.

Artificial intelligence may feel digital and invisible, but the systems powering it have a very real physical footprint. Dive into the infrastructure behind AI — from data centers and energy consumption to environmental and societal impacts — and what the rapid growth of AI means for the future of our digital society.

Panelists

Wendy H. Wong, Professor, University of British Columbia – Okanagan Campus

Wendy H. Wong is Professor and Principal’s Research Chair at the University of British Columbia Okanagan, where her research examines global governance, technology, human rights, and civil society. Her book We, the Data: Human Rights in the Digital Age explores how Big Data and artificial intelligence challenge traditional understandings of human rights and won the 2024 Balsillie Prize for Public Policy. Her current research includes AI and the future of extractive politics, making her an important voice on how emerging technologies intersect with governance, data, power, and individual rights. 

Caroline Gwynn Monagle, Vice President, Strategic Initiatives, R1 RCM

Caroline Gwynn Monagle is Vice President of Strategic Initiatives at R1 RCM, a healthcare technology and services company, where she leads strategic initiatives within an industry undergoing rapid technological transformation. A Georgia Tech alumna, Monagle was recognized as a Georgia Tech 40 Under 40 honoree in 2025 and previously received the Ivan Allen Jr. Legacy Award. Her leadership experience at the intersection of healthcare, technology, strategy, and organizational change brings an industry perspective to the conversation about AI's impact on health and society. 

Marilyn A. Brown, Regents and Brook Byers Professor, Jimmy and Rosalynn Carter School of Public Policy, Georgia Institute of Technology

Marilyn A. Brown is Regents’ and Brook Byers Professor of Sustainable Systems in Georgia Tech’s Jimmy and Rosalynn Carter School of Public Policy and Director of the Climate and Energy Policy Laboratory. Before joining Georgia Tech, she held leadership roles at Oak Ridge National Laboratory and later served as a presidentially appointed member of the Tennessee Valley Authority Board. Her research examines energy policy, efficiency, electricity systems, clean-energy technologies, and resilience, providing critical expertise on the rapidly growing relationship between artificial intelligence, energy demand, infrastructure, and sustainability. 

How is artificial intelligence changing the way knowledge is created? Examine AI's growing role in academic research, including how researchers use emerging tools to accelerate discovery, approach complex questions, and navigate the ethical and practical implications of AI-assisted scholarship.

Panelists

Sebastian Porsdam Mann, Assistant Professor CeBIL, University of Copenhagen

Sebastian Porsdam Mann is Assistant Professor at the University of Copenhagen’s Center for Advanced Studies in Bioscience Innovation Law. With training spanning philosophy, neuroscience, applied ethics, and international human rights law, his research examines how emerging technologies can advance scientific progress while navigating ethical and regulatory challenges. His work has directly explored generative AI in academic writing and idea generation, as well as AI's potential role in the future of academic peer review, positioning him to address both the opportunities and risks AI creates throughout the research process. 

Kevin Mills,  Head of Education and Government GTM, OpenAI

Kevin Mills is Head of Education and Government Go-to-Market at OpenAI, where his work focuses on expanding the responsible use of artificial intelligence across educational and public-sector institutions. His work includes initiatives supporting the adoption of AI tools in education, including ChatGPT Edu and partnerships focused on helping students, educators, and institutions develop practical experience using AI. He brings an industry perspective on how AI tools are moving from experimentation into real academic and institutional environments. 

Sarah H. Salter, Director of the Writing Program & Professor of Pedagogy, Emory University

Sarah H. Salter is a Teaching Professor and Director of the Writing Program at Emory University whose research focuses on American literature, periodical studies, collaboration, and digital humanities. Her scholarship has included interdisciplinary work using machine-learning methods to analyze the visual structures of historical newspapers, combining literary study, library science, and computational approaches. Her perspective brings an important humanities dimension to the conversation about how computational tools and AI are changing research methods, scholarly interpretation, writing, and knowledge production. 

Allegra Smith, Assistant Professor of Technical Communication, S School of Literature, Media, and Communication, Georgia Institute of Technology

Allegra Smith is an Assistant Professor in Georgia Tech’s School of Literature, Media, and Communication whose research examines technical and professional communication, digital technologies, user experience, access, and equity. Her teaching and research include work involving generative AI, digital communication, and undergraduate research, alongside extensive scholarship on how people interact with technology. She brings a valuable perspective on how AI is affecting research, writing, communication, pedagogy, and the experiences of the people using these emerging tools. 

