{"691534":{"#nid":"691534","#data":{"type":"event","title":"Machine Learning Seminar Series | Accelerating fundamental physics: From theory design to experimental tests at CERN","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Fundamental physics is about designing bottom-up theories to explain the Universe, from elementary particles to the nature of gravity. Theoretical progress has traditionally relied on human insight into complex mathematics, with no systematic way to explore the space of ideas. I will discuss a series of neuro-symbolic AI results that systematize this approach while minimizing biases to prior literature.\u0026nbsp;Our AI tools also compute theory predictions and help design experimental tests. These AI tools also help calculate theory predictions and design experimental tests while providing human-readable insights from problem-solving process and explicitly cite previous scientific literature that inspired new LLM-generated ideas.\u003C\/p\u003E\u003Cp\u003EOn the experimental side, testing theories at the world\u0027s largest experiments, such as the Large Hadron Collider, is yet another computational challenge. High-dimensional data arrive at 40 MHz (~40 TB\/s), and decisions must be made rapidly. I will discuss recent advancements in robust neural inference techniques with reliable uncertainty quantification that let us exploit the full high-dimensional data in hypothesis tests. Additional machine learning methods make these genAI predictions trustworthy, enabling tests that outperform likelihood-ratio-based statistical tests.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Aishik Ghosh is an assistant professor in the School of Physics at Georgia Tech with a focus on developing AI methods to accelerate fundamental physics and astrophysics. His group works on theoretical physics, statistical methods, and experiment design. For robust scientific applications, Dr. Ghosh focuses on uncertainty quantification, interpretability, and verifiability of AI algorithms, targeting publications in physics journals and ML conferences. He has also published policy documents with the Organization for Economic Co-operation and Development and took a leading role in a book on AI and the Future of Science. He received his PhD in particle physics from Paris-Saclay University for introducing digital twins and neural inference techniques to a Large Hadron Collider experiment and was a postdoc at UC Irvine and Lawrence Berkeley National Laboratory. Website: \u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fprofaishikghosh.github.io%2F\u0026amp;data=05%7C02%7Cchrista.ernst%40research.gatech.edu%7Cfdf92a724a344d51ca2608df254a8272%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639270674070433784%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=xwviGQMOR5t2ty%2BoxRGZ3hv4lrEBPZSTzquTOH6W59o%3D\u0026amp;reserved=0\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/profaishikghosh.github.io\/. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/profaishikghosh.github.io\/\u003C\/a\u003E\u003C\/p\u003E\u003Ch4\u003E\u0026nbsp;\u003C\/h4\u003E\u003Ch4\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E\u003Ch5\u003E\u0026nbsp;\u003C\/h5\u003E\u003Ch5\u003E\u0026nbsp;\u003C\/h5\u003E\u003Ch5\u003E\u003Cstrong\u003EJoin Via Zoom:\u003C\/strong\u003E https:\/\/gatech.zoom.us\/j\/97583133407?pwd=arlGKeB48JGRzqOQt3mPELCH1sfL5J.1\u0026nbsp;\u003C\/h5\u003E\u003Ch5\u003E\u003Cstrong\u003EMeeting ID: 975 8313 3407\u0026nbsp;\u003C\/strong\u003E\u003C\/h5\u003E\u003Ch5\u003E\u003Cstrong\u003EPasscode: 799040\u003C\/strong\u003E\u003C\/h5\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAll Seminars Held 12pm - 1pm in CODA\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Aishik Ghosh, Georgia Institute of Technology \u2013 School of Physics "}],"uid":"27863","created_gmt":"2026-08-07 14:20:55","changed_gmt":"2026-10-21 19:41:20","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-28T12:00:00-04:00","event_time_end":"2026-10-28T13:00:00-04:00","event_time_end_last":"2026-10-28T13:00:00-04:00","gmt_time_start":"2026-10-28 16:00:00","gmt_time_end":"2026-10-28 17:00:00","gmt_time_end_last":"2026-10-28 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Building 9th floor Atrium \u0026 Virtual","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/97583133407?pwd=arlGKeB48JGRzqOQt3mPELCH1sfL5J.1","title":"Zoom Link"},{"url":"https:\/\/profaishikghosh.github.io\/","title":"Lab Website"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[{"id":"9167","name":"machine learning"},{"id":"187023","name":"go-data"},{"id":"654","name":"College of Computing"},{"id":"188087","name":"go-irim"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"691555":{"#nid":"691555","#data":{"type":"event","title":"IRIM Fall 2026 Seminar Series |  The Dynamics of Fluid Physical Interaction: Safe, Adaptive, and Compliant Robot Intelligence","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ELOCATION UPDATE\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDalney Building \u2013 Room 180\u003Cbr\u003E\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fmaps.app.goo.gl%2Fc4rjT9frxiDFmcm77\u0026amp;data=05%7C02%7Cchrista.ernst@research.gatech.edu%7Cf725767e563e40d653ad08df2ed13002%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639281148226250700%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=JCGppUyQ6E2J4otQ%2Bf6%2FiWbn5gqHZU6KuFKaCnZ4PpM%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/maps.app.goo.gl\/c4rjT9frxiDFmcm77. Click or tap if you trust this link.