Every smartphone, laptop, gaming console, and AI accelerator begins as a digital chip design. Yet one of the most important
steps in bringing that design to life remains largely invisible to most engineers and consumers. At Synopsys, engineers develop the software, algorithms, models, and simulation tools that enable both the design and manufacturing of advanced semiconductor devices. This work spans computer science, electrical engineering, physics, mathematics, high-performance computing, and advanced manufacturing, creating exciting career opportunities for students interested in solving some of the world’s most challenging technical problems.

A critical stage in a chip’s journey from concept to product is tapeout, the process between design and manufacturing. During tapeout, engineers transform a completed integrated circuit design into a set of photomasks used to print billions of transistor features onto silicon wafers. Because these features are now measured in nanometers, manufacturing introduces complex optical and physical effects that can distort the intended circuit patterns. To overcome these challenges, engineers use advanced computational lithography techniques to analyze, modify, and optimize mask patterns so the manufactured chip matches the original design intent.
This presentation will explore the fascinating technologies behind leading-edge photomask development, including pattern correction, verification, mask writing, and inspection. Attendees will learn how sophisticated software, physics-based modeling, and advanced manufacturing technologies work together to make modern semiconductor devices possible. Along the way, real-world engineering challenges that require expertise across multiple disciplines will be examined and demonstrate how innovation in computational engineering continues to drive the semiconductor industry forward.

By the end of this session, students will have a behind-the-scenes view of how a digital chip design becomes a manufacturable product and discover a hidden but highly impactful career
path at the intersection of software, physics, chip design, and semiconductor manufacturing. Whether your interests lie in computer science, electrical engineering, data science, or applied physics, tapeout engineering offers a unique opportunity to
help create the technologies that power the modern world. Manufacturing and chip design careers will also be discussed.

Bio: Larry Melvin is a Senior Director in the Product Management Group at Synopsys, where he leads development of software and models used in semiconductor manufacturing. His work focuses on predicting how microchips will be fabricated and ensuring that chip designs can be manufactured accurately and efficiently.

Throughout his career, he has worked on a variety of advanced lithography and semiconductor technologies, including extreme ultraviolet (EUV) lithography, optical proximity correction (OPC), and computational lithography. Recent projects include developing specifications for EUV photomasks, designing optical devices that account for manufacturing effects, and creating semiconductor digital twins to model the chip design and manufacturing process to an electrical analysis. Dr. Melvin received his Ph.D. from The University of Texas at Austin and his B.S. from the University of Illinois Urbana- Champaign. He also completed postdoctoral research in X-ray lithography and microelectromechanical systems (MEMS) at the University of Wisconsin-Madison. His career spans the intersection of physics, engineering, manufacturing, and software, with a focus on helping the semiconductor industry design and build increasingly complex microchips.

Agenda

09:00-09:25 Coffee and Snacks Marcus Nano Atrium  

• Attend in-person at the Petit Biotechnology Building (IBB) - Lunch provided, while supplies last
• REGISTER HERE for virtual participation link

Abstract: Time series learning has become a central problem in modern machine learning, with applications spanning science, engineering, healthcare, and finance. While much of the existing research has focused on improving forecasting accuracy, accurate prediction is only the starting point. This talk explores a broader view of time series learning, moving from forecasting toward reasoning and scientific discovery. I will first discuss our work on efficient time series forecasting, introducing cross-architecture knowledge distillation to develop lightweight models that achieve strong predictive performance with reduced computational costs. I will then explore spatio-temporal reasoning, presenting methods that integrate time series, spatial structures, and large language models to understand how events evolve and propagate across connected systems. Finally, I will discuss whether AI can move beyond prediction to discover the underlying mathematical and causal relationships governing temporal dynamics. These directions highlight the potential of time series learning to advance from accurate prediction toward deeper understanding and scientific discovery.

Bio: Wei Jin is an Assistant Professor in the Department of Computer Science and the Department of Biostatistics and Bioinformatics at Emory University. His research focuses on time series analysis and AI for health. His honors and achievements include two NIH R01 awards as principal investigator, IJCAI-ECAI Early Career Spotlights, AAAI New Faculty Highlights, KAUST Rising Stars, the INNS Doctoral Dissertation Runner-up Award, recognition for Most Influential Papers in KDD and WWW by Paper Digest, and top finishes in three NeurIPS competitions. His research has been published in Nature Portfolio journals, PNAS, and leading conferences including ICLR, KDD, ICML, and NeurIPS. He has also organized multiple tutorials and workshops at major AI conferences.

Registration closes one day prior to the workshop. Registrants will be sent the link to the virtual session by email on the morning of the workshop. If a session is no longer listed on the registration page, then it has reached capacity.

Please visit https://gatech.service-now.com/home?id=kb_article_view&sysparm_article=KB0042355 for more information and to register.

Title: Optimization in Scientific ML - is Accuracy Certification a Viable Goal?

Abstract: Generating nonlinear reduced models for parametric families of PDEs or learning associated parameter-to-solution maps often leads to minimizing a convex energy in a Hilbert space over a nonlinear hypothesis class. Hence, optimization over the budget of trainable weights, defining the hypothesis class, becomes (highly) non-convex. In this talk we discuss adaptive strategies for enhancing robustness and accuracy of optimization success, revolving around "conditional convergence guarantees". The main conceptual constituents are natural gradient flow in combination with an adaptive network expansion. Adaptation aims at increasing alignment with an ideal descent path determined by the gradient in the ambient (infinite dimensional) Hilbert space. This can be further combined with perturbed proximal point methods that can be understood as approximate implicit Euler schemes for the ideal Hilbert space gradient flow. The rationale is that each proximal point step is (much) easier to realize than the global optimization task because in each step the initial guess gets the closer to the optimum, the smaller the step-size. This adaptation to an implicit ideal Hilbert space gradient directions is of interest because the dynamical systems arising in the context of natural gradient flows are generically extremely stiff or even DAEs. Exploiting stable variational formulations of the PDE system, allows one to derive in certain relevant cases a posteriori criteria to check whether an approximate proximal step is sufficiently accurate to guarantee convergence. Roughly, network expansions are triggered when these criteria fail to be met even when the step-size reaches some lower bound. In this sense the results can be understood as "conditional convergence" with accuracy certificates. Part of the material draws on the recent paper [1].

