Presenter:
Samantha Yeligar
Associate Professor of Medicine
Emory University School of Medicine / Atlanta VA Medical Center

Reasons to go:

• For this year (2027), we will be offering a $1000 subsidy for program participants!
• Global tech impact: See where the next billion users are coming online.
• Career growth: Employers love global tech experience.
• Community: Learn and travel with fellow GT CS students.
• Adventure: From hackathons to heritage sites—discover India.

Structure of the program:

• Two online courses for the first four weeks, then the last two weeks onsite in Mumbai, India
• Two weeks in Mumbai will be planned for you with class time and field trips, as well as cultural outings while interacting with students at Mumbai’s Atlas Skilltech University 
• First four weeks, take the online courses anywhere; for the last two weeks, participation onsite in Mumbai and lodging at Atlas Skilltech's accommodation are required

Email indiaprogram@cc.gatech.edu for questions. Application deadline: February 1st in Atlas.

Ask questions about the CoC's newest program, "Technology Design and Ethics in India," a 6-week program (May 17 - June 25, 2027), with 4 weeks of online instruction followed by 2 weeks of continued GT instruction in Mumbai, India. Drop in for a few minutes to ask your question or stay the whole hour and hear what other students are asking. 

Program Courses:

The 2 foundational Computer Science courses of the program will be taught by Georgia Tech CS faculty and Program Director, Naveena Karusala.

• CS 4001 – Computing & Society (Ethics Credit) - Students will critically examine how issues around technology, such as globalization, bias, privacy, and others, affect people worldwide.

• CS 3751 – Intro to User Interface Design - Students will explore culturally situated approaches to design and, through the course project, create an inventive design artifact.

No questions and ready to go? Apply HERE. Email contact: indiaprogram@cc.gatech.edu. To learn more about available virtual meeting opportunities, visit cc.gatech.edu/india.

Doctor of Philosophy in Physics 

School of Physics Dissertation Defense

Jiahao Chen
Dr. Dragomir Davidovic, School of Physics, Georgia Institute of Technology (Advisor)

Numerical Approach to the Time-Convolutionless (TCL) Master Equation

Date: Tuesday, November 10, 2026
Time: 8:30 a.m. EST
Location: Howey N201/202
Virtual: Join the Microsoft Teams meeting / Meeting ID: 273 524 787 663 512 4 / Passcode: ub6Fd2TB

Thesis Committee:

Dr. Brian Kennedy, School of Physics, Georgia Institute of Technology

Dr. Martin Mourigal, School of Physics, Georgia Institute of Technology

Dr. Xueda Wen, School of Physics, Georgia Institute of Technology

Dr. Qi Tang, School of Computational Science and Engineering, Georgia Institute of Technology

Abstract:

Open quantum systems are quantum systems that interact with their environment. The time-convolutionless (TCL) master equation provides a formally exact, time-local description of their dynamics. However, the computational cost of evaluating higher-order terms often limits practical applications to the second-order approximation. We develop systematic numerical methods that reduce the temporal complexity to O(N log N) for TCL4 and O(N log² N) for TCL6, where N is the number of time points. We extend the construction to higher orders and assess its accuracy using spin–boson benchmarks. We also investigate the convergence limits of the TCL expansion and explore resummation methods for extending accurate predictions beyond direct perturbative truncation.

Abstract: 

Rare earth elements (REEs) are essential to advanced and clean energy technologies. Sustainable REE resource development requires both a fundamental understanding of the geochemical processes governing resource formation and advances in environmentally compatible extraction and recovery strategies. Highly weathered, clay-rich deposits represent important natural REE resources. However, the molecular-scale mechanisms by which solution chemistry, mineral surfaces, and naturally occurring ligands regulate REE behavior remain incompletely understood. Meanwhile, conventional REE extraction and recovery often involve high chemical and energy consumption and substantial waste generation. Bio-assisted approaches, including fungal bioleaching, offer promising alternatives that operate under milder conditions and may reduce chemical consumption and environmental impacts. However, the mechanistic links among cultivation conditions, microbial metabolism, and REE mobilization remain poorly understood.

This dissertation investigates the key geochemical controls on REE speciation, mobility, secondary phase formation during chemical weathering, and explores fungal bioleaching as a promising approach to REE extraction. Controlled laboratory experiments integrate solid-state nuclear magnetic resonance spectroscopy, synchrotron X-ray absorption spectroscopy, microscopy, aqueous-phase analyses, and extracellular metabolomics to connect molecular-scale reaction mechanisms controlling REE behavior at mineral-water interfaces and extraction performance. Using yttrium (Y) as a probe for heavy REEs, phosphate and citrate as representative ligands, kaolinite as a mineral substrate, this work identifies complementary mechanisms governing REE retention and release during weathering. Phosphate promotes Y immobilization at kaolinite-water interfaces through ternary surface complex and secondary Y-phosphate precipitation. In contrast, citrate can promote either Y retention or remobilization, depending on ligand concentration, solution pH, and reaction sequence. Reactant concentrations and solution pH further regulate the crystallinity of newly formed REE-bearing secondary phase. Extending this investigation to biologically mediated mobilization, experiments with Aspergillus niger and natural REE-bearing mineral sands suggest that initial pH act as a signaling cue shaping subsequent metabolic response and leaching trajectories. These findings suggest that cultivation conditions could be used to guide microbial metabolism and regulate the balance between REE dissolution and precipitation.

Together, this work advances the mechanistic understanding of REE speciation, mobility, redistribution, and secondary-phase formation in weathering systems and provides a basis for tuning bioleaching systems to achieve desired extraction outcomes.

Committee members: Dr. Yuanzhi Tang (Advisor), Dr. Martial Taillefert, Dr. Jennifer B. Glass, Dr. Christopher T. Reinhard, and Dr. Brian L. Phillips

Date & Time: Friday November 13th, 2:00 pm 

Location: ES&T L1114

Abstract:

Reliable geological carbon storage requires estimates of subsurface CO₂ saturation and pressure despite incomplete observations and uncertain reservoir properties. This dissertation develops uncertainty-aware Digital Shadows and Digital Twins that combine physics-based simulation with amortized Bayesian inference for monitoring evolving reservoir states.

The proposed framework uses ensembles propagated through multiphase flow, rock physics, seismic modeling, and imaging to train conditional normalizing flows that generate posterior samples from time-lapse seismic and well observations. The dissertation examines three extensions of this framework: multimodal monitoring, robustness to uncertain rock physics, and context-aware inference. Rock-physics augmentation improves reconstruction under tested model mismatch, while a three-phase extension enables joint estimation of oil and CO₂ saturation. A sensitivity-aware Digital Twin treats rock-physics assumptions as explicit context, supporting assumption-specific inference and what-if analysis. Finally, a collaborative case study demonstrates how probabilistic Digital Shadow estimates can be supplied to a separately developed injection-control workflow. Together, these studies provide a simulation-based framework for uncertainty-aware subsurface monitoring and decision support.