\u0022\u003E926 Dalney Street NW\u003C\/a\u003E\u003Cbr\u003EAtlanta, GA 30318\u003Cbr\u003EWest Midtown\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E For decades, we have envisioned robots that can move, adapt, and collaborate with humans as fluidly as we do with each other. Yet even the most advanced systems struggle to achieve what I call fluid physical interaction: a regime where motion, force, and intent predictions are continuously co-regulated through constraint-aware estimation, learning, and control; enabling safe, adaptive, and seamless exchanges of energy and information. Achieving this requires robots that are stable yet flexible, adaptive yet predictable, and compliant yet purposeful. In this talk, I will show how a dynamical-systems perspective provides a unifying foundation for realizing fluid physical interaction. By shaping robot behavior through stable vector fields, viability manifolds, and adaptive dynamics models, we can generate motion policies that remain reactive, safe, and consistent even under uncertainty. I will present recent results that demonstrate how this framework enables robots to generalize complex behaviors from minimal demonstrations, adapt online to changes in their dynamics and environment, avoid obstacles in real time, and maintain long-horizon safety during physical collaboration. I will also discuss new efforts that combine dynamical-systems principles with visuomotor learning to achieve stable, compliant, and force-aware behavior from simulation-guided data. Together, these developments move us closer to embodied, adaptive, and compliant robot intelligence that can truly flow with humans and the environments they inhabit.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003ENadia Figueroa is the Shalini and Rajeev Misra Presidential Assistant Professor of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania, with secondary appointments in Computer and Information Science and Electrical and Systems Engineering. She is a core faculty member of the GRASP Lab. Her research integrates learning, control, and estimation to enable safe, adaptive, and fluid human\u2013robot interaction and collaboration. Her work bridges control theory, machine learning, perception, and biomechanics, with an emphasis on formal guarantees for robot behavior in dynamic, human-centered environments. Before joining Penn, she was a Postdoctoral Associate in MIT\u2019s CSAIL. She earned her Ph.D. in Robotics, Control, and Intelligent Systems from EPFL and conducted research at the German Aerospace Center (DLR) and NYU Abu Dhabi. She holds a B.Sc. in Mechatronics Engineering from Tecnol\u00f3gico de Monterrey and an M.Sc. in Automation and Robotics from TU Dortmund. She received a 2025 NSF CAREER Award and was a finalist for the 2020 Georges Giralt Ph.D. Award and the 2017 KUKA Innovation Award. Her publications have received multiple best paper honors at ICRA, CASE, RSS, and IEEE Transactions on Robotics. She chairs the IEEE RAS Women in Engineering Committee, leading global efforts to recognize and celebrate women in robotics.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAll Seminars Held on Wednesdays 12:15 - 1:15pm\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Nadia Figueroa - Shalini and Rajeev Misra Presidential Assistant Professor of Mechanical Engineering and Applied Mechanics, University of Pennsylvania"}],"uid":"27863","created_gmt":"2026-08-07 17:23:07","changed_gmt":"2026-10-20 17:49:11","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-21T12:15:00-04:00","event_time_end":"2026-10-21T13:15:00-04:00","event_time_end_last":"2026-10-21T13:15:00-04:00","gmt_time_start":"2026-10-21 16:15:00","gmt_time_end":"2026-10-21 17:15:00","gmt_time_end_last":"2026-10-21 17:15:00","rrule":null,"timezone":"America\/New_York"},"location":"Dalney Building \u2013 Room 180 | 926 Dalney Street NW Atlanta, GA 30318 ","extras":["free_food"],"related_links":[{"url":"https:\/\/nbfigueroa.github.io\/","title":"PI Website"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[{"id":"188087","name":"go-irim"},{"id":"11230","name":"Human Robot Interaction"},{"id":"9167","name":"machine learning"},{"id":"189814","name":"go-researchevents"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003Echrista.ernst@research.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"693183":{"#nid":"693183","#data":{"type":"event","title":"School of CSE Seminar Series: Wolfgang Dahmen","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Wolfgang Dahmen, professor at the University of South Carolina\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 23, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Peng Chen\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EOptimization in Scientific ML - is Accuracy Certification a Viable Goal?