Bio: Wolfgang Dahmen is a Research Professor in the Department of Mathematics at the University of South Carolina, where he previously held the SmartState Chair and Williams-Hedberg-Hedberg Chair. He earned his Ph.D. from RWTH Aachen and his Habilitation from the University of Bonn and has held faculty appointments at the University of Bielefeld, the Free University of Berlin, and RWTH Aachen. His research spans applied and numerical analysis, approximation theory, model order reduction, high-dimensional problems, and scientific machine learning. Dr. Dahmen is a recipient of the Gottfried Wilhelm Leibniz Prize, the Robert Piloty Prize, and the Keck Futures Initiative Award of the US National Academies. He is an elected Fellow of both SIAM and the AMS, a member of the German National Academy of Sciences Leopoldina and the North Rhine-Westphalian Academy of Sciences, and former Chair of the Foundations of Computational Mathematics (FoCM).

Title: Bridging Particle-scale Physics to Continuum Closure for Particle-laden Flows

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

BIO
H. Tom Soh is the W.M. Keck Foundation Professor of Electrical Engineering, Bioengineering and Radiology at Stanford University. He earned his B.S. with Distinction with a double major in Mechanical Engineering and Materials Science from Cornell University and Ph.D. in Electrical Engineering from Stanford University. Prior to academia, he served as a technical manager of MEMS device research group at Bell Laboratories and Agere Systems. Between 2003 and 2015, he was the Ruth Garland Professor at UC-Santa Barbara (UCSB) in the departments of Materials and Mechanical Engineering. His lab moved to Stanford in 2015. He is a recipient of numerous awards including MIT Technology Review’s “TR 100” Award, ONR Young Investigator Award, Beckman Young Investigator Award, ALA Innovator Award, NIH TR01 Award, Guggenheim Fellowship, Humboldt Fellowship, and Chan-Zuckerberg Biohub Investigatorship. He is a fellow of the American Institute for Medical and Biological Engineering (AIMBE) and member of the National Academy of Inventors (NAI).

Faculty host: Todd Sulchek

 

Learn about Conflict of Interest at Georgia Tech

Enjoy coffee and networking as you learn how to navigate the conflict of interest process at Georgia Tech.  

Hear from Terry Bridges, director for Conflict of Interest at Georgia Tech. Bridges leads efforts to identify, manage, and mitigate situations in which personal interests could compromise—or appear to compromise—professional judgment or objectivity.

In this session, you will: 

• Explore the challenges faculty entrepreneurs face when navigating conflict-of-interest requirements and commercialization processes.
• Identify opportunities to streamline processes, reduce administrative barriers, and improve the faculty experience.
• Understand how Georgia Tech balances research integrity and institutional compliance with its commitment to entrepreneurship and innovation.

There will be a Q&A session at the end of the presentation. This is a great opportunity to get all your patent questions answered. 

Bio: Dominic Kao is an Assistant Professor in the Siebel School of Computing and Data Science at the University of Illinois Urbana-Champaign, where he directs the Virtual Futures Lab. His research asks how virtual worlds shape the people who use them: how avatars and identity, feedback design, and virtual reality change motivation, performance, and learning. His lab builds its own games and VR systems and runs controlled experiments inside them, with more than 30,000 study participants to date. Before academia, he worked as a game developer at Electronic Arts. His work has been recognized with an NSF CAREER Award, a Best Paper Award from ACM Transactions on Interactive Intelligent Systems, and Honorable Mentions at CHI and CHI PLAY. He received his PhD in Computer Science from MIT.

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IPaT: GVU Lunch Lecture Series

Journey to the Georgia coast with G. Wayne Clough, CE 63, MS CE 65, HON PhD 15, President Emeritus of Georgia Institute of Technology and Secretary Emeritus of the Smithsonian Institution, and author of the new book, The Ever-Changing Georgia Coast: A Natural History of Its Creation, Transformation, and Future.

Meet us at Scheller Tower in the heart of Tech Square for a special conversation between Clough and Georgia Tech College of Sciences Dean Susan Lozier as we travel “by kayak, seaplane, and ATV to explore the rich geological history and fascinating ecology of this exceptional natural treasure” — Georgia’s Golden Coast — and understand the facets of its vibrant ecosystems through a story that is “part travelogue, part natural history, and part nature guide.”

Audience Q&A and a book-signing reception with refreshments will follow the conversation. Copies of Clough’s new book will be available for purchase and signing at the program. This event is free and open to the public. 

RSVP here to be entered into a drawing for one of 14 signed copies of the new book — one for each of Georgia’s major barrier islands. Pre-event registration is encouraged. Space is filled on a first come, first seated basis.

About the Author

G. Wayne Clough, born in South Georgia, received his Ph.D. from the University of California, Berkeley, served on the faculties of prominent research universities, and traveled the world as a geological and earthquake engineer. He served as president of the Georgia Institute of Technology from 1994 to 2008 and as secretary of the Smithsonian Institution from 2008 to 2015. He was named Conservationist of the Year in 2020 by the Satilla Riverkeeper, and his book Things New and Strange: A Southerner’s Journey Through the Smithsonian Collections won him Author of the Year in History by the Georgia Writers Association in 2020. His new book is The Ever-Changing Georgia Coast: A Natural History of Its Creation, Transformation, and Future.

About the Moderator

Susan Lozier is dean and Betsy Middleton and John Clark Sutherland Chair in the College of Sciences at Georgia Institute of Technology. One of the world’s foremost physical oceanographers, Lozier is the international project lead for the Overturning in the Subpolar North Atlantic Program (OSNAP). She recently served as president of the American Geophysical Union and currently serves on the Board of Trustees for the Woods Hole Oceanographic Institution and the Board of Directors for the Monterey Bay Aquarium Research Institute. Her recent honors include election as a fellow of the American Academy of Arts and Sciences in 2020 and receipt of the Henry Stommel Research Medal in 2022, the highest honor given to an oceanographer by the American Meteorological Society. In 2025, Lozier was named Faculty of the Year by the Georgia Tech Graduate Student Government Association.

About Presenting Science

Hosted in collaboration with the Georgia Tech Friends of Sciences, the Presenting Science series hosts distinguished researchers and thought leaders who share the latest findings and topics of interest with the Atlanta community. Our audience includes professionals, faculty, staff, alumni, students, and researchers throughout the greater metro community. Our alumni and student audience — from the College of Sciences and across the Institute — are among the most engaged. 

Lead photo: Salt marsh coast near Skidaway Island, Georgia (Maxwell Guberman / Georgia Tech).

Event questions: Leslie Roberts
Media questions: Jess Hunt-Ralston

Featured Speakers

Adharsh Rajagopal works in DRAM Device and Cell Technology at Micron Technology, where he develops advanced memory technologies for next-generation semiconductor devices. His expertise includes semiconductor device physics, materials characterization, process integration, and thin-film technologies. Before joining Micron, he conducted doctoral research at the University of Washington focused on high-performance tandem perovskite solar cells and emerging photovoltaic technologies. He holds a doctorate in materials science and engineering.