Defense date: November 6, 2026

Defense time: 10:30 am - 01:30 pm EST

Defense location: ES&T L1114

Advisor (Chair):

Felix Herrmann, Professor, Georgia Institute of Technology

Committee members:

Andrew Newman, Professor, Georgia Institute of Technology

Zhigang Peng, Professor, Georgia Institute of Technology

Sheng Dai, Professor, Georgia Institute of Technology

Olav Moyner, Senior Research Scientist, SINTEF, Norway

Wenhao Qin

Advisor:  Dr. Shiladitya Banerjee, School of Physics, Georgia Institute of Technology

Boundary Manifestations of Higher Berry Phases
Friday, November 6, 2026

10:00 a.m.      

Howey W401

Virtual: Wenhao Qin Thesis Proposal 

Committee Members:

Dr. JC Gumbart, School of Physics, Georgia Institute of Technology

Dr. Zeb Rocklin, School of Physics, Georgia Institute of Technology

Dr. Minsu Kim, Department of Physics, Emory University

As artificial intelligence becomes increasingly capable of conversation, companionship, and emotional responsiveness, what happens to our understanding of human connection? Unpack AI, empathy, intimacy, and relationships while considering what it means to form meaningful connections in an increasingly AI-mediated world.

Co-sponsored by the Michael E. Tennenbaum Family Institute for Technology and Civic Leadership.

What does creativity mean when machines can generate images, music, writing, and other forms of creative work? Explore how artificial intelligence is reshaping creative industries, changing the relationship between technology and human expression, and raising new questions around authorship, originality, labor, and the future of creative work.

Co-sponsored by the Michael E. Tennenbaum Family Institute for Technology and Civic Leadership.

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.

Co-sponsored by the Michael E. Tennenbaum Family Institute for Technology and Civic Leadership.

Panelists

Sebastian Porsdam Mann, Assistant Professor, CeBIL, University of Copenhagen

Sebastian Porsdam Mann is an 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. 

Chad Pasha, Education at OpenAI

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, 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. 

Join us for the final virtual artist talk of the Craft of Paper: Contemporary Takes on Tradition exhibition. We'll be closing the series with presentations from Sara Rayo, lucha rodríguez, and Claude-Gerard Jean.

About the Exhibit: 

Curated by paper artist Michael Velliquette, The Craft of Paper: Contemporary Takes on Tradition explores modern interpretations of paper crafts, including cutting, folding, rolling, weaving, and layering. This exhibition aims to establish a unified language of paper craft techniques, while highlighting how contemporary artists are adapting these methods in innovative ways. It underscores the tools and techniques that have contributed to the recent resurgence of paper crafts, such as the development of high-quality, commercially available paper stocks. Central themes include the evolution of paper as an artistic medium, the fusion of traditional and modern techniques, and the diverse applications of paper in both art and design.

How to Register for this event:

Register here for workshop. Please email anna.doll@rbi.gatech.edu for questions or more information.

Weaving a Web is the fourth in a series of five talks featuring artists on view in The Craft of Paper: Contemporary Takes on Tradition exhibit at the Robert C. Williams Museum of Papermaking.

In this virtual talk, we will be hearing from exhibiting artists, rhiannon skye tafoya and Julie VonDerVellen, both working the tradition of weaving into their paper art.

About the Exhibit: 

Curated by paper artist Michael Velliquette, The Craft of Paper: Contemporary Takes on Tradition explores modern interpretations of paper crafts, including cutting, folding, rolling, weaving, and layering. This exhibition aims to establish a unified language of paper craft techniques, while highlighting how contemporary artists are adapting these methods in innovative ways. It underscores the tools and techniques that have contributed to the recent resurgence of paper crafts, such as the development of high-quality, commercially available paper stocks. Central themes include the evolution of paper as an artistic medium, the fusion of traditional and modern techniques, and the diverse applications of paper in both art and design.

How to Register for this event:

Register here for workshop. Please email anna.doll@rbi.gatech.edu for questions or more information.

Mathematics is being transformed by the combination of AI, formal methods, and computer algebra (AI+FM+CA). The Center aims to catalyze and reorient this work at Georgia Tech and tighten its connections to mathematics by securing public and private funding, arranging compute resources, supporting team building, and organizing seminars, workshops, and tutorials. We also hope to openly discuss the AI-driven transformation of mathematical research, including concerns about the diverging value systems of academia and the companies working on AI for math.

The town hall is held as part of the AI for the Working Mathematician lunch discussion group, which meets on select Thursdays, 11:30am to 12:30pm in Skiles 006.

Bio: Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania, where he holds secondary appointments in Psychology, Bioengineering, Genomics and Computational Biology, and Operations, Information and Decisions. His group builds chatbots and language analysis tools for psychological and medical research.  They study the drivers of physical and mental well-being and their cultural variation, and develop socially sensitive AI-based tutors and coaches.

For CODA guest access, please contact shatcher8@gatech.eduat least 2 business days prior to the event.

Zoom link: https://gatech.zoom.us/j/91607375625?pwd=ybCsFPzknA8VqYZaSqvenqlWbrvyzx.1

Meeting ID: 916 0737 5625
Passcode: 038828

Join Justin Burns, PhD, Chief Innovation Officer and Vice President of Innovation and Entrepreneurship, Georgia Research Alliance, from noon to 1:00 PM via Zoom. Drawing on tech transfer, venture investing, and running GRA’s commercialization funding, Burns will walk through how funders size technical, market, and regulatory risk, which milestones change a valuation, and what to stop spending on before your next raise or license.

The Bench2Market Talks series is created to provide commercialization guidance to the university research community. For more details on the series, visit our website.

Join Georgia Tech's Marilyn Brown, Valerie Thomas, and Susan Graff as they celebrate two new Springer Nature books — Energy Technology and Policy Innovation and Sustainability Leaders: A Guide to Transforming Organizations — and explore competing visions for change. Drawing on research and real-world experience, this lively conversation will challenge assumptions, examine trade-offs, and ask who should lead, who should pay, and how to turn promising ideas into lasting progress.

About the Books

Whether you're looking to make new friends, explore student organizations, learn about MSA, or simply take a break and have a conversation, everyone is welcome. Stop by, say hello, grab a treat, and connect with us! Students are also welcome to join our community chats to stay informed about upcoming events, service opportunities, and ways to get involved.

Our goal is to foster a more welcoming, inclusive, and connected campus where students from all backgrounds feel comfortable building relationships, finding community, and getting involved.

All Georgia Tech students are welcome. Come as you are, bring a friend, and leave with a new connection!

Important information:

1. Bring a black and white image file on your computer. If you can, pick an image that doesn't have too many closed loops (unless you want the whole shape cut out)

2. Wear closed toe shoes for safety! You will not be able to participate if you aren't wearing safe attire!

3. Come to the entrance to the metal room inside the Invention Studio hub. If the building is closed, wait at the main entrance (which shares a courtyard with the Love Building and GTMI) and your host will come get you.

Help EMSaT keep our CPR-athon going!!! 

Free food will be provided (usually pizza).

Open to all students!