Bio: Sarah H. Q. Li is an assistant professor in the School of Aerospace Engineering at the Georgia Institute of Technology, where she leads the Control, Coordination, and Competition under Uncertainty (C3U) Lab. She received her Ph.D. in aeronautics and astronautics at the University of Washington, and completed her postdoc with the Autonomous Control Lab at ETH Zurich. Her work combines optimal control, stochastic decision processes, and game theory to study how autonomous agents can coordinate safely and efficiently in uncertain environments.

1. Assisting student performers with understanding of Minecraft and using the computer software 
2. For those with music ability, assisting performers as needed 
3. Serving as event production support on the weekend of November 14th

The work period is late September through November 14th, with remote
planning/build sessions, an in-person workshop on November 7th, and the
November 14 performance. This is a volunteer opportunity, and participants receive two complimentary
performance ticketsand free admissionto Jazzii’s November 7th workshop.

Apply here by September 25th at 11:59 PM. Some applicants may be invited to a brief online follow-up conversation during the week of September 28. If so, we will contact you directly to schedule.

The American Southeast sits at the exact intersection of these trends. With its expanding industrial footprint, world-class port infrastructure, and major investments in battery and automotive manufacturing, the region is uniquely positioned to drive U.S.–East Asia supply chain integration. This symposium brings together international diplomats, policy experts, and regional leaders to examine how Washington, its Indo-Pacific partners, and the Southeast can collaborate to advance economic security and technological leadership.

Registration requested.

Event Schedule

9:30 – 10:45 a.m. Keynote Speaker

A framing perspective on how geoeconomics and strategic supply chain resilience are reshaping U.S. foreign policy and Indo-Pacific security.

• Patrick Cronin (Asia-Pacific Security Chair, Hudson Institute)

11 a.m. – 12:45 p.m. Expert Panel: East Asian Perspectives on the New Geoeconomic Landscape

Practitioners from Taiwan, Japan, and South Korea share ground-level insights on semiconductor integration, rare earth supply chain models, and balancing commercial ties with alliance commitments.

• Taiwan: Roy Chun Lee (Associate Research Fellow, Chung-Hua Institution for Economic Research)
• Japan: Kazuto Suzuki (Professor, University of Tokyo; Director, Institute of Geoeconomics)
• South Korea: Seong-Hyon Lee (Senior Fellow, George H.W. Bush Foundation for U.S.-China Relations)

12:45 – 2 p.m. Luncheon Address: Taiwan’s Strategic Partnership with the United States

Ambassador Yui offers key diplomatic perspectives on the evolving U.S.–Taiwan bilateral economic partnership and cross-Pacific supply chain architecture.

• Ambassador Alexander Tah-ray Yui (Representative, Taipei Economic and Cultural Representative Office in the United States)

2 – 3:45 p.m. Roundtable: Opportunities for U.S.-East Asia Partnerships and the Southeast United States

Regional leaders discuss how the Southeast can leverage its ports, advanced manufacturing footprint, and foreign direct investment to support allied supply chain resilience.

• Jared Lin (Director General, Taipei Economic and Cultural Office in Atlanta)
• Stefan A. Harrigan (Senior Manager, Global Business Development, Metro Atlanta Chamber)
• Japan & South Korea Representatives: TBA

Parking and Directions

Carla will share her journey from Georgia Tech student to pharmaceutical industry professional, highlighting how perseverance, growth, and embracing opportunities helped her achieve goals beyond what she imagined as an undergraduate.

📅 September 18, 2026

🕚 11:00 a.m. - 11:30 a.m.

📍 U.A. Whitaker, Room 1103

Whether you're considering graduate school, interested in the biomedical industry, or curious about career paths that combine engineering, data science, and healthcare, this is a great opportunity to learn from a fellow Yellow Jacket who has built a successful career at the intersection of research and innovation.

RSVP here today: https://forms.cloud.microsoft/r/8bVXi7iPHg

Ion Trap Mass Spectrometry Beyond m/z

ABSTRACT:

This seminar will introduce me and how I think about chemistry. Naturally, the goal of any chemist is to do cool chemistry that matters, but the challenge is how to get there. This will be the seminar’s thematic center. Two ideas guide my approach: an appreciation for chemistry in a broad sense and knowledge about the technical details of instrumental analysis. As an illustration, I will highlight a few key findings from the literature and merge this narrative with my own work. On the technical side, my key argument is that quadrupole ion traps offer under-exploited functions perfect for the AI-powered era. I will discuss my work with serine octamer chiral molecular clusters and MS/MS fragmentation, which has broad relevance in origins of life chemistry/homochirality and chemical analysis. An important motivator for me is mentorship and I will take time to explain my work with undergraduate and visiting scholars. To close, I will zoom back out and discuss chemistry’s unmet needs and explain how my work fits in. Since AI has all the “settled science” at its fingertips, doing novel experiments has never been more advantageous and ion traps offer several avenues for new experiment types.