Michael Hamilton is the James B. Davis Professor in electrical and computer engineering at Auburn University and leads wiring, interconnects, and packaging efforts for quantum computing at Google Quantum AI. His research spans superconducting and cryogenic devices, advanced packaging and integration technologies, nanotechnology-enabled electronic and photonic systems, and semiconductor device performance in extreme environments. He previously served as director of the Alabama Micro/Nano Science and Technology Center and worked at MIT Lincoln Laboratory.

Event Details

Date: Tuesday, November 3, 2026
Time: 9:15–10:45 a.m.
Location: Marcus Nanotechnology Building, Georgia Tech

Adharsh Rajagopal will speak from 9:15 to 10 a.m., followed by Michael Hamilton from 10 to 10:45 a.m. 

Registration

The Brand Lecture is presented as part of Microelectronics Day, a full-day event hosted by the Institute for Matter and Systems. Registration is free, and all Brand Lecture attendees must register for Microelectronics Day to attend.

Register for Microelectronics Day

Location: The Kendeda Building Patio
Date & Time: Wednesday, October 21, 11:00 AM - 12:00 PM

The Center for Student Engagement invites all students, faculty, and staff to Buzz to the Booth, a series of civic engagement events designed to help the campus community register to vote, vote early, stay informed on key election deadlines, and connect with others around voting and civic participation.

Find full details in the Civic Engagement Engage portal. Events at a glance:

• Early Voting on Campus | Wednesday, Oct. 14 & Thursday, Oct.15 | 9 a.m. - 5 p.m. | Multicultural Lounge *Bring government-issued photo ID
• Election Day Watch Party | Tuesday, Nov. 3 | 7 – 10:30 p.m. | Cypress Theater

Special emphasis is given to Tissue Engineering and Regenerative Medicine and particular applications and more details are described on the lab web page.

Faculty host: Alexander Vlahos

 

• 3:30 p.m.- Ramblin' On: Miles of Memories party on the Instructional Center Lawn begins
• 4:30 p.m.- Ramblin On: Miles of Memories bike ride begins
• 5:30 p.m.- Event Concludes

This month, we will focus on combatting loneliness by exploring how to make meaningful friendships and foster social wellness. We will also let students know how to access core services on campus that promote belonging and community. 

Please join SEWB on Thursday, October 22 from 11 a.m. to 12 p.m. in the Rafael Bras Meeting Room of the John Lewis Studen Center for good discussion, yummy Dunkin’ munchkins, and giveaways. The more voices we hear, the better we can continue building a Georgia Tech that reflects and supports the needs of our students.

Let’s keep the conversation going—because your voice matters!

Abstract: Abstract: Decision-making under uncertainties has been a subject of study for many years. In particular, the decision making (optimization) for complex systems such as engineering and economic systems involves human-decision phase. This triggers the occurrences of uncertainties in the decision making phase in addition to the widely-existed inherent uncertainties in the actual systems. In this talk, such challenges will be addressed by summarizing the year’s efforts of the presenter when he was with the University of Manchester before 2016. At first, a generic framework on the decision making for uncertainty systems has been formulated into a “closed loop control design problem”, where the uncertainties in both decision making phase and the actual systems have been represented by the uncertainty injections to the “controller” and to the “plant to be controlled”. The uncertainties in human decision making phase is characterized by their probability density functions (PDF) of the brain-cell’s signal collected via brain-computer-interface (BCI). Using such a generic framework, decision making under uncertainties are formulated as a PDF control problem of objective functions and constraints- leading to a total solution for the stochastic optimization for complex systems. Two case studies will be presented together with the rationale and claims that most of the existing stochastic optimizations are special cases of the presented theory. Note that the presentation is based upon the published materials by the author.
 

Bio: Professor Hong Wang (Member of European Academy of Sciences and Arts, FIEEE, FIET, FInstMC, SMIEEE) received the BSc form Anhui University of Science and Technology in 1982, the master’s and Ph.D. degrees from the Huazhong University of Science and Technology, Wuhan, China, in 1984 and 1987, respectively. He was a Research Fellow with Salford University, Salford, U.K., Brunel University, Uxbridge, U.K., and Southampton University, Southampton, U.K., before joining the University of Manchester Institute of Science and Technology (UMIST), Manchester, U.K., in 1992. He was a Chair Professor in process control of complex industrial systems with the University of Manchester (UoM), U.K., from 2002 to 2016, where he originated probability density function control theory in 1996 and was the Deputy Head of the Paper Science Department, the Director of the UMIST Control Systems Centre from 2004 to 2007, which is the birthplace of Modern Control Theory established in 1966. He was a University Senate member and a member of general assembly during his time in Manchester. Whilst he has been an Emeritus Professor of UoM, from 2016 to 2018, he was with the Pacific Northwest National Laboratory (PNNL), Richland, WA, USA, as a Laboratory Fellow and Chief Scientist,
and was the Co-Leader and the Chief Scientist for the Control of Complex Systems Initiative. He joined the Oak Ridge National Laboratory in January 2019.

His research focuses on stochastic distribution control, fault diagnosis and tolerant control, and intelligent controls with applications to complex system area. He has published 6 books and 200+ journal papers in these areas together with 10+ awards/prizes at international conferences.

He is an associate editor for IEEE Transactions on Neural Networks and Learning Systems and was an Associate Editor of IEEE Transactions on Automatic Control (2002 – 2004), IEEE Transactions on Control Systems Technology (2013 – 2018), and the IEEE Transactions on Automation Science and Engineering. He is also a member for three IFAC Committees for the three areas of his research.

Abstract: We study a class of nonconvex–nonconcave minimax problems in which the inner maximization problem satisfies a local Kurdyka–Łojasiewicz (KL) condition that may vary with the outer minimization variable. In contrast to the global KL or PL conditions commonly assumed in the literature—which are significantly stronger and often too restrictive in practice—this local KL condition accommodates a broader range of practical scenarios. However, it also introduces new analytical challenges. In particular, as an optimization algorithm approaches a stationary point, the region over which the KL condition holds may shrink, leading to a more intricate and potentially ill-conditioned landscape. To address this challenge, we show that the associated maximal function is locally generalized Hölder smooth. Leveraging this key property, we develop an inexact proximal gradient method for solving the minimax problem, where the inexact gradient of the maximal function is computed by applying a proximal gradient or sequential convex programming method to a KL-structured subproblem. Under mild assumptions, we establish complexity guarantees for computing an approximate stationary point of the minimax problem.

This is joint work with Xiangyuan Wang (University of Minnesota).
 