\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EZoom Link:\u003C\/strong\u003E \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/9923742334?pwd=aVdnMjZHUDFwWE44UkdNVmNhVVhwdz09\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/9923742334?pwd=aVdnMjZHUDFwWE44UkdNVmNhVVhwdz09\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E 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 \u0022conditional convergence guarantees\u0022. 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 \u0022conditional convergence\u0022 with accuracy certificates. Part of the material draws on the recent paper [1].\u003Cbr\u003E\u003Cbr\u003E[1] \u0026nbsp;Wolfgang Dahmen, Wuchen Li, Yuankai Tengang, Zhu Wang, Expansive Natural Neural Gradient Flows for Energy Minimization, Journal of Computational Physics, 563 (2026), 115117\u003Cbr\u003E\u003Cbr\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E 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).\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Wolfgang Dahmen, professor at the University of South Carolina\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 23, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Peng Chen\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EOptimization in Scientific ML - is Accuracy Certification a Viable Goal?\u003C\/em\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"School of CSE hosts a seminar from Wolfgang Dahmen, professor at the University of South Carolina"}],"uid":"36319","created_gmt":"2026-10-09 18:34:05","changed_gmt":"2026-10-20 13:35:26","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-23T14:00:00-04:00","event_time_end":"2026-10-23T15:00:00-04:00","event_time_end_last":"2026-10-23T15:00:00-04:00","gmt_time_start":"2026-10-23 18:00:00","gmt_time_end":"2026-10-23 19:00:00","gmt_time_end_last":"2026-10-23 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda, Room 114","extras":[],"hg_media":{"681445":{"id":"681445","type":"image","title":"Wolfgang-Dahmen.jpg","body":null,"created":"1792153925","gmt_created":"2026-10-16 12:32:05","changed":"1792153925","gmt_changed":"2026-10-16 12:32:05","alt":"CSE Seminar Wolfgang Dahmen","file":{"fid":"265853","name":"Wolfgang-Dahmen.jpg","image_path":"\/sites\/default\/files\/2026\/10\/16\/Wolfgang-Dahmen.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/16\/Wolfgang-Dahmen.jpg","mime":"image\/jpeg","size":28185,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/16\/Wolfgang-Dahmen.jpg?itok=DoKQJmTF"}}},"media_ids":["681445"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"166983","name":"School of Computational Science and Engineering"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EPeng Chen (pchen402@gatech.edu)\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"693193":{"#nid":"693193","#data":{"type":"event","title":"School of CSE Seminar Series: Min Wang","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Min Wang, staff scientist at Los Alamos National Laboratory\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;November 6, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 230\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Qi Tang\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EBridging Particle-scale Physics to Continuum Closure for Particle-laden Flows\u003C\/em\u003E\u003C\/p\u003E\u003Cdiv\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThe phase interaction models for disperse multiphase flows are crucial for modeling various scientific and engineering applications. In the existing theory of disperse multiphase flows, phase interactions are represented as forces between the phases. It is well known that models using only force-based interactions are ill-posed, resulting in non-hyperbolic governing equations. In this work, using ensemble averaging and nearest particle statistics, the fluid-particle phase interaction is decomposed into a particle-mean-field force (representing the conventional drag force) and the divergence of the particle-fluid-particle (PFP) stress. To explore the physics of PFP stress and develop a practical mathematical model, a series of particle-scale-resolved simulations have been conducted using CFD-DEM-IBM.\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EIt is found that for a fluid-particle system with high particle-fluid density ratios, the PFP stress is attractive along the flow direction and repulsive in the direction perpendicular to the flow. This serves as the macroscopic representation of the well-known drafting-kissing-tumbling (DKT) phenomena observed in experiments, which is still absent in existing particle-laden flow theories. To quantify the essential physics, a preliminary PFP stress model, expressed in terms of particle volume fraction and Reynolds number, is proposed based on physical principles and particle-resolved direct numerical simulations.