You will get to try 茶道 (Sadou) firsthand using real bamboo whisks and traditional bowls to make your own matcha. We will also have plenty of Japanese tea snacks for everyone to enjoy!

No prior experience with tea etiquette is needed. Just come by, make some tea, and meet new people!

Event Details

• When: November 13, 5:00 PM - 7:00 PM
  
   
• Where: George/Scheller Tower 232

We have also created a Mini Murph option for less experienced athletes!

The full muprh:

- 1 mile run

- 100 pullups

- 200 pushups

- 300 squats

- and another mile. 

The Mini Murph:

- 2/3 mile run

- 100 rows

- 200 knee pushups

- 300 squats

- another 2/3 mile

Committee Members:

Dr. David Myers (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Dr. Tara Deans (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Dr. Todd Sulchek (George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Dr. Ovijit Chaudhuri (Department of Mechanical Engineering, Stanford University)

Dynamics of Blood Clot Viscoelasticity Mediates Clot Maturation via Platelet Mechanotransduction

Clot formation is an essential step in hemostasis and needs to be precisely regulated. Dysfunctional clot growth can manifest in different cardiovascular conditions. Excessive clotting can lead to thrombosis, while insufficient clotting can cause hemorrhagic disorders. While clot initiation has been extensively studied and well-characterized, clot cessation represents a critical gap in our understanding of the hemostatic process.  Clots represent a highly dynamic environment, rapidly transitioning from a liquid-like, viscous material to a solid-like elastic material. Platelets have been known to sense their mechanical environments, specifically substrate stiffness. I extend this reasoning to substrate viscoelasticity and hypothesize that clot viscoelasticity is a mechanical regulator of clot growth arrest. To test this, I will use tunable interpenetrating networks (IPNs) to investigate how substrate viscoelasticity regulates platelet activation at the molecular level, and how physiological shear stresses interact with clot mechanics to govern clot cessation. Aim 1 will establish physiological viscoelastic relevance of the IPNs by comparing their viscoelastic properties of the IPNs to whole blood clots and contrived spatial clot models. Aim 2 will be to investigate platelet response to viscoelastic microenvironments in both 2D and 3D environments and elucidate the molecular mechanisms that govern platelet activation through integrin-driven signaling pathways. Aim 3 will extend these findings to physiological flow conditions using microfluidic platforms, determining the synergistic effect of hemodynamic shear and clot viscoelasticity on platelet mechanotransduction. These studies will uncover viscoelastic mechanosensing as a previously unrecognized regulator of clot cessation, generating a new mechanobiological perspective for understanding hemostasis and thrombosis with direct implications for the development of precision therapies for both thrombotic and hemorrhagic disorders.

Grace Barkhuff

Ph.D. Student in Human-Centered Computing 

School of Interactive Computing 

Georgia Institute of Technology 

Date: November 13, 2026

Time:  3pm - 5pm ET

Location:  TSRB 233

Committee 

Dr. Ellen Zegura (Advisor) - School of Interactive Computing and School of Computer Science, Georgia Institute of  Technology
Dr. Rodrigo Borela - School of Computing Instruction, Georgia Institute of Technology

Dr. Betsy DiSalvo - School of Interactive Computing, Georgia Institute of Technology

Dr. Carl DiSalvo - School of Interactive Computing, Georgia Institute of Technology

Dr. Casey Fiesler - Department of Information Science, University of Colorado Boulder

Abstract 

The technology industry develops pervasive, ubiquitous tools that impact both society broadly and our personal, daily lives. From social media's influence on elections to generative AI for emotional support, computing technologies and those who develop them have a profound impact on how we live. As a result, calls abound for new computing technologies to be developed "ethically" and "responsibly." For the past fifty years, academia's efforts in this realm have focused on computing ethics education, a subject within computing that teaches students to consider the societal impacts of the tools they design. Because this education is critical, we must pause to evaluate the state of our ethics education and its effectiveness and imagine how we might improve it. In this thesis proposal, I provide an overview of the current state of ethics education in the United States, including an analysis of educational materials that meet ethics learning outcomes, educators' perceptions of ethics instruction, prevalence of required ethics instruction in computing programs, and students' approach to ethics when designing new technologies. I reflect on what it might mean for instructors to model ethical engagement with technology in their own classrooms, then propose work related to using ethics education to help students develop an understanding of how their values connect to their careers in computing.

Meeting Details  

  https://gatech.zoom.us/j/4265896666?pwd=bW10czF5UGVJcTNzWEFQa0NYem1TZz09

Advisor: Dr. Dimitri Mavris

Milestone: PhD Thesis Final Examination (Defense)

Degree Program: Aerospace Engineering

Title: A Scalable and Efficient Framework for Graph-Based Analysis of the Digital Thread

Abstract: The increasingly connected and rapidly evolving aerospace operational environment, coupled with tight budgets and aggressive timelines, poses significant challenges to the current document-centric analytical paradigm. Addressing these challenges requires Digital Transformation and the application of Digital Engineering principles, with the Digital Thread serving as a key enabler. However, the Digital Thread’s scale and complexity can limit the efficiency of advanced analytics. Digital Thread graphs can support these analyses through graph representation learning, particularly Graph Neural Networks (GNNs). Processing entire graphs introduces scalability challenges, while partitioning them into smaller isolated subgraphs restricts information flow. Furthermore, learning representations for prediction does not, by itself, provide an effective strategy for design-space exploration. This thesis addresses these challenges through hybrid graph representations and gradient-based exploration of regression embeddings. Hybrid graphs preserve detailed local information while incorporating aggregated global context from external partitions. Embedding space exploration searches learned representations and decodes them into admissible input states. The AC Optimal Power Flow (AC-OPF) problem in electricity transmission serves as the primary proxy for Digital Thread analytics. The methods are also applied to flight delay prediction and schedule optimization to assess whether the observed trends hold in a different application domain. Across both applications, hybrid graphs recover predictive accuracy lost through isolation while reducing peak memory requirements relative to processing entire graphs. This follows the expected balance between information retention and computational efficiency. Training time benefits are more conditional: additional training batches limit savings in the electricity transmission experiments, whereas hybrid models reduce training time in the flight delay demonstration without subsampling. Embedding space exploration also reduces search time and memory compared with optimizing the original system inputs directly. The improvement achieved in the learned representation must be translated/decoded back into feasible changes to the engineering system. Decoding preserves a substantial portion of the improvement obtained through direct input optimization in the electricity transmission experiments, with a greater loss of improvement in the flight schedule application. These findings show the potential and limitations of hybrid graphs and learned representations for computationally efficient graph-based analysis and optimization of engineered systems, providing a foundation for their application to Digital Thread graphs.