The program will open with an update from Jennifer Chirico on the Georgia Tech Climate Action Plan. Presentations from leading researchers will follow, including Suhas Jain, Ali Sarhadi, Abigale Stangl, and Iris Tien, followed by an interactive panel discussion where attendees can engage with the speakers and gain insights from diverse perspectives across climate science, engineering, risk analysis, and sustainability research.

Registration is required. Please complete the registration form to reserve your spot. Breakfast will be provided.

Mohit Chandra

Ph.D. Student in Computer Science

School of Interactive Computing 

Georgia Institute of Technology 

https://mohit3011.github.io/

Date: 29th September, 2026

Time: 10 am - 12:30 pm ET

Location:  CODA C1215

Microsoft Teams Meeting Link: Mohit Chandra: CS PhD Thesis Proposal | Meeting-Join | Microsoft Teams

Committee:

Dr. Munmun De Choudhury (Advisor), School of Interactive Computing, Georgia Institute of Technology

Dr. Srijan Kumar, School of Computational Science and Engineering, Georgia Institute of Technology

Dr. Jennifer Gahee Kim, School of Interactive Computing, Georgia Institute of Technology

Dr. Monojit Choudhury, Mohamed bin Zayed University of Artificial Intelligence

Dr. Scott Counts, IDEAS Research Group, Microsoft

Abstract:

With nearly 70% of individuals around the globe lacking adequate access to mental healthcare and wait times for clinical appointments extending up to several weeks, individuals are increasingly turning to Large Language Models (LLMs) to obtain healthcare information, emotional validation, and social and mental health support. However, the use of generative AI systems in mental health settings presents risks. Current AI development, training, and evaluation paradigms continue to rely on simplified mental health scenarios that dehumanize users by treating them as abstract data subjects. While LLMs achieve high scores on objective medical benchmarks, they fail to understand subjective, contextual, and personal nuances that define real-world mental health interactions. By failing to understand these experiential insights, these systems provide advice that may fail to reflect the empathy, practical actionability, and therapeutic alignment inherent to human-facilitated mental healthcare. 

This dissertation posits that meaningful human-AI alignment in mental health scenarios requires a shift toward lived-experience inspired assessment and stakeholder-informed operationalization to ensure meaningful integration of generative AI systems in mental health contexts. To this end, this dissertation establishes an ecosystem for centering humans in generative AI development process through four pillars: (1) providing a theoretical foundation for lived-experience-centered AI design, (2) computational approaches for assessing how lived-experience dimensions manifest within current AI models, (3) operationalization methods to capture stakeholder insights and simulate human-AI interactions, and (4) integrating stakeholder insights into model alignment and response generation.

• (1) A Theoretical Foundation for Lived-Experience Centered Design [AIES 2025]: Drawing from work across psychology, education, healthcare, and social policy, this work presents a framework (LEAF) for grounding lived experiences within AI systems. LEAF outlines mechanisms for embedding these perspectives at every stage of the AI development pipeline, from problem definition and data curation to model evaluation and post-deployment monitoring.

• (2) Assessing Presence of Lived Experience within AI systems [Web Conference 2024, NAACL 2025]: In this pillar, I introduce computational approaches for assessing presence of linguistic identity, and domain experiential knowledge dimensions of lived experience in generative AI systems. Through XLingEval and the XLingHealth benchmark, I highlight the disparity in quality of LLM-generated responses to healthcare queries across four languages, showing that non-English LLM responses suffer from reductions in factual correctness, output consistency, and verifiability. Through the Psych-ADR benchmark and ADRA framework, I evaluate alignment between LLM and experts on addressing adverse drug reactions from psychiatric medications, revealing that while models achieve tonal alignment with clinicians, they lack diagnostic ability, and provide less actionable harm-reduction strategies.

• (3) Operationalization of Lived Experience for AI systems [FAccT 2025, ACL 2026]: To translate stakeholder experiences into actionable mechanisms for model development, this pillar presents methods for systematically capturing lived-experience insights and simulating realistic clinical workflows. I introduce a novel AI-psychological risk taxonomy (comprising 19 AI behaviors, 21 negative psychological impacts, and 15 user contexts) and a multi-path vignette framework to highlight cases when interactions with AI systems could cause mental health related harms. In the second work,  addressing the need for realistic post-training data, I present MedAgent to synthetically generate clinically grounded mental health sensemaking conversations and present MultiSenseEval, revealing how frontier reasoning AI models struggle with diagnostic accuracy and patient-centered communication across diverse patient personas and extended dialogue turns.