Bio: Zhaosong Lu is a Full Professor in the Department of Industrial and Systems Engineering at the University of Minnesota. He received his Ph.D. in Operations Research from Georgia Tech. His research focuses on the theory and algorithms of continuous optimization, with applications in data science and machine learning. Dr. Lu has published extensively in leading journals, and his research has been supported by major funding agencies, including AFOSR, NSF, and ONR. He has served on several prize committees, such as the INFORMS George Nicholson Prize Committee and the ICCOPT Best Paper Award Committee. He has also served as an Associate Editor for leading journals, including Mathematics of Operations Research, SIAM Journal on Optimization, Computational Optimization and Applications, and Journal of Global Optimization.

Bio: Saiprasad Ravishankar is currently an Associate Professor in the Departments of Computational Mathematics, Science and Engineering and Biomedical Engineering at Michigan State University (MSU). He directs the signals, learning, and imaging (SLIM) research group and the data-driven neuroscience of meditation (DANSOM) lab at MSU. He received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology Madras, India, in 2008, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering in 2010 and 2014, respectively, from the University of Illinois at Urbana-Champaign, where he was then an Adjunct Lecturer and a Postdoctoral Research Associate. From August 2015 to 2018, he was a postdoc in the Department of Electrical Engineering and Computer Science at the University of Michigan, and then a Postdoc Research Associate in the Theoretical Division at Los Alamos National Laboratory from August 2018 to February 2019, before joining MSU. His research interests include machine learning, computational and biomedical imaging, signal processing, image processing, inverse problems, data science, neuroscience, and physics and astrophysics applications. His research has been recognized with numerous awards including an NSF CAREER Award, IEEE Signal Processing Society Young Author Best Paper Award, and best student paper awards or finalist at numerous conferences such as the IEEE International Symposium on Biomedical Imaging (ISBI) 2018, IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2017, ISBI 2020, and Optical Imaging Congress 2023.

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

While we prefer you join in person, if you are unable to attend, join online at:
https://gatech.zoom.us/j/98109284552?pwd=CrXDIye86vmEtCywAV7wmjjz1LqEY8.1
Meeting ID: 981 0928 4552
Passcode: 947902

Bio:  Saiprasad Ravishankar is currently an Associate Professor in the Departments of Computational Mathematics, Science and Engineering and Biomedical Engineering at Michigan State University (MSU). He directs the signals, learning, and imaging (SLIM) research group and the data-driven neuroscience of meditation (DANSOM) lab at MSU. He received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology Madras, India, in 2008, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering in 2010 and 2014, respectively, from the University of Illinois at Urbana-Champaign, where he was then an Adjunct Lecturer and a Postdoctoral Research Associate. From August 2015 to 2018, he was a postdoc in the Department of Electrical Engineering and Computer Science at the University of Michigan, and then a Postdoc Research Associate in the Theoretical Division at Los Alamos National Laboratory from August 2018 to February 2019, before joining MSU. His research interests include machine learning, computational and biomedical imaging, signal processing, image processing, inverse problems, data science, neuroscience, and physics and astrophysics applications. His research has been recognized with numerous awards including an NSF CAREER Award, IEEE Signal Processing Society Young Author Best Paper Award, and best student paper awards or finalist at numerous conferences such as the IEEE International Symposium on Biomedical Imaging (ISBI) 2018, IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2017, ISBI 2020, and Optical Imaging Congress 2023.

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

While we prefer you join in person, if you are unable to attend, join online at
https://gatech.zoom.us/j/93328955144?pwd=qepbKpZ2pV9Jl0ocrT6JGbHCX169qw.1
Meeting ID: 933 2895 5144
Passcode: 331085

Title: Applying Scientific Computing Perspectives to Neural Network Training

Abstract: Machine learning techniques and their AI decedents are increasingly important part of modern science and engineering. They have proven to be powerful in areas such as surrogate model development, hypothesis generation, and data analysis. Often, these approaches rely on a parameterized function approximation known as the neural network. These approximators are renowned for their flexibility and relative ease of use (if not accuracy). With that ease of use comes a large computational expense. For instance, recent work has demonstrated that pre-training a LLM on the Frontier supercomputer would require two years with ideal parallelization [1]. This talk seeks to examine the neural network with a scientific computing lens to enhance our ability to understand details of the approximation and improve training. Underpinning these ideas is an aspirational hypothesis that insights will lead to multilevel (or hierarchical) methodologies to accelerate training using dramatically fewer resources. 

This talk proceeds in two parts. In the first part, we discuss an adaptive basis perspective that has proved fruitful in Scientific Machine Learning (SciML) [2]. The central idea is that the output of the penultimate layer can be seen as providing a basis for the approximation space. With this perspective we develop efficient “operator-split” training algorithms, and new initialization strategies motivated by stability concerns. The second part extends the adaptive basis perspective by considering all layers of the neural network to be basis functions in a learned approximation space. We discuss the challenges associated with the typical neural network architectures that use globally supported basis functions. We then describe Kolmogorov-Arnold networks (KANs) as an alternate architecture built on locally supported splines basis functions [3]. A one-to-one relationship between KANs and a multi-channel ReLU network is shown and used to argue a relaxation property reminiscent of properties of matrix-split iterative linear solvers. Finally, using a natural refinement algorithm combined with the relaxation property, we develop a multilevel training algorithm for KANs demonstrating it on problems in SciML.

1. Dash, et al., Optimizing distributed training on frontier for large language models. In ISC High Performance 2024 Research Paper Proceedings (39th Intl. Conference), 2024.
2. Cyr, et al., Robust training and initialization of deep neural networks: An adaptive basis viewpoint, Mathematical and Scientific Machine Learning, 2020. 
3. Southworth, et al. Multilevel Training for Kolmogorov Arnold Networks, arXiv:2603.04827, 2026 (submitted to SISC)

Bio: Eric C. Cyr has been at Sandia Albuquerque since 2009 and is a Distinguished Member of the Technical staff. Prior to that he received a BS in Computer Science from Clemson University in 2002, and a PhD in Computer Science from University of Illinois at Urbana-Champaign in 2008. His formal training is in numerical methods, and scientific computing. As a Sandian he has worked in a range of diverse areas including high-performance computing, preconditioners for multi-physics, discretizations for computational plasma simulation, sensitivity analysis for PDEs, numerical optimization, and software development for science applications. In 2018, Eric received the DOE Early Career Award to fund a focus on developing layer-parallel methods for training deep neural networks. This work has broadened his exposure to machine learning. To this end, Eric is working to extend the applicability of HPC to deep learning, understand the behavior and approximation properties of neural networks, and develop methodologies where machine learning can be used to enhance the impact of computation on science and engineering disciplines.