Date and time: 2026-11-16, 8:30 AM

Location: Collaborative Visual Environment (CoVE); Weber Space Science and Technology Building (SSTIII)

Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Dr. Kyriakos G. Vamvoudakis, School of Aerospace Engineering
Dr. Kai A. James, School of Aerospace Engineering
Dr. Woong Je Sung, School of Aerospace Engineering
Dr. Arun Ramamurthy, Siemens Technology (Princeton

• Dr. Pengfei Liu - Associate Professor, School of Earth & Atmospheric Sciences at Georgia Tech, studying air pollution, wildfire smoke, and their effects on climate and human health.
• Dr. Katherine Graham - Assistant Professor, School of Civil & Environmental Engineering at Georgia Tech, researching water, climate, and health, including how pathogens spread through water systems.
• Dr. Jenny McGuire - Associate Professor, School of Earth & Atmospheric Sciences at Georgia Tech, studying how climate change reshapes biodiversity and how species and ecosystems adapt.

Register Online to attend via Microsoft Teams

Committee: 

Dr. Zonouz, Advisor       

Dr. Mertoguno, Chair

Dr. Chou

Committee: 

Dr. Inan, Advisor  

Dr. Aghazadeh, Chair

Dr. Shah

Committee: 

Dr. Krishna, Advisor      

Dr. Mahajan, Chair

Dr. Hao

Dr. Huang

Dr. Wang

Committee: 

Dr. Yu, Advisor    

Dr. Lin, Chair

Dr. Mukhopadhyay

Doctor of Philosophy in Applied Physiology

In the

School of Biological Sciences

Joelle Dick

Will defend her dissertation

MANAGING REDUNDANCY FOR STABLE TASK PERFORMANCE UNDER CONSTRAINTS

Friday, November 6th, 2026

12:00 PM

Applied Physiology Building (555 14th St.), Room 1253

Teams

 Thesis Advisor:

Young-Hui Chang, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

Committee Members:

Lewis Wheaton, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

Boris Prilutsky, Ph.D.

School of Biological Sciences

Georgia Institute of Technology

Greg Sawicki, Ph.D.

Schools of Mechanical Engineering and Biological Sciences

Georgia Institute of Technology

Colin Grove, Ph.D.

Department of Rehabilitation Medicine

Emory University School of Medicine

ABSTRACT:

Human movement requires the nervous system to use motor and sensory redundancy to maintain stability and achieve task-specific goals. This redundancy provides flexibility to adapt movement strategies in response to changing internal, mechanical, and environmental constraints. Understanding how the nervous system uses this flexibility to maintain task performance is essential for understanding motor coordination and adaptation.

This dissertation investigates how the nervous system organizes movement variability and joint coordination in response to three distinct constraints: neuromuscular fatigue, increasing running speed, and altered gravity. Using uncontrolled manifold analysis and system identification techniques, three studies examine how changing task demands influence joint-level coordination and the stabilization of task-relevant variables.

The first study investigated running speed in non-amputees and unilateral transtibial amputee sprinters, showing that runners without a prosthesis shift from interjoint toward individual joint coordination at higher speeds, whereas runners with a prosthesis relied more on interjoint covariation. The second study examined lower-limb coordination during repetitive squatting revealing that  kinematic coordination remained relatively consistent as fatigue progressed.  The third study examined postural control following simulated hypogravity adaptation, revealing a significant reduction in whole-body center of mass sway without significant changes in joint moment variability or relative ankle-to-hip contributions.

Together, these findings suggest that the nervous system responds to changing physiological, mechanical, and environmental constraints by adjusting movement coordination and control. This dissertation highlights the importance of interpreting movement variability in relation to task-specific goals and provides insight into how the human motor system uses redundancy and flexible coordination strategies to maintain performance across diverse conditions.

(Advisor: Prof. Vladimir V. Tsukruk)

will defend a doctoral thesis entitled,

Ionic and Interfacial Assembly of Inorganic–Organic Hybrid Nanomaterials with Chiral and Magnetic Functions

on

Tuesday, November 10, 2026,

at

11:00 a.m.–1:00 p.m.

in

Molecular Science and Engineering Building (MoSE) Room 1226

Abstract

Inorganic–organic hybrid nanomaterials with chiral and magnetic functions are promising for chiral photonics and enantioselective sensing, as well as for magnetically recoverable adsorbents and catalysts, because they combine the robustness of an inorganic component with the chemical tailorability of an organic one. However, these functions are usually installed through covalent synthesis or in organic solvents, and the resulting nanoscale building blocks are often fragile or metastable. How aqueous, non-covalent processing relates to the nanoscale structure and functional properties of these hybrids remains largely unexplored.

This work examines ionic pairing and interfacial coordination in water as processing routes to chiral and magnetic hybrid nanomaterials, and relates the resulting nanoscale structures to the chiroptical and magnetic functions of the hybrids. First, sulfonated polyhedral oligomeric silsesquioxane (POSS) nanocages were paired ionically with the amino acid L-tryptophan. The amino acid keeps its chirality on the rigid inorganic cage, while the cage makes the hybrid more robust and directs its assembly into ordered nanostructures. Second, a one-pot aqueous synthesis was developed in which solution basicity switches the shape of the layered zeolitic imidazolate framework ZIF-L, and magnetic nanoparticles attached to the ZIF-L surfaces add magnetic response and protect the metastable layered phase. Third, preliminary results combine the two approaches: magnetic nanoparticles leave the chirality of an ionic POSS–amino acid hybrid unchanged in solution and add in-plane order to its films, and POSS–nanoparticle hybrids can be organized by a magnetic field.

Together, these results identify the mobile ionic counterion and the nanoparticle surface as general design handles for functional hybrid materials made in water. This work provides a basis for the design of robust, water-processable chiral and magnetic nanomaterials, from chiral optical films to recoverable materials for water treatment.

Committee Members:

Prof. Vladimir V. Tsukruk (Advisor) – School of Materials Science and Engineering

Prof. Blair Brettmann – School of Chemical and Biomolecular Engineering

Prof. Scott Danielsen – School of Materials Science and Engineering

Prof. Shucong Li – School of Materials Science and Engineering

Prof. Todd Sulchek – George W. Woodruff School of Mechanical Engineering

Dr. Dhriti Nepal – Air Force Research Laboratory

(Advisor: Prof. Vladimir Tsukruk)

will defend a doctoral thesis entitled,

Engineered Nanoscale Interfaces for 
Electrophysiological and Electrochemical Sensing

On

Thursday, November 12, 2026 at 9:00 a.m.

Krone Engineered biosystems building (EBB) 3029 Conference Room
and/or virtually via MS Teams

Abstract

The signal quality of a sensing device is largely determined at the interface between the device and its target, a region typically less than a few hundred nm thick. In wearable electrophysiology, this interface must maintain contact with skin that deforms and perspires, whereas in trace-level chemical sensing it must discriminate analytes with few reactive functional groups. In both cases, the thickness and surface chemistry of the interface are usually dictated by the choice of material. This reserach presents two nanoscale interface platforms in which both parameters are defined at the design stage.

The first platform is an ultrathin skin-conformal nano-electrode composed of Ti3C2Tx MXene (50 nm), poly-L-lysine, and parylene (≈300 nm), with the parylene thickness determined from a work-of-adhesion analysis of contact with skin texture. The hydrophilic MXene side and hydrophobic parylene side allow the film to be transferred onto skin by water-assisted capillary flow and to remain attached without gel or adhesive. Compared with commercial gel electrodes, the nano-electrode showed approximately 35% lower skin interfacial impedance and up to threefold higher signal-to-noise ratio in ECG and EMG. ECG was recorded in a sauna and a swimming pool, where gel electrodes detached within minutes, and stable recording was maintained over 30 h of continuous wear.