• (4) Integrating Lived Experience [Completed Work, and the Proposed Study]: For the last pillar of the dissertation, I demonstrate how to integrate human perspectives into model post-training and AI-experimental studies. Within the preliminary study before the proposed study, I introduce the COPES Dataset and three-axis evaluation framework for post-training LLMs to align with community perspectives on mental health support-seeking queries. For the proposed study, I build on these findings to aim to conduct a single-session Randomized Control Trial to assess the effectiveness of AI-assisted peer support for life struggles.

Collectively, this dissertation establishes an ecosystem of theoretical frameworks, computational methodologies, and empirical resources for centering human lived experience within AI for high-stakes mental health use-case. Rather than treating lived experience as an abstract design aspiration, this work concretely enables researchers and practitioners to move past static benchmarks, objective metrics, overly simplified human-AI interaction modeling to adapt multi-axes assessment approaches, stakeholder-informed human-AI interaction modeling, and methodologies for integrating subjective lived experiences in AI development lifecycle.

Meeting Details: The meeting will be held in a hybrid format. Attendees may participate either in person at CODA C1215 or virtually via Microsoft Teams using the provided link.

Friday, Oct. 2 
6:00 - 8:00 p.m.
Tech Rec
John Lewis Student Center
Pizza to be provided

For more about CSE GSE, check out: https://cse.gatech.edu/cse-graduate-student-association

This event is part of the Ivan Allen Advantage Alumni Speaker Series. Refreshments will be provided. All Georgia Tech students, faculty, and staff are welcome to attend. A limited number of 1:1 and small-group mentorship slots will be available to students who RSVP for the event.    

About the Speakers

Edward V. Byrns Jr. is a triple-degree recipient from Georgia Tech, holding a Ph.D. in Engineering, an M.S. in Economics, and an M.S. in Engineering. While a graduate student, he realized that his academic interests spanned engineering and social sciences. Georgia Tech was the ideal institution to build a bridge between both. For over 25 years, Byrns has been working in commodity and weather markets, and he currently heads the climate risk team at Atrium Underwriting, a syndicate of Lloyd’s of London. Byrns has been an entrepreneur at the intersection of insurance underwriting, commodity trading, and analytic technology. He founded a startup, held quantitative leadership positions, and briefly served as an adjunct professor. His career trajectory reflects a consistent drive to translate technical insights into market-based tools for addressing large-scale global challenges.   

Amy Phuong is vice president of government relations for the Atlanta Hawks and State Farm Arena. This position is an expansion of the Atlanta Hawks’ External Affairs efforts to unite the broader Atlanta community through the play of basketball while deepening the organization’s relationships with local and state leaders. Amy is responsible for the Hawks’ strategic government and external affairs strategy which includes managing various lobbying efforts and policy regulation. She served as Chief Operating Officer for Saving Our Atlanta Region’s Residents (SOARR), a regionally coordinated, cross-sector response to the growing eviction crisis of renters in Atlanta, as an Executive on Loan in 2021. In this role, she was responsible for helping to operationalize this effort by bringing together public and private resources and a diverse set of civic leaders to keep families stabilized and housed for the duration of Covid-19.

Registration Deadline

• Tuesday, Sept. 8 @ 11:59 ET - Register Here

View sponsorship opportunities

Symposium Agenda

Location: Marcus Nanotechnology Building, Rooms 1116-1118 (unless otherwise noted)

• 7:30 a.m.     Check-in | Continental Breakfast
• 8:20 a.m.     Welcome - Adegboyega Oyelere, Symposium Chair, Georgia Tech
• 8:25 a.m.     Opening Remarks - Vicki Wysocki, Chair, School of Chemistry and Biochemistry, Georgia Tech

Session I - Oral Presentations

Moderator: Tyler Beyett

• 8:30 a.m.    "Targeting Highly Aggressive Cancers by Uncovering Druggable Vulnerabilities" - Ozgur Sahin, Medical University of South Carolina
• 8:50 a.m.     "Inhibition of Topoisomerase IIα Activity by Linker Histone H1" - Yuhong Fan, Georgia Institute of Technology
• 9:10 a.m.     "Neo-Cysteine Molecular Glues for Targeting Mutated SMAD4 Protein" - Pooja Kumari, Emory University
• 9:30 a.m.     "In Vivo Efficacy of Abbapolin Degraders of the PLK1 PBD and Synergy With Androgen Therapy in Prostate Cancer" - Shikha Kumari, University of South Carolina
• 9:50 a.m.     "Cathepsin Inhibitor Suppresses the Growth of Ectopic Hepatocellular Carcinoma Tumors in Mouse Models" - Olamide Crown, Alabama A&M University
• 10:10 a.m.   Break