CHOOSE FROM TWO WORKSHOPS:

Workshop #1 - In-Person
Thursday, October 29 | 10 a.m. - 12 p.m. | R. Randall Rollins room 226
*lunch provided following the workshop

Workshop #2 - Virtual
Friday, October 30 | 10:00am-12:00pm | Zoom

This workshop is intended for students, faculty, and staff at Georgia Tech and guests interested in learning more about patent searching. The session will cover patent classification systems and focus on the following two patent databases: Espacenet (Open access) and PatSnap (Georgia Tech only). We will provide an overview of the database platforms and examine the unique search features of each database. Attendees are encouraged to follow along with tool demonstrations.

Patents provide valuable and cutting-edge information for innovators and researchers. This workshop will begin with a brief introduction to intellectual property and then will focus on patents. The presenter will demonstrate how to conduct preliminary patent searches using publicly accessible patent tools. Attendees will have an opportunity to participate in hands-on learning activities.

About the Artists

Nydia Blas is a visual artist who grew up in Ithaca, New York, and resides in Atlanta, Georgia. She is an Assistant Professor in the Department of Art and Visual Culture at Spelman College in Atlanta, Georgia. She has completed artist residencies at Constance Saltonstall Foundation for the Arts and The Center for Photography at Woodstock.

Her work has been commissioned by The New York Times, New York Magazine, The New Yorker, Time Magazine, Harper’s Bazaar, and more. Blas uses photography, collage, video, and books to explore themes of sexuality, intimacy, and her lived experience as a girl, woman, and mother. Blas is widely recognized for The Girls Who Spun Gold, a collection of images that resulted from a Girl Empowerment Group she founded after observing a lack of space and community for teen girls of African descent in Ithaca, N.Y. Her first major monograph Love You Came from Greatness (2025), is an exploration of one Ithaca-based Black family and its community across many generations. The book is also a formally rigorous examination of the taxonomy and syntax of family portraiture.

Joshua Dudley Greer is a photographer based in Atlanta, Georgia, where he teaches at Georgia State University. His work has appeared in The New York Times, The California Sunday Magazine, The Atlantic, PDN, Le Monde, The Georgia Review, GUP Magazine, and Oxford American. He has received grants from the Maryland State Arts Council, Tennessee Arts Commission, and the Aaron Siskind Foundation. He has published two monographs to date – Somewhere Along the Line (Kehrer Verlag, 2019) and The Makeshift City (GOST, 2024). His work is included in the permanent collections of the Harvard Art Museums, the Museum of Contemporary Photography, the Ogden Museum of Southern Art, the New York Public Library, the Do Good Fund, and the High Museum of Art.

Yohanne Lamoulère, a photographer based in Marseille, France, graduated from the École nationale supérieure de photographie in Arles in 2004. Her preferred themes are urban peripheries and insularity in its multifaceted forms. She published Faux Bourgs (Le Bec en l’air) in 2018, a compilation of her series on Marseille. Her work has been featured in numerous exhibitions: MUCEM (Marseille), Portrait(s) festival (Vichy), Fondation Schneider (Wattwiller), ImageSingulières festival (Sète), Clervaux-Cité de l’image (Luxembourg), and is included in public and private collections (CNAP, BnF, Neuflize-OBC). A member of the collectives Tendance Floue and Zirlib, she released her first film, L’œil Noir, in 2025. 

Geoffroy Mathieu’s photography explores how environmental and political issues are made tangible in the landscapes. Through travel and immersion-based projects, he documents shifting territories, in-between spaces, and objects and actions that reveal resistances in the way in which places are used. His photography series are all pursued as poetic investigations, combining rigorous documentary research with a poetic approach to build situated narratives. He collaborates with associations, collectives, and researchers to circulate his images beyond the art world, support causes, and contribute to public debate on ecological care.

A graduate of the French Higher School of Photography (ENSP) in Arles, he lives and works in Marseille. He presents his works as publications (Actes Sud, Poursuite, Filigranes, Zoème, Wildproject, Building Books), solo or collective exhibitions, and, more recently, walked performances. He participated in the fourth edition of Regards du Grand Paris (2021), received the “Radioscopie of France” Major Photojournalism Commission (2022), and co-published Anti-installation with Jordi Ballesta (Building Books, 2023), supported by the French Center for Visual Arts (CNAP) publishing grant.

Blanche Lafuente is a French drummer and improviser. Trained in theater and jazz (DEM in jazz, 2018), she develops a body of work situated at the crossroads of rock, free jazz, traditional and electronic music, and performance. She is a founding member of the duo Qonicho Ah! and the trio NOUT (Jazz Migration 2021, Zenith Award 2023), and in 2025 she will launch Ganagobie, a project combining voice, dance, electronic music, and live performance. She regularly collaborates with large ensembles, notably Mats Gustafsson’s Fire! Orchestra and Kogoba Basigui by Eve Risser and Naïny Diabaté. Her work explores rhythm as a collective and sensorial force, linking music, bodies, and shared spaces.

Sponsored by: Ivan Allen College of Liberal Arts; School of Modern Languages; School of Literature, Media and Communication; Georgia Tech Arts; Atlanta Global Study Center; School of Design; France-Atlanta; Villa Albertine x Consulat Général de France à Atlanta; City of Atlanta – Mayor’s Office of Cultural Affairs; Delta Airlines; Air France; Jade Fiducial. 
 

Be as creative as you can on the costumes ;)

Our distinguished guests share their perspectives, examine local and global trends, delve into the nuances of leadership, and illuminate the interconnectedness of our changing business world. You’re invited to join us for a dynamic convergence of minds where ideas take center stage.

Join us for a special edition of the series, hosted as part of the TechForward MBA Conference, featuring Claudio Zanardo, president and CEO of Pirelli North America. Attendees will have the opportunity to learn about Pirelli's North American operations and its role in driving technological innovation, including the integration of AI-based computer vision and advancements in autonomous driving. The conversation will also highlight Pirelli's commitment to sustainability and offer a behind-the-scenes look at the company's involvement in Formula 1.

Our Tech Talks Business audience consists of industry leaders, working professionals, faculty, staff, alumni, and students. Our student and alumni audience – from Scheller College and across the Institute – are among the most engaged. At the end of the session, Claudio will have the opportunity to engage directly with the audience during a brief Q&A.