The second platform is an extended-gate field-effect transistor (EGFET) for tertiary amines of the tryptamine family, with gramine as a structural surrogate for N,N‑dimethyltryptamine (DMT). Since these molecules have no N–H bond and no useful redox activity, selectivity was introduced through chemical activation. Sequential N‑oxidation and Polonovski rearrangement convert the tertiary amine into an amide, which is covalently bound to an amino-terminated self-assembled monolayer on the gold gate by transamidation, and the resulting surface-potential change is read by a commercial MOSFET. The sensor exhibited a limit of detection of 7 nM over four orders of magnitude. In artificial saliva, gramine was still activated in the presence of thiocyanate and urea, and the extraction step of the Polonovski reaction separated the amide from the matrix before surface coupling.

In both platforms, a function normally supplied by an added layer was instead built into the interface itself by controlling its thickness and surface chemistry: water tolerance at the electrode and molecular selectivity at the gate.

Committee

• Prof. Vladimir Tsukruk – School of Materials Science and Engineering (advisor)
• Prof. Eric Vogel – School of Materials Science and Engineering
• Prof. Shucong Li – School of Materials Science and Engineering
• Prof. Peter Hesketh – School of Mechanical Engineering
• Prof. Todd Sulchek – School of Mechanical Engineering

_______________________________________________________________

This event is a part of International Education Week (IEW) 2026, occurring November 2-November 5. Celebrate global learning, cultural exchange, and international collaboration and come join the fun!

BioE PhD Proposal Presentation

11:00 am, Friday, November 13th, 2026

Location: Whittaker 1103

Zoom Link: https://gatech.zoom.us/j/93160060109?pwd=bE94BQ44D5XKOHXVYgQ7UazBPpF4u0.1

Advisor: Dr. Wilbur Lam (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Committee Members:

Dr. David Myers (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Dr. Tara Deans (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Dr. Todd Sulchek (George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Dr. Ovijit Chaudhuri (Department of Mechanical Engineering, Stanford University)

Dynamics of Blood Clot Viscoelasticity Mediates Clot Maturation via Platelet Mechanotransduction

Clot formation is an essential step in hemostasis and needs to be precisely regulated. Dysfunctional clot growth can manifest in different cardiovascular conditions. Excessive clotting can lead to thrombosis, while insufficient clotting can cause hemorrhagic disorders. While clot initiation has been extensively studied and well-characterized, clot cessation represents a critical gap in our understanding of the hemostatic process.  Clots represent a highly dynamic environment, rapidly transitioning from a liquid-like, viscous material to a solid-like elastic material. Platelets have been known to sense their mechanical environments, specifically substrate stiffness. I extend this reasoning to substrate viscoelasticity and hypothesize that clot viscoelasticity is a mechanical regulator of clot growth arrest. To test this, I will use tunable interpenetrating networks (IPNs) to investigate how substrate viscoelasticity regulates platelet activation at the molecular level, and how physiological shear stresses interact with clot mechanics to govern clot cessation. Aim 1 will establish physiological viscoelastic relevance of the IPNs by comparing their viscoelastic properties of the IPNs to whole blood clots and contrived spatial clot models. Aim 2 will be to investigate platelet response to viscoelastic microenvironments in both 2D and 3D environments and elucidate the molecular mechanisms that govern platelet activation through integrin-driven signaling pathways. Aim 3 will extend these findings to physiological flow conditions using microfluidic platforms, determining the synergistic effect of hemodynamic shear and clot viscoelasticity on platelet mechanotransduction. These studies will uncover viscoelastic mechanosensing as a previously unrecognized regulator of clot cessation, generating a new mechanobiological perspective for understanding hemostasis and thrombosis with direct implications for the development of precision therapies for both thrombotic and hemorrhagic disorders.

Advisors: Josh Kacher and Aaron Stebner

will defend a doctoral thesis entitled,

Influence of Heterogeneous Particulate Reinforcements on Deformation and Damage in Aluminum Composites Formed by Reactive Additive Manufacturing

On

Thursday, November 12, 2026

12 pm – 2 pm

-------------

or virtually via Teams:

Join: https://teams.microsoft.com/meet/248266455555984?p=93WUJ1utqZm4Pd8eD9

Meeting ID: 248 266 455 555 984

                                                                                            Passcode: zZ9Kw7aL

Committee:

Prof. Josh Kacher - School of Materials Science and Engineering (advisor)

Prof. Aaron Stebner - School of Materials Science and Engineering (co-advisor)

Prof. Naresh Thadhani - School of Materials Science and Engineering

Prof. Richard Neu - Woodruff School of Mechanical Engineering

Prof. Ashley Spear - Department of Mechanical Engineering, University of Utah

Abstract

   Laser powder bed fusion (PBF-LB) enables the fabrication of complex parts, but aluminum alloys manufactured through this process remain susceptible to solidification cracking and anisotropic mechanical properties associated with columnar grain growth. Reactive additive manufacturing (RAM) is a method of promoting grain refinement and introducing reinforcement particles through in situ chemical reactions between reactive powder constituents during processing. However, incomplete reactions contribute to heterogeneous microstructures containing variations in particle size, shape, composition, and spatial distribution, which can influence deformation and fracture behavior. Understanding these effects is important for identifying potential damage initiation mechanisms and their effect on tensile properties. In this work, I investigated the relationships between heterogeneous reinforcement particles, deformation and fracture, and mechanical properties in Al-Ti-B₄C composites formed through RAM.

First, in situ scanning electron microscopy (SEM) tensile testing was coupled with digital image correlation (DIC) to analyze local strain distributions as they relate to the reinforcement particles over different volume fractions. Machine learning approaches were then employed to quantify the relative importance of particle geometry and composition in predicting particle crack initiation and propagation under uniaxial tension. Finally, the laser-material interaction time during PBF-LB was progressively increased to study the influence of increasing thermal exposure on the progression of the in situ chemical reactions, porosity, and subsequent tensile properties. These studies provide a foundation for the microstructural considerations necessary in developing PBF-LB processing strategies that balance the benefits of in situ reinforcement particle formation against the introduction of features which may compromise tensile performance.

RSVP via Jacket Journey under the "Activities" tab. 

RSVP via Jacket Journey under the "Activities" tab. 

RSVP via Jacket Journey under the "Activities" tab. 

RSVP via Jacket Journey here. 

Registration requested.

Told almost entirely through still photographs, Chris Marker’s La Jetée (1962) is a haunting 28-minute journey through time, memory, and a world after catastrophe. More than sixty years later, it still shapes how filmmakers imagine the future. Four scholars will look at Marker’s short film from several angles: experimental and science-fictional modes of filmmaking, the relationship between cinema and the photographic image, and the ways the creative arts can take up science-fiction storytelling. The panel ends with an open Q&A, so bring your questions.