Session II - Oral Presentations

Moderator: Campbell McInnes

• 10:30 a.m.   "Turning α-Amylase Activity Into Light: Polycyclic 1,2-BN-Heteroarene-Based AIE Supramolecular Nanocapsules for Biosensing" - Carl Saint-Louis, Kennesaw State University
• 10:50 a.m.   "Passive and Activatable Targeting of Near-Infrared Fluorophores for Tissue, Bone, Cartilage, and Disease Imaging in Image-Guided Surgery" - Maged Henary, Georgia State University  
• 11:10 a.m.   "Application of Natural and Semisynthetic Saponins in Biomedicine" - Pengfei Wang, University of Alabama at Birmingham
• 11:30 a.m.   "FMCAP (DDG-002): A Potent Modified-Nucleotide Analog Against Monkeypox Virus (MPXV)" - Uma Singh, University of Georgia
• 11:50 a.m.   "Developing Ir(III)/Ru(II) Bisterpyridine Complexes as Antimicrobial Photodynamic Therapeutic Agents" - Wenfang Sun, The University of Alabama 
• 12:10 p.m.   Lunch - Petit Biotechnology Building ("IBB") - next door to Marcus Nanotech Bldg.

Session III - Oral Presentations

Moderator: Y. George Zheng

• 1:20 p.m.     "Reactive Oxygen Species (ROS) Research: How Much Do We Really Know What Our Tools Are Measuring?" - Binghe Wang, Georgia State University
• 1:40 p.m.     "A Compact Tag-Directed Platform Enables Rapid Targeted Protein Degradation" -  Dongwen Lyu, Augusta University
• 2:00 p.m.     "Optical Tools for Precisely Controlling Dopamine Receptors" - Prashant Donthamsetti, Vanderbilt University   
• 2:20 p.m.     "Advancing Lead Generation: Overcoming Selectivity Challenges With DNA-Encoded Libraries" - Srinivas Chamakuri, Baylor College of Medicine
• 2:40 p.m.      "Chemical Biology of Druggable Bacteria to combate Antibiotic-Resistant Pathogens" - Ashfaqul Alam, University of Kentucky
• 3 p.m.           Break

Session IV - Keynote Lecture

Moderator: Alex G. Waterson

• 3:15 p.m.     Keynote Presentation - "A Novel Chemical Biology Platform for Deubiquitylases" - Sara Buhrlage, Harvard Medical School*

Session V - Poster Session and Networking Reception

Moderator: Victor Ogungbe

• 4:30 p.m.     Odd-numbered posters
• 5:40 p.m.     Even-numbered posters
• 6:40 p.m.     Adjourn

**********************************

*Keynote Lecture:
Sara Burlage
Associate Professor
Dana-Farber Cancer Institute department of Cancer Biology
Department of Biological Chemistry and Molecular Pharmacology
Harvard Medical School

ABSTRACT
Deubiquitylases (DUBs) are a large family of enzymes that remove ubiquitin or ubiquitin chains from substrate proteins. Similar to other components of the UPS, DUBs have been associated with disease and pursued as drug targets. Despite enthusiasm around targeting DUBs both with inhibitors as well as DUBTACs, there remain unanswered fundamental questions around substrates and substrate scope as well as how DUBs work at a detailed mechanistic level. The overarching goal of our lab is to develop chemical tools that can be deployed to study basic function and translational potential of DUBs. Our platform integrates DUB library synthesis, medicinal chemistry, biochemistry, high-throughput screening, chemoproteomics, chemical genomics, structural biology, target validation and cancer biology. I will discuss recent discoveries enabled by our platform including new mechanism-of-action ligands for DUBs and their study in rare disease as well as new insights into DUB interplay with other components of the UPS.

BIO
Sara Buhrlage is an Associate Professor holding joint appointments in the Dana-Farber Cancer Institute department of Cancer Biology and the Harvard Medical School department of Biological Chemistry and Molecular Pharmacology. Buhrlage is a leader in harnessing deubiquitylases (DUBs) as emergent drug targets, where her lab has pioneered new approaches for interrogating DUB function, new insights into the chemical tractability of DUBs, and mapping the therapeutic potential of DUBs in cancer. In addition to research, she is dedicated to graduate education, holding leadership roles in multiple graduate programs and teaching graduate level courses. More recently, she has become involved in biotech and company creation as a scientific founder of Entact Bio. Buhrlage earned a Doctor of Philosophy in organic chemistry from the University of Michigan and completed a post-doctoral fellowship at the Broad Institute.