View Claudio Zanardo's Bio

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Conversations@TechSquare is a dynamic space for new ideas, not an environment for established concepts. We gather creators and innovators from across Georgia Tech, the broader Tech Square community, and beyond, to engage in open dialogue around some of today’s biggest challenges and opportunities. These gatherings are organized and hosted by the Georgia Tech Institute for People and Technology (IPaT) and will occur several times during a semester at the Tech Square Clubhouse. The Clubhouse address is 848 Spring Street NW, Atlanta, Georgia, 30308 (street level, behind the Centergy One Bldg.).

Tech Square Clubhouse

PARKING:
Parking is available at the Centergy One parking deck, located right next door. You can also find additional street parking via Park Mobile on Spring and 5th Street. Centergy One parking deck daily rates: Half Hour: $3.00 | One Hour: $6.00 | Two Hours: $12.00 | Daily Max: $20.00

GT CAMPUS BUS: Take the Gold route bus which stops at Tech Square.

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

ABSTRACT
The plasma membrane serves as the critical interface where cells endure and respond to their physical environment. We recently revealed that the PIEZO1 mechanosensing axis actively safeguards membrane integrity through a hierarchical, two-layer mechanoprotective mechanism. This involves rapid architectural buffering followed by a calcium-dependent positive feedback loop engaging Calmodulin and Filamin A to reinforce cortical stability. This fundamental discovery in mechanoprotection serves as the blueprint for our translational innovations in "Thrombo-protective Oncology." By engineering a microfluidic "CAT-on-chip" to recapitulate venous shear stress, we discovered that metastatic cancer cells exploit a strikingly similar mechanobiological network to trigger pathological clotting. Specifically, tumor-induced hypercoagulation is driven by a Focal Adhesion Kinase (FAK)-Calmodulin (CaM) axis, which structurally "decrypts" Tissue Factor (TF) by disengaging it from cytoskeletal Filamin A. To translate these microfluidic discoveries into clinical practice, we developed "SmartClot", an AI-driven Point-of-Care Testing (POCT) platform that rapidly stratifies cancer-driven thrombotic risk using blood diffusion kinetics. This seminar will highlight how decoding fundamental nanoscale mechanosensing paves the way for next-generation diagnostic and therapeutic technologies.

BIO
Professor Lining Arnold Ju (PhD, GAICD, FHEA) is a Snow Fellow, Australian Heart Foundation Future Leader Fellow, and recipient of the Australian Academy of Science John Booker Medal. He received his PhD in Biomedical Engineering from Georgia Tech and Emory University in 2013 and now directs the Mechanobiology and Biomechanics Laboratory (MBL) at the University of Sydney's School of Biomedical Engineering.

Ju’s research operates at the intersection of fundamental mechanobiology and biomedical engineering. His team recently decoded the PIEZO1 mechanosensing axis and has pioneered multiple biomechanical nanotools, including multi-parametric thrombus profiling microfluidics ("CAT-on-chip") and patient-specific vessel-on-a-chip platforms. His novel understanding of the mechanics behind blood clot formation has directly driven the development of point-of-care testing (POCT) technologies, such as the machine learning-assisted SmartClot diagnostic tool. His overarching vision integrates advanced biomanufacturing, high-throughput microfluidic phenotyping, and generative AI to create intelligent biosensing technologies to predict and prevent cardiovascular and cancer-associated thrombotic risks.

Andrés García, faculty host

Each seminar will feature three speakers who will be given 10-15 minutes to present their current research in an accessible manner for broad audiences, there will then be a 10-minute questions from the audience and feedback from the CoS Young Alumni Board Panel.

All Georgia Tech students are welcome to attend. 

Event Details:

Making Science Accessible + CoS Young Alumni Board Networking

Oct 21st, 2026: 1:00 pm – 2:15 pm Talks, 2:15 -3:00 pm Refreshments and Networking
MoSE 3201A, 901 Atlantic Dr. N.W.
Atlanta, GA 30332

 

Abstracts due October 9th:

Submit here 

Please RSVP if you wish to attend.

All Georgia Tech students are welcome to attend. 

This seminar series will feature graduate students from the CoS community presenting their research in plain language

and provide opportunity for students to interact with their peers outside of their department and field! 

Each seminar will feature three speakers who will be given 10-15 minutes to present their current research in an accessible

manner for broad audiences, there will then be a 10-minute questions from the audience and feedback from the CoS Young Alumni Board Panel.

Event Details:

Making Science Accessible + CoS Young Alumni Board Networking

Nov 18th, 2026: 1:00 pm – 2:15 pm Talks, 2:15 -3:00 pm Refreshments and Networking
MoSE 3201A, 901 Atlantic Dr. N.W.
Atlanta, GA 30332

 

Abstracts due October 9th:

Submit here 

Please RSVP if you wish to attend.

ABOUT THE ACADEMY:
This eight-week proposal development academy will orient researchers to NIH and its most frequently used award mechanisms – the R01. This program will review the core components of R01 applications, provide suggestions for structuring your proposal, and demystify the review process.

WHO SHOULD PARTICIPATE? 
This academy is best suited for early-career faculty members and others who have not yet secured an R01 or equivalent award. Applicants at any stage of readiness are welcome, and those committed to applying within the next six to 12 months are particularly encouraged to join.

WHEN & WHERE?
Courses will take place via Zoom on Mondays from 12 - 1 p.m., Sept. 28 - Nov. 16.

ABOUT THE ACADEMY:
This eight-week proposal development academy will orient researchers to NIH and its most frequently used award mechanisms – the R01. This program will review the core components of R01 applications, provide suggestions for structuring your proposal, and demystify the review process.

WHO SHOULD PARTICIPATE? 
This academy is best suited for early-career faculty members and others who have not yet secured an R01 or equivalent award. Applicants at any stage of readiness are welcome, and those committed to applying within the next six to 12 months are particularly encouraged to join.

WHEN & WHERE?
Courses will take place via Zoom on Mondays from 12 - 1 p.m., Sept. 28 - Nov. 16.

ABOUT THE ACADEMY:
This eight-week proposal development academy will orient researchers to NIH and its most frequently used award mechanisms – the R01. This program will review the core components of R01 applications, provide suggestions for structuring your proposal, and demystify the review process.

WHO SHOULD PARTICIPATE? 
This academy is best suited for early-career faculty members and others who have not yet secured an R01 or equivalent award. Applicants at any stage of readiness are welcome, and those committed to applying within the next six to 12 months are particularly encouraged to join.

WHEN & WHERE?
Courses will take place via Zoom on Mondays from 12 - 1 p.m., Sept. 28 - Nov. 16.

ABOUT THE ACADEMY:
This eight-week proposal development academy will orient researchers to NIH and its most frequently used award mechanisms – the R01. This program will review the core components of R01 applications, provide suggestions for structuring your proposal, and demystify the review process.