Featuring:

• Stéphanie Boulard, Professor of French Literature and Visual Arts
• Kristi McKim, Associate Professor of Film
• Ida Yoshinaga, Assistant Professor of Film

3:15 – 4:15 p.m. | Creative Art Workshop

Now it’s your turn to create. Inspired by Marker’s work, this hands-on workshop invites you to explore artistic expression, collaboration, and the creative process. Whether your interest is film, photography, or simply creative thinking, you’ll leave with new ways of seeing and making.

Featuring:

• Jillann Hertel, Creative Director and Faculty
• Rachel Parish, AECT

Refreshments will be served.

Organized by the Center of Excellence for French and Francophone Studies. Sponsored by the School of Modern Languages and the School of Literature, Media, and Communication. 

Himadri S. Pandey
Machine Learning PhD Candidate
H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology

Committee

1. Dr. Gian-Gabriel P. Garcia (Advisor), Industrial and Systems Engineering, University of Washington
2. Dr. Jing Li, Industrial and Systems Engineering, Georgia Institute of Technology
3. Dr. Lauren N. Steimle, Industrial and Systems Engineering, Georgia Institute of Technology
4. Dr. Kai Wang, Computational Science and Engineering, Georgia Institute of Technology
5. Dr. Landon Lempke, School of Medicine, Virginia Commonwealth University

Abstract

Machine learning has shown great promise for improving healthcare through more accurate diagnosis, risk prediction, and personalized care. However, accurate predictions alone do not guarantee better decisions. In practice, healthcare providers must make decisions with limited time, staffing, and resources. Yet these constraints are often overlooked during model development. This dissertation investigates how optimization can be integrated into machine learning to develop decision-making tools that explicitly account for these operational constraints. It addresses three interconnected questions: When is individualized information worth collecting? What information should we prioritize when resources are limited? And who should receive scarce interventions, and when?

The first part of this dissertation examines the value of information in clinical decision-making, developing a framework to quantify how individualized baseline testing changes diagnostic decisions in sports-related concussion assessment. The second part develops an operationally constrained machine learning framework that jointly selects diagnostic assessments and trains interpretable prediction models while accounting for uncertain administration times, clinical knowledge, and operational requirements. The third part introduces a mixed-integer optimization framework for ranked feature selection that optimizes feature rankings simultaneously across multiple resource budgets, accounting for feature acquisition costs and the predictive value of each successive feature set. The final part addresses the dynamic allocation of scarce healthcare resources among pediatric patients whose clinical conditions evolve over time. It proposes a multi-action restless multi-armed bandit framework and a decision-focused learning approach that combines neural networks and long-run resource planning to coordinate clinical interventions under resource constraints.

Together, these contributions advance a shift in healthcare AI from “What can we predict?” to “What actions should we take and for whom, given the resources available?”

School of Psychological and Brain Sciences

Ph.D. Dissertation Defense Meeting

Time: Monday November 9th, 2026 9am Eastern Time

Location: Room 150 or https://gatech.zoom.us/j/94024313801

Dissertation Committee Chair/Advisor:

Dr. Scott Moffat (Georgia Tech)

Dissertation Committee Members:

Dr. Robert Ariel – (Virginia Wesleyan University, Department of Psychology)

Dr. Thackery Brown – (Georgia Tech)

Dr. Paul Verhaeghen – (Georgia Tech)

Dr. Steven Weisberg – (University of Texas at Arlington, Department of Psychology)

Title: Individual Differences in Navigation Performance and Metacognitive Monitoring:

The Role of Confidence in Route Learning

Abstract:

Learning an environment requires both knowledge of spatial relationships and an ability to judge when that knowledge is reliable. Confidence may also influence the strategies navigators use both when learning an environment and retrieving spatial information. Seventy-one mainly younger adults learned landmarks on two routes in immersive virtual reality. They then made 56 directional pointing judgments, each accompanied by a chosen continuous angular area intended to contain the correct direction with 90% confidence. Based on pointing performance, participants were classified as integrators (accurate within and between routes), non-integrators (accurate within routes but inaccurate between routes), or imprecise navigators (inaccurate on both). They also completed baseline measures and a three-arm Y-maze to assess allocentric versus egocentric strategy preference. Pointing errors and confidence intervals were wider for between-route judgments. Absolute calibration gaps were larger between routes, with non-integrators resembling integrators within routes but imprecise navigators between routes. Relative monitoring was also substantially weaker between routes: a 10° increase in confidence half-width was associated with a 12.9% increase in pointing error within routes, compared with only 1.4% between routes. Integrators reported a better general sense of direction than imprecise navigators. Interestingly, non-integrators performed relatively well on mental rotation and reported comparatively strong spatial ability, yet rated their general sense of direction more poorly than integrators. These findings suggest that confidence reflected the greater demands of between-route judgments but provided less information about the accuracy of individual responses. Non-integrators' relatively strong spatial abilities and within-route performance suggest that their difficulties with route integration may reflect how spatial knowledge is constructed or applied, rather than a general limitation in spatial ability. Testing whether confidence influences strategy selection, rather than simply reflecting performance, could help explain why some navigators with otherwise adequate spatial abilities seem to struggle to integrate routes into a survey representation of the environment.

Advisor: Dr. Lakshmi Sankar

Milestone: PhD Thesis Final Examination (Defense)

Degree Program: Aerospace Engineering

Title: Roughness Tolerant Airfoil Design for Rotor and Propeller Applications

Abstract: An inverse design methodology for airfoil was used to design roughness tolerant airfoil for subsonic applications in propeller and helicopter rotor. Methodologies for designing airfoils were first validated with known airfoils such as the NACA airfoils, and were subsequently used for designing a family of airfoils with various thickness to chord ratios from 10% to 22% for UAV propeller and helicopter main rotor improvement applications. While designing the roughness tolerant airfoils, pressure distribution shape on the airfoils was chosen so that the adverse pressure gradient was delayed as far back on the airfoil on the upper surface as possible to delay boundary layer transition and reduce boundary layer thickness. Drag polars of smooth and rough airfoils between designed and baseline airfoils were compared and shown better drag buckets for a range of useable lift coefficients prior to propeller and rotor applications. Icing simulation was also completed to demonstrate lower ice accumulation (a natural roughness phenomenon) for the newly designed airfoils. In-house blade element-momentum and CFD tools were used to analyze propeller and helicopter rotor performance in 3D applications. The current inverse design methodology was able to successfully demonstrate a few possible applications where the airfoils are more roughness tolerant than nominal airfoils. Applications that used designed airfoils showed slightly better performance at higher thrust and lift conditions compared to nominal propeller or helicopter rotor applications. An undesirable higher nose down pitching moment was introduced with the new airfoil design due to aft shifting of loads to delay transition and reduce drag. It was observed that the new airfoils are tolerant to lower surface roughness only. Upper surface roughness tolerance still requires more investigation.