Abstract: Two-sided matching platforms, including labor markets, dating apps, accommodation services, and ridesharing systems, must make matching decisions in the presence of choice congestion and strategic platform design challenges. When agents have correlated preferences, popular options can attract too much demand, reduce overall efficiency, and lead to poor market outcomes. In this talk, I will present a framework for two-sided assortment optimization that studies how a platform should decide which options to display to agents and in what order, with the goal of improving matching performance. The main focus will be on maximizing the expected number of matches under general choice models. I will describe several natural classes of platform policies, ranging from static simultaneous displays to fully adaptive sequential policies, and compare their power through adaptivity gap results. I will also discuss polynomial-time approximation algorithms for computing near-optimal policies, and then briefly discuss the revenue-maximization version of the problem, where matches generate pair-dependent rewards. This talk is based on joint works with Alfredo Torrico, Ulysse Hennebelle, and Mohammadreza Ahmadnejadsaein.
 

Bio: Omar El Housni is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell Tech and Cornell University. He is a Field Member of the Center of Applied Mathematics at Cornell. He is also an Amazon Scholar. His research focuses on decision-making under uncertainty where he aims to develop optimization models and design robust and efficient algorithms to address a wide range of operational problems, including revenue management problems such as assortment optimization and online matchings. Omar has spent time as a research scientist at Amazon and Uber where he contributed to the design and implementation of data-driven optimization models for matching and retailing platforms. Omar holds a PhD in Operations Research from Columbia University and an MS and BS in Applied Mathematics from Ecole Polytechnique (Paris). His work has been recognized by INFORMS George Nicholson award and his current research is supported by NSF. 

Abstract: Prior literature shows that self-reports, especially those of sensitive behaviors, tend to be biased. For example, respondents may over-report their family origin and volunteering experiences while under-reporting their drinking and smoking behaviors. In this study I examine a social network-based approach to addressing self-reporting bias, which is to ask peers (e.g. classmates or co-workers) to provide alternative reports that can be used to cross-validate and supplement self-reports. I first formalize the data generation process statistically by proposing a model containing two sub-models, one for the self-reports and the other for the peer-reports. In each of the sub-models, I treat the observed report as a probabilistic realization of a truthful report and a false report. The model can incorporate both self- and peer-characteristics and also dyadic characteristics. A Bayesian approach helps make the model self-containing by imposing a prior on the unknown ego's behavior. Then the Bayesian approach simulates self- and peer-reports according to the data generation process iteratively until the simulated reports emulate the observed reports. Through a case study on self- and peer-reports of smoking among adolescents, I demonstrate that the Bayesian approach can not only reveal how multiple characteristics are related to reporting biases but also incorporate these characteristics effectively into the imputation of the true behavior.
 

Bio: Dr. Weihua An is Professor and Chair of Sociology and Professor of Data and Decision Sciences at Emory University. He is also an affiliated faculty member of the East Asian Studies Program, the Goizueta Business School, and the Rollins School of Public Health. He earned his Ph.D. in Sociology and A.M. in Statistics from Harvard University. Dr. An's research advances theories and methods in network analysis and causal inference. He has published widely in both methodological and substantive journals and also authored multiple statistical packages, which have received 200K downloads in total. He currently serves as the Editor of Sociological Methodology and the Chair-Elect of the Methodology section of the American Sociological Association. He is a recipient of the Faculty Teaching Award from Emory Sociology and the Clifford Clogg Award and the Leo Goodman Award from the American Sociological Association. He has advised 28 PhD dissertations and ten undergraduate honors theses.

Abstract: The agriculture sector is a major economic driver for Africa. However, climatic change is driving severe disruption across Africa, causing prolonged dry seasons and erratic rainfall. As a result, farmers are facing lower farming yield. To mitigate this serious challenge, farmers must adopt modern and green technologies, like solar irrigation. To show the potential of solar irrigation system to mitigate this critical problem, a research project has been developed with the collaboration of Georgia Tech, University of Rwanda and Adama Science and Technology University. The project aims at developing a PV irrigation system that integrates IoT and controllers for real-time monitoring of the performance of the PV-irrigation system and for optimizing water conservation. This project is envisioned to be a prototype model for further scaling up the deployment of PV-irrigation systems in Africa to enhance sustainable agricultural. 
As part of the whole project, this seminar focuses more on the design and economic assessment of the system for a particular village in Rwanda.
 