WHO SHOULD PARTICIPATE? 
This academy is best suited for early-career faculty members and others who have not yet secured an R01 or equivalent award. Applicants at any stage of readiness are welcome, and those committed to applying within the next six to 12 months are particularly encouraged to join.

WHEN & WHERE?
Courses will take place via Zoom on Mondays from 12 - 1 p.m., Sept. 28 - Nov. 16.

ABOUT THE ACADEMY:
This eight-week proposal development academy will orient researchers to NIH and its most frequently used award mechanisms – the R01. This program will review the core components of R01 applications, provide suggestions for structuring your proposal, and demystify the review process.

WHO SHOULD PARTICIPATE? 
This academy is best suited for early-career faculty members and others who have not yet secured an R01 or equivalent award. Applicants at any stage of readiness are welcome, and those committed to applying within the next six to 12 months are particularly encouraged to join.

WHEN & WHERE?
Courses will take place via Zoom on Mondays from 12 - 1 p.m., Sept. 28 - Nov. 16.

Date: Wednesday, Oct. 21, 2026
Time: 1:30–4:45 p.m.
Location: Marcus Nanotechnology Building, Conference Rooms 1116–1118
Format: In person and online

Program

• 1:30 p.m. | Electron Beam Lithography Fabricated Gratings for Space Applications | Fabien Grisé, Penn State University
  • Fabien Grisé will discuss the use of electron beam lithography to fabricate diffraction gratings for future space telescopes. The presentation will address nanoscale patterning, large-area writing, stitching control, resist and dose optimization, and fabrication considerations for X-ray, extreme-ultraviolet, and far-ultraviolet applications.
• 2:15 p.m. | Electron Beam Lithography from Elionix’s Perspective | Lukas Stampfer, STS-Elionix
  • Lukas Stampfer will provide a vendor’s perspective on the inner workings of electron beam lithography systems, the technical trade-offs involved in their development, and strategies for addressing equipment-related effects that can influence exposure results.
• 3 p.m. | Coffee Break
• 3:15 p.m. | Advanced Data Preparation and Techniques for Optimized Patterning | Kaustubh Vyas, GenISys GmbH
  • Kaustubh Vyas will examine the data preparation steps that help translate a design file into a successfully fabricated structure. Topics will include machine-specific fracturing, shot placement, writing order, field control, proximity-effect correction, simulation, and scanning electron microscopy-based metrology.
• 4 p.m. | Electron-Beam Lithography for Photonic Device Fabrication: Applications and Practical Considerations | Ashkan Zandi, Georgia Institute of Technology
  • Ashkan Zandi will discuss the development and practical implementation of electron beam lithography processes for integrated optics, metaphotonic devices, and grayscale-fabricated three-dimensional structures. The presentation will highlight resist selection, exposure-dose optimization, proximity effects, pattern fidelity, development conditions, reproducibility, and fabrication yield.
• 4:45 p.m. | Adjourn

About the Speakers

Fabien Grisé is an associate research professor in the Department of Astronomy and Astrophysics at Penn State University. His research focuses on diffraction-grating technology for future NASA space telescopes, including electron beam lithography fabrication for X-ray, extreme-ultraviolet, and far-ultraviolet gratings.

Lukas Stampfer has served as an application engineer for European and North American customers at STS-Elionix since 2021. He earned a doctorate in quantum transport from the University of Copenhagen and a master’s degree in condensed matter physics from the Technical University of Munich.

Kaustubh Vyas works across applications engineering, product improvement, and technical sales at GenISys. His background includes III-V and silicon photonics, and his current work focuses on lithography data preparation, predictive simulation, and process improvement.

Ashkan Zandi is a research faculty member in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. His research spans nanofabrication, integrated photonics, metaphotonics, biosensors, quantum sensing, and biomedical engineering.

Sponsors

This seminar is sponsored by STS-Elionix and GenISys GmbH.

Please join us for coffee and an informal discussion of this incident and what it implies about AI safety and security.  We will be joined by members of the AI Safety Initiative, who hosted an event about this incident last month.

Georgia Tech students, faculty, and staff are welcome. If you do not have access to Coda, near the beginning of the event we will have a staff member or student waiting by the reception desk near the elevators to escort people up.

Abstract: This talk describes the progress in analysis and optimization of Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) with infinite state spaces and possibly noncompact action sets. We shall also discuss applications to inventory control and to controlled linear Gaussian systems. 
 

Bio: Eugene A. Feinberg received MS in Applied Mathematics and Computer Engineering from Moscow University of Transportation, Russia, in 1976 and Ph.D. in Probability and Statistics from Vilnius University, Lithuania, in 1979. Currently he is Distinguished Professor at the Department of Applied Mathematics and Statistics of Stony Brook University.

His research interests include stochastic models of operations research, probability theory, real analysis, Markov Decision Processes, and applications of operations research and statistics to engineering, biology, and medicine. He has published more than 100 papers and edited the Handbook on Markov Decision Processes. His research has been partially supported by the National Science Foundation, Office of Naval Research, National Institute of Health, New York Office of Science, Technology and Academic Research, and private industry. He has served as a Council Member of the INFORMS Applied Probability Society and on several editorial boards. He is a fellow of INFORMS.

Host: Jiapeng Gao

Title: Title: Machine Learning Across Scales: From Hidden Exoplanets to Efficient Model Training

Abstract:

Non-transiting planets can remain hidden while leaving dynamical signals in the transit timing variations (TTVs) of observed planets. DeepTTV provides a machine learning (ML) approach to this inverse problem, using N-body simulations to generate training data for a neural network that combines recurrent and Transformer architectures to infer the mass and orbital properties of unseen planetary companions. In the first part of this talk, I will discuss DeepTTV. In the second part, I will introduce my current work in industry on improving the efficiency of large-scale ML training, including directions such as transfer learning and improving computational resource utilization.

• Agilent - Life Science
• BMG LABTECH
• Corning Incorporated - Life Sciences
• Cytek BioSciences
• 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
• Percival Scientific
• QIAGEN
• Quintara Biosciences - Sales
• R&D Systems - Reagent Sciences, Analytical Sciences
• Sartorius Corporation - Lab Essentials 
• Slingshot Biosciences Inc.
• Standard Biotools
• STERIS Corporation - Life Sciences
• Thermo Fisher Scientific - Laboratory Consumables Products
• Thermo Fisher Scientific - Bioscience division
• 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. 

Attendees should register through the Genius LMS, using the "GT Login" button. Click on "View Course Catalog", then enter "RCR" in the search bar to view the current RCR workshop sessions. You can view information about each class (including class times) by clicking on "more info".  To register for a class, click on "Register", then "Proceed to Checkout" (there is no cost for the sessions). Then click on "Confirm". You will receive a confirmation email with a calendar file. You will need to follow instructions given to you during the session in order to receive RCR in-person contact hour credit for attending.