Date and time: 2026-11-30, 10am-12pm

Location: MK317

Committee:
Dr. Lakshmi Sankar (advisor), School of Aerospace Engineering
Dr. Brian German, School of Aerospace Engineering
Dr. Suhas Jain, School of Mechanical Engineering
Dr. Graeme Kennedy, School of Aerospace Engineering
Dr. Juergen Rauleder, School of Aerospace Engineering

 

Advisor: Dr. Keegan Moore

Milestone: MS Thesis Proposal

Degree Program: Aerospace Engineering

Title: A Physics-Enforced Dual-Phase Framework for Dynamics Identification in Forced Nonlinear Systems

Abstract: System identification is critical to many engineering applications, especially those involving vibrating structures. The Energy-based Dual-phase Dynamics Identification (EDDI) method is a data-driven technique that discovers equations of motion from measured responses in compliance with physical balance laws. This work expands the original EDDI method to the identification of nonlinear single-degree-of-freedom (SDOF) oscillators under external forcing. The major innovation presented here is the reformulation of EDDI to incorporate external forces into the identification process. The method is deployed in two phases to systematically extract mathematical models for the damping and stiffness of the structure. At its core, EDDI leverages conservation of energy and Newton’s second law to express the measured data in a form that allows identification of the underlying dynamics. Phase I estimates the energy dissipated by damping using conservation of energy, and then uses that estimate to identify a mathematical model for the damping. Phase II applies Newton’s second law to isolate the conservative force directly, which is then used to identify a mathematical model for the stiffness of the structure. The method is first demonstrated using a numerically simulated Duffing oscillator with known parameters to test the effectiveness of the proposed method. It is then applied to experimentally measured responses of a nonlinear oscillator with unknown stiffness and damping parameters, excited by a nonlinear external force through a magnetic stinger and a modal shaker. EDDI requires only the measured response, the external force, and the mass of the oscillator, and no prior information about the system dynamics is necessary 

Date and time: 2026-11-11, 9am-11am

Location: Weber 200 Conferce Room

Committee:
Dr. Keegan Moore (advisor), School of Aerospace Engineering
Dr. Graeme Kennedy, Associate Professor ,School of Aerospace Engineering
Dr. Alper Erturk, Professor, School of Mechanical Engineering
, 

 

Himadri S. Pandey
Machine Learning PhD Candidate
H. Milton Stewart School of Industrial and Systems Engineering
Georgia Institute of Technology

Committee

1. Dr. Gian-Gabriel P. Garcia (Advisor), Industrial and Systems Engineering, University of Washington
2. Dr. Jing Li, Industrial and Systems Engineering, Georgia Institute of Technology
3. Dr. Lauren N. Steimle, Industrial and Systems Engineering, Georgia Institute of Technology
4. Dr. Kai Wang, Computational Science and Engineering, Georgia Institute of Technology
5. Dr. Landon Lempke, School of Medicine, Virginia Commonwealth University

Abstract

Machine learning has shown great promise for improving healthcare through more accurate diagnosis, risk prediction, and personalized care. However, accurate predictions alone do not guarantee better decisions. In practice, healthcare providers must make decisions with limited time, staffing, and resources. Yet these constraints are often overlooked during model development. This dissertation investigates how optimization can be integrated into machine learning to develop decision-making tools that explicitly account for these operational constraints. It addresses three interconnected questions: When is individualized information worth collecting? What information should we prioritize when resources are limited? And who should receive scarce interventions, and when?

The first part of this dissertation examines the value of information in clinical decision-making, developing a framework to quantify how individualized baseline testing changes diagnostic decisions in sports-related concussion assessment. The second part develops an operationally constrained machine learning framework that jointly selects diagnostic assessments and trains interpretable prediction models while accounting for uncertain administration times, clinical knowledge, and operational requirements. The third part introduces a mixed-integer optimization framework for ranked feature selection that optimizes feature rankings simultaneously across multiple resource budgets, accounting for feature acquisition costs and the predictive value of each successive feature set. The final part addresses the dynamic allocation of scarce healthcare resources among pediatric patients whose clinical conditions evolve over time. It proposes a multi-action restless multi-armed bandit framework and a decision-focused learning approach that combines neural networks and long-run resource planning to coordinate clinical interventions under resource constraints.

Together, these contributions advance a shift in healthcare AI from “What can we predict?” to “What actions should we take and for whom, given the resources available?”

Only 25 spots available – submit the interest form by Nov. 10!

Related LibGuide: Data Visualization by Raven Davis

Join the Georgia Tech Library in Crosland 2130 on Thursday, Nov. 12 from 1 to 2:30 p.m. for our Introduction to R Studio workshop.

Learn the basics of navigating the R Studio development environment. By the end of the workshop, attendees will know how to read data files, work with variables, wrangle data, and create visualizations using R’s Tidyverse package. Attendees are welcome to bring their own laptops, but there will also be computers in the room.

Prior to the workshop please set up a free login on Posit.cloud here: http://posit.cloud 

Related LibGuide: Using Data by Justin Ellis

This pre-summit education session will feature a practical workshop demystifies how to ask Copilot for what you need to achieve better results. We’ll explore how to phrase questions and instructions across apps like Word, Outlook, Excel, and Teams to harness Copilot’s capabilities in your daily work. Expect interactive examples and friendly guidance to strengthen your prompt writing skills.

Learn more about the FORGE AI Summit at b.gatech.edu/FORGESummit. 

Aimed at technical participants, this pre-summit education session explains what AI agents are and how Microsoft’s Copilot Studio enables you to create custom agents that can perform specialized tasks for your team. We’ll cover how these agents work and why they’re powerful for automation and integrating enterprise data. This is the starting point for Track B’s journey toward building a working agent by the FORGE AI Summit Hackathon.

Registration Link: https://events.teams.microsoft.com/event/819952e5-418f-4de2-88ad-81667a4e0823@482198bb-ae7b-4b25-8b7a-6d7f32faa083?source=copyLinkOneEventsShareDialog

Microsoft Teams meeting: https://teams.microsoft.com/meet/2103804674439285?p=2ILGzNMGho8H2SHAcS
Meeting ID: 210 380 467 443 928 5
Passcode: em9As37v

Register for the FORGE AI Summit forgesummit.rsvpify.com. 

This pre-summit session introduces the core fundamentals of building custom agents. Microsoft will walk attendees through the Copilot Studio interface and the key components involved in agent creation (such as defining the agent’s purpose, adding topics and initial instructions, and understanding how an agent processes user input). By the end, attendees be equipped to start creating simple agents and ready to add more capabilities in subsequent sessions.

Registration Link: https://events.teams.microsoft.com/event/a544e032-fda1-4399-bab4-71e615561865@482198bb-ae7b-4b25-8b7a-6d7f32faa083?source=copyLinkOneEventsShareDialog

Microsoft Teams meeting: https://teams.microsoft.com/meet/2967363283896111?p=9zyyOpf8VBscN2acHU
Meeting ID: 296 736 328 389 611 1
Passcode: c7ff9eX6

Learn more about the FORGE AI Summit at b.gatech.edu/FORGESummit. 