Bio: Getachew Biru Worku obtained his MSC and PhD in Electrical Engineering from Dresden University of Technology, Germany. He has more than 30 years of academic and research experience in academic institutions and industry. He has extensive experience in teaching a broad range of electrical engineering courses with excellent feedback and acknowledgements from faculties and students. He has been lecturing courses such as Power Quality and Reliability, Power System Operation and Control, High Voltage Engineering, Power System Analysis, Power Transmission and Distribution Engineering, Electrical Machines Design, Smart Grid and Traction Power System in various Ethiopian Universities and University of Rwanda. He is currently employed as an associate professor at the University of Rwanda giving lectures and advising postgraduate students. He is a dedicated researcher in renewable energy deployment focusing on reliability of off-grid and microgrids to bring sustainable electrical power to the underserved areas. His research areas are electrical power and renewable energy and has authored and co-authored more than 45 papers in peer-reviewed journals.

The application, details, and rubric can be found here: https://gatech.infoready4.com/#freeformCompetitionDetail/2030289

If you cannot make your assigned group day, please feel free to come by on any operating date below: 

• Time: 10:00AM - 3:00PM
• Dates: 
  • 10/6: Staff
  • 10/7: Faculty
  • 10/8: Ph.D. Students

Recommendations for attire: 

• Wear blue, or dark-colored clothing (will be on a white backdrop)
• Do NOT wear red
• Avoid wearing large jewelry and patterns

Advisor: Dr. Koki Ho

Milestone: PhD Thesis Proposal

Degree Program: Aerospace Engineering

Title: Optimization of Sustainable Space Logistics Systems

Abstract: As human space exploration transitions from Apollo-era single-spacecraft missions to interconnected, multi-asset space systems, maximizing system performance requires collaboration among orbital assets. Long-term sustainability in these complex operations demands rigorous mathematical modeling and systematic optimization. However, extending terrestrial routing studies to space logistics is inherently challenging. Because orbital mechanics are nonlinear and nonconvex, no universal solvers exist, so problem-specific optimization frameworks are needed. This thesis presents optimization frameworks to enable sustainable space logistics systems, focusing on Earth-orbiting satellite servicing, orbital infrastructure, and resource operations. First, a mathematical formulation and solution methodology are presented to determine in-space depot placement in continuous orbital space for multi-satellite servicing, overcoming the combinatorial complexity and potential suboptimality of conventional orbit discretization. Second, multi-satellite servicing architectures with en route refueling are formulated as arc-based and path-based formulations to determine coupled decisions on visiting sequences, refueling amounts, and transfer trajectories, accompanied by a comparative analysis of the two formulations. Finally, for a space circular economy, this thesis unifies active debris removal and on-orbit servicing into an integrated orbital resource harvesting and redistribution framework, reducing reliance on supply launches from Earth. Collectively, this thesis establishes integrated optimization frameworks for continuous depot placement, satellite servicing with trajectory design and en route refueling, and in-space resource recycling, providing insights for sustainable space logistics systems.

Date and time: 2026-09-16, 10:00 am to 12:00 pm

Location: Montgomery Knight Building 317

Committee:
Dr. Koki Ho (advisor), School of Aerospace Engineering
Dr. Koki Ho, School of Aerospace Engineering
Dr. Brian C Gunter, School of Aerospace Engineering
Dr. Glenn Lightsey, School of Aerospace Engineering 
, 
, 

Committee:

Dr. Maryam Saeedifard, ECE, Chair, Advisor

Dr. Mitchell Walker, AE, Co-Advisor

Dr. Morris Cohen, ECE

Dr. David Andreson, ECE

Dr. Evangelos Theodorou, AE

Dr. Ken Hara, Stanford

Committee: 

Dr. Hasler, Advisor         

Dr. Chatterjee, Chair

Dr. Sathe

Committee: 

Dr. Bakir, Advisor 

Dr. Ansari, Chair

Dr. Cressler

Abstract: Former Delta data scientist Nick Sovich introduces SCORPION, a machine learning model that predicts standby boarding probabilities for nearly 500,000 Delta flights up to four months in advance. ​

Built from his experience on 500+ standby flights, SCORPION continuously retrains on historical outcomes and is now used by thousands of Delta employees.​

Book sale and signing to follow the reading.

Register for Ally's Webinar

Whether you're new to Ally or looking for ways to maximize its impact, this session will help you feel more confident about supporting all learners while saving time.