Animal/Human Subjects Research
🗓️ Friday, October 30th
⏱️11 AM - 12 PM 
📍ONLINE

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

Attendees should register through the Genius LMS, using the "GT Login" button. Click on "View Course Catalog", then enter "RCR" in the search bar to view the current RCR workshop sessions. You can view information about each class (including class times) by clicking on "more info".  To register for a class, click on "Register", then "Proceed to Checkout" (there is no cost for the sessions). Then click on "Confirm". You will receive a confirmation email with a calendar file. You will need to follow instructions given to you during the session in order to receive RCR in-person contact hour credit for attending.

Research Misconduct
🗓️ Friday, October 30th
⏱️10 AM - 11 AM 
📍ONLINE

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

Attendees should register through the Genius LMS, using the "GT Login" button. Click on "View Course Catalog", then enter "RCR" in the search bar to view the current RCR workshop sessions. You can view information about each class (including class times) by clicking on "more info".  To register for a class, click on "Register", then "Proceed to Checkout" (there is no cost for the sessions). Then click on "Confirm". You will receive a confirmation email with a calendar file. You will need to follow instructions given to you during the session in order to receive RCR in-person contact hour credit for attending.

Mentoring and Collaborative Research
🗓️ Friday, October 23rd
⏱️10 AM - 11 AM 
📍ONLINE

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

Attendees should register through the Genius LMS, using the "GT Login" button. Click on "View Course Catalog", then enter "RCR" in the search bar to view the current RCR workshop sessions. You can view information about each class (including class times) by clicking on "more info".  To register for a class, click on "Register", then "Proceed to Checkout" (there is no cost for the sessions). Then click on "Confirm". You will receive a confirmation email with a calendar file. You will need to follow instructions given to you during the session in order to receive RCR in-person contact hour credit for attending.

Authorship 
🗓️ Friday, October 23rd
⏱️11 AM - 12 PM 
📍ONLINE

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

EndNote is a powerful bibliographic management tool that will help with your research process.

EndNote software is available to the Georgia Tech community, as part of your Georgia Tech Technology Fee.

At the end of this session you will be able to add references to EndNote from databases and online sources, manage references and PDFs in EndNote, and use Cite While You Write to add citations from EndNote to MS Word documents.

No prior experience with EndNote required.

This workshop will help you gain familiarity with tools for measuring scholarship and outputs of research. We will cover

• Resources for finding credible journals in your field
• Library databases for journal impact measures
• Tools for measuring citation counts and tracing citations
• Options for managing your scholarly identity and visibility
• Resources for open access publishing

The goal of the National Safety Council's DDC is to provide drivers with knowledge and safe driving techniques to prevent accidents and violations. This course focuses on accident prevention through hazard recognition and application of accident-avoidance techniques. In addition, the course addresses common driving violations that result in accidents and how to change driving habits to eliminate moving violations.

Throughout the 6-hour course, participants learn how to recognize both potential and immediate hazards, how to avoid accidents in a variety of driving conditions and how to choose safe and legal driving behaviors. The emphasis is on identifying and choosing safe and legal behind-the-wheel behaviors and actions.

In order to attend this course you must have a valid state driver license.

You are entitled to a discount on your auto insurance in Georgia after the completion of this course.

To Register:

1. Go to Genius LMS and use your GT Login
2. Click "View Course Catalog"
3. Search for "defensive"
4. Click "Register" for your preferred date
5. Click "Proceed to Checkout" and follow the instructions

IF YOU HAVE TROUBLE REGISTERING, or IF YOU DON'T GET AN EMAIL IMMEDIATELY AFTER REGISTERING, please contact ors@ors.gatech.edu.

Who Should Attend?:

All current Georgia Tech employees and students. Individuals who drive vans to transport 15 or more people must take the Van Safety course. To register for Van Safety, email generalsafety@ehs.gatech.edu.

Register Here

Grab your team and put your creativity to the test as you compete to build the ultimate edible haunted house. Expect surprise twists, mystery ingredients, fun challenges, and plenty of Halloween chaos along the way.

Prizes and bragging rights are on the line!

Bring your own decorating materials and/or use materials provided by GT Arts.

Sign up your team today! Sign up link: https://gatech.co1.qualtrics.com/jfe/form/SV_cNreuRHaI9X2cse)

Racers, start your engines! Join retroTECH and the Library's Gaming Collection for kart-racing action, from Super Mario Kart for the Super Nintendo to Mario Kart World for the Nintendo Switch 2.

Play for fun or sharpen your skills ahead of the Oct. 17 Mario Kart Live event, presented by Georgia Tech Arts, the Georgia Tech Jazz Ensemble, Atlanta's Video Games Alliance, and Georgia Tech Esports.

Location: Virtual/Zoom

Register

Malcolm MacIver
Professor, McCormick School of Engineering
Northwestern University

Co-sponsored by the Institute for Robotics and Intelligent Machines

Faculty Host: Nabil Imam

Trainees: Sign up to meet with the speaker.

Join virtually here.

Gordon Smith
Associate Professor, Department of Neuroscience
University of Minnesota

Co-sponsored by the School of Psychological and Brain Sciences

Faculty Host: Audrey Sederberg

Trainees: Sign up to meet with the speaker here

Join virtually here

Free food will be provided (usually pizza).

Date: November 10, 2026
Time: 11:00 a.m. - 1:00 p.m.
Location: Scholars Event Theater, Georgia Tech

This event is free and open to the public.

Drawing connections between Hip Hop, creative technology, digital storytelling, user experience design, media production, and artificial intelligence, Wilson will introduce participants to the concept of Design Remix Logic and its relevance in today's rapidly evolving technological landscape. Attendees will gain new perspectives on innovation, culture, and the creative processes that drive meaningful change across industries and communities.

Date: October 16, 2026
Time: 11:00 a.m. - 1:00 p.m.
Location: Scholars Event Theater

This event is free and open to the public.

Drawing from history, technology, and contemporary social issues, Bobb will examine the opportunities and challenges presented by AI while encouraging participants to think critically about the future of innovation. Attendees will gain insights into the intersections of technology, education, public policy, and society, and consider how creative technology can contribute to more thoughtful, responsible, and human-centered approaches to technological development.

Register to Attend

BEFORE YOU SIGN UP ON ENGAGE: Fill out the "Wreck Parade 2026: Entry Information" Google form.

Please only sign up for this event if you are participating individually or with an organization. Everyone else is welcome to come watch without signing up!

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.