Time:  2PM - 3PM ET

Virtual Link: https://teams.microsoft.com/meet/2205202324560830?p=ujaza5yWTRsOGWnxsv

Marilyn Braojos

Robotics PhD Student

School of Aerospace Engineering

Georgia Institute of Technology

Committee members

• Dr. E. Glenn Lightsey (advisor), School of Aerospace Engineering, Georgia Institute of Technology
• Dr. Yashwanth Nakka, School of Aerospace Engineering, Georgia Institute of Technology
• Dr. Sean Wilson, School of Electrical and Computer Engineering, Georgia Tech Research Institute
• Dr. Julie Wertz, Jet Propulsion Laboratory
• Dr. Kar-Ming Cheung, Jet Propulsion Laboratory

Summary:

Spacecraft rely on state estimation robust to dynamic environments for increased autonomy. This proposal presents predictive modeling frameworks that increase spacecraft awareness and resilience. The first aim of this work addresses navigation challenges from extended periods of radio communication outages. Global LSTM-based architectures were benchmarked with ARIMA architectures to model GPS satellites’ clock bias for extended 6-hour horizons at < 2 ns accuracy. The second aim of this proposal transitions to mobile vehicle uncertainty awareness from proprioceptive sensor information. To mitigate the limitations of exteroceptive sensors, this aim demonstrates an uncertainty-aware terrain classification mechanism based on an evidential deep learning architecture. Extracting accurate uncertainty from out-of-distribution sensor data provides further insight into system faults and terrain hazards. The final aim of this proposed work integrates the uncertainty-aware mechanism into an adaptive extended Kalman filter to achieve real-time state estimation in the Husky A200. This capability will be demonstrated by dynamically scaling the EKF’s measurement noise covariance matrix in ROS Gazebo as the mobile robot traverses pre-defined trajectories with varying friction characteristics to represent different terrain types. Together, these aims deliver a comprehensive framework capable of safe and reliable state estimation resilient to dynamic environments and unexpected sensor faults.

• Agilent - Life Science
• BMG LABTECH
• Corning Incorporated - Life Sciences
• Cytek BioSciences
• Cytiva
• Eppendorf
• Fisher Scientific - Research and Safety
• GenScript USA Inc.
• Hunt Optics & Imaging Inc.
• ibidi
• IKA Works Inc.
• Laxco Inc.
• MilliporeSigma - Lab Water
• MilliporeSigma - Discovery Solutions
• QIAGEN
• Quintara Biosciences - Sales
• R&D Systems - Reagent Sciences, Analytical Sciences
• Sartorius Corporation - Lab Essentials 
• Slingshot Biosciences Inc.
• Standard Biotools
• Thermo Fisher Scientific - Laboratory Consumables Products
• Thermo Fisher Scientific - Bioscience division
• Thermo Fisher Scientific - Safety Production and Lab
• USA Scientific
• VWR
  
  Registration includes:
• One six-foot exhibit table, two chairs - electricity available upon request
• Event promotion across campus and throughout Georgia Tech's bio community
• One complimentary parking pass per vendor company registration (to be used in the Area 5 Visitor Parking Deck only)
• Lunch vouchers at IBB's Bob's Café for up to two company representatives

Note

• Exhibit tables are limited, a maximum of two company representatives may attend per vendor registration
• A maximum of three exhibitor tables per company/organization will be accepted*
  • *Additional Table Availability: If exhibitor tables remain unsold two weeks prior to the event (beginning Oct. 14, 2026), any remaining tables will be released for open registration. At that time, companies that have already reached the three-table limit may register for additional exhibitor tables on a first-come, first-served basis, subject to availability.
• Proceeds support the annual operations of the Bioengineering and Bioscience Unified Graduate Students (BBUGS)

Raffle Contribution Request:
Each exhibitor is encouraged to donate a promotional item (valued under $75) for attendee drawings throughout the event. 

School of Psychological and Brain Sciences – Ph.D. Dissertation Defense Meeting

Date: Friday, November 13th, 2026

Time: 9:00 - 11:00 AM

Location: JS Coon 148 or online (https://teams.microsoft.com/meet/2176377007980978?p=agsRjcSoRb5kP54DnK)

Dissertation Committee Chair/Advisor:

Bruce Walker, Ph.D. (Georgia Tech)

Dissertation Committee Members:

Richard Catrambone, Ph.D. (Georgia Tech)

Mark Himmelstein, Ph.D. (Georgia Tech)

Eric Schumacher, Ph.D. (Georgia Tech)

Nina Dalkner, Ph.D. (Medical University Graz)

Title: Development and Validation of the Model of Acceptance of Futuristic Technologies (MAFT)

Abstract: Established models of technology acceptance (i.e., TAM, UTAUT) provide parsimonious explanations of adoption when users can evaluate technology through experience or familiar comparisons. They are less explicit about how adoption intentions form when a technology is not yet available, its operation and consequences are difficult to understand, and reliable evidence concerning performance, failure, or misuse is limited. This dissertation developed and tested the Model of Acceptance of Futuristic Technologies (MAFT) to explain early adoption intentions under these conditions of experiential and informational uncertainty. Across three studies, flying cars were used as an exemplar futuristic technology. The research program combined assessments of prior beliefs and discrete emotional responses, structural equation modeling, and pre-post simulated exposure delivered through desktop-based 360 video and immersive virtual reality. The findings indicate that prior beliefs and affective responses provided an initial interpretive framework through which perceived value, trust, and risk were evaluated. These judgments formed an affectively organized pathway associated with adoption intention, with perceived risk playing a less dominant role than originally anticipated. Although psychological distance contributed to the broader framework, the findings placed greater explanatory emphasis on affective and evaluative processes. MAFT extends technology acceptance research by explaining how people evaluate emerging technologies before meaningful experience and reliable performance evidence are available. The findings suggest that responsible communication, design, and governance should support appropriately calibrated beliefs, affective expectations, and trust by presenting realistic benefits, limitations, uncertainties, safeguards, and error modes. Such calibration may reduce both overtrust and unwarranted rejection of technological novelty.

RSVP FORM IS HERE: https://docs.google.com/forms/d/e/1FAIpQLSda2c4QixErOXe2SFVR05qMQonJ_yY_G0n37JjXc-OtvFz8cw/viewform

Our event is open to everyone, including all GT Students, Staff, and Faculty!

We are bringing together a powerhouse group of GT alumni who hail from or are currently driving innovation in the Southern Cone (South America). In this exclusive hybrid event, our virtual panelists will share their post-graduation journeys, insights into international markets, and how they leverage their GT experience to make a global impact.

Whether you're interested in working abroad, expanding your international network, or just want to hear inspiring success stories from fellow Yellow Jackets, this event is for you!

📍 Format: Join us in person on campus for the live broadcast, interactive Q&A, Chick-fil-A, and networking with fellow students! (Our alumni panelists will be joining virtually).

🌍 Who should attend? All GT students! You do not need to be from the region to attend—everyone is welcome.

🍗 FREE CHICK-FIL-A PROVIDED! (First come, first served)