Audience: Instructors & Faculty
Date: September 16, 2026 at 10AM EST

Register for Ally's Webinar

Whether you're new to Ally or looking for ways to maximize its impact, this session will help you feel more confident about supporting all learners while saving time.

Audience: Instructors & Faculty
Date: September 16, 2026 at 2PM EST

Register for Ally's Webinar

• Thursday, September 24 at 3PM EST | Register for Turnitin's Webinar

Register for Perusall's Webinar

Register for Perusall's Webinar

In this session, you'll learn how to:

• Discuss AI best practices and explore academic integrity features
• Add and create Checkpoint prompts or quizzes within a reading, video or podcase

Register for Perusall's Webinar

In this Innovate session, you'll learn how to:

• Create student groups for flexible collaboration
• Set up grading and analytics for all assignment types

Register for Perusall's Webinar

In this Innovate session, you'll learn how to:

• Create student groups for flexible collaboration
• Set up grading and analytics for all assignment types

Register for Perusall's Webinar

Tuesday, September 8: Exhibition Opening & Artist Panel (5–7 PM) 

Kick off Creative Wellness Week with an evening of art, conversation, and community. Explore an exhibition featuring works by Georgia Tech students TeAiris Majors and Sylvia H. Janicki, as well as Atlanta artists Honey Pierre and Jasmin Warnock. Stay for light refreshments and an artist panel led by Belonging and Student Support.

Click Here to RSVP!

Wednesday, September 9: Printmaking Workshop with Jasmin Warnock (4–6 PM)

Discover printmaking as a practice of reflection, expression, and emotional release while creating your own custom tote bag. This guided workshop invites participants to slow down, connect through creativity, and leave with a one-of-a-kind piece to take home.

Click Here to RSVP!

Thursday, September 10: Neural Threads Workshop with Honey Pierre (4–6 PM)

Explore the relationship between color, memory, the nervous system, and emotional well-being through natural dye and textile practices. This interdisciplinary workshop offers a restorative space for mindfulness, creativity, and self-expression.

Click Here to RSVP!

Friday, September 11: Sound Bath with Ruby Velle (4:30–6 PM)

Close out Creative Wellness Week with an immersive sound bath designed to encourage rest, reflection, and nervous system regulation. Through sustained tones and meditative sound, participants are invited to decompress, reconnect, and recharge.

Please bring a yoga mat, blanket, towel, or another comfortable item to rest on.

Click Here to RSVP!

Competition Events

Event #1-Spaghetti Tower

• In this event, competitors will be tasked with assembling a tower under tight time pressure.​
• Towers will be scored based on a weighted sum of height (measured by a judge) plus an audience popularity score.​
• For this event, participants will be given a planning phase to formulate their plan to assemble the tower. Little time will actually be given to build the tower so thinking ahead is a must!

Event #2-Write it, Do it

• In this event, one team member will be provided a model and must direct the other team members to recreate a Lego structure as accurately as possible. ​
• Judges will be provided a rubric with the model split into different "sections," and errors in each section will result in deductions.
• This task requires careful communication between team members to accurately convey spatial information with limited time.​​

​Event #3-Newspaper Chair

• In this event, teams will be paired with audience members (clients) to construct a chair based on client demands. (Style, ease of use, stability, etc.)​
• Event judges will work with clients to ensure demands of similar difficulty. Teams' scores will be a weighted sum between audience vote and judges' evaluation of completion of the clients' demands.​
• Unlike other events that have already been "solved", the introduction of client demands ensures each team's task is different and requires them to parse verbal information for engineering requirements.​

​

​In addition, engineering-focused student groups are encouraged to participate in the miniature resource fair of the event. If your organization would like to table at this event, please contact Jenn Bennett, jbennett316@gatech.edu.

RSVPing on Engage will ensure you have a seat reserved as an audience member. If you would like to be a competitor in the event, fill out the form below to be considered. If you would like to be placed in a group (must be 4 members), make sure each member puts the same team name.  

Link to Team Registration Form: 

https://forms.cloud.microsoft/r/NTcd3QsfUm 

*Refreshments: 12-12:30 PM, ES&T Atrium

• David Beasley, former Governor of South Carolina and former Executive Director of the United Nations World Food Programme
• Ambassador Michèle Taylor, former U.S. Ambassador to the UN Human Rights Council and Distinguished Professor of the Practice at the Nunn School

Together, they will draw on their deep experience at the front lines of global diplomacy to explore how humanitarian efforts must adapt to tackle escalating food crises in a rapidly changing world.

Seating is free, open to the public, and available on a first-come, first-served basis. Join us for an inspiring discussion on the future of global hunger relief!