\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Dr. Min Wang is a Staff Scientist in Fluid Dynamics and Solid Mechanics Group at Theoretical Division in Los Alamos National Laboratory (LANL). He obtained his PhD in computational mechanics, DEM-LBM\/CFD, from Swansea University in 2016. From 10.2015-06.2018, he worked in Rockfield Software L.t.d UK as a project engineer and focused on the development of Finite Element commercial software for multi-field coupling in geomechanics. In June 2018, he moved to Los Alamos National Laboratory, first as a Postdoc Research Associate, to perform research on the multiscale theory and technique for large material deformations, and on the multiphase flow theory and related closure issues using high-resolution CFD-DEM simulations and statistical mechanics. Then he was promoted to a Staff Scientist position. Dr. Wang\u0027s research interests include computational solid and fluid mechanics; multi-material\/phase flow theory; multiphysics and multiscale geomechanics, and application of machine learning to enhance the understanding of materials and multi-material\/phase flows. \u0026nbsp;He has published over 60 journal articles and served as editorial roles in international journals, such as Computers and Geotechnics, Journal of Rock Mechanics and Geotechnical Engineering, Rock and Soil Mechanics and so on since 2019. His research work is primarily supported by Department of Energy, LANL and oil industries like BP.\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Min Wang, staff scientist at Los Alamos National Laboratory\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;November 6, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 230\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Qi Tang\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EBridging Particle-scale Physics to Continuum Closure for Particle-laden Flows\u003C\/em\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"School of CSE hosts a seminar from Min Wang, staff scientist at Los Alamos National Laboratory"}],"uid":"36319","created_gmt":"2026-10-12 13:02:39","changed_gmt":"2026-10-13 16:11:57","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-06T14:00:45-05:00","event_time_end":"2026-11-06T15:00:00-05:00","event_time_end_last":"2026-11-06T15:00:00-05:00","gmt_time_start":"2026-11-06 19:00:45","gmt_time_end":"2026-11-06 20:00:00","gmt_time_end_last":"2026-11-06 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda, Room 230","extras":[],"hg_media":{"681407":{"id":"681407","type":"image","title":"Min-Wang.jpeg","body":null,"created":"1791810220","gmt_created":"2026-10-12 13:03:40","changed":"1791810220","gmt_changed":"2026-10-12 13:03:40","alt":"CSE Seminar Min Wang","file":{"fid":"265810","name":"Min-Wang.jpeg","image_path":"\/sites\/default\/files\/2026\/10\/12\/Min-Wang.jpeg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/12\/Min-Wang.jpeg","mime":"image\/jpeg","size":26412,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/12\/Min-Wang.jpeg?itok=-lXsix7O"}}},"media_ids":["681407"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"166983","name":"School of Computational Science and Engineering"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EQi Tang (qtang@gatech.edu)\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"693145":{"#nid":"693145","#data":{"type":"event","title":"Virtual Office Hour for \u0022Technology Design and Ethics in India\u0022","body":[{"value":"\u003Cp\u003EDrop in during our Virtual Office Hour (over \u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_YWI1MWZmYzEtNTUxNy00MDlkLWE0ZmMtYzhiODEyMTg2Nzll%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%221f4e064b-0d3f-4bac-85b9-1ea00c689fe7%22%7d\u0022\u003ETeams\u003C\/a\u003E), \u003Cstrong\u003EWednesday, November 4, \u0026nbsp;6 to 7 pm. \u003C\/strong\u003E\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_YWI1MWZmYzEtNTUxNy00MDlkLWE0ZmMtYzhiODEyMTg2Nzll%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%221f4e064b-0d3f-4bac-85b9-1ea00c689fe7%22%7d\u0022\u003E\u003Cstrong\u003EJOIN HERE\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E.\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAsk questions about the CoC\u0027s newest program, \u0022Technology Design and Ethics in India,\u0022 \u003C\/strong\u003Ea 6-week program (May 17 - June 25, 2027), with 4 weeks of online instruction\u003Cstrong\u003E followed by\u0026nbsp;2 weeks of continued GT instruction in Mumbai, India.\u003C\/strong\u003E Drop in for a few minutes to ask your question or stay the whole hour and hear what other students are asking\u003Cstrong\u003E.\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EProgram Courses:\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThe 2 foundational Computer Science courses of the program will be taught by Georgia Tech CS faculty and Program Director, Naveena Karusala.\u003C\/p\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e0c65d4fdcbe0bb8043059f45f05b46db\u0022\u003E\u003Cstrong\u003ECS 4001 \u2013 Computing \u0026amp; Society (Ethics Credit) -\u0026nbsp;\u003C\/strong\u003EStudents will critically examine how issues around technology, such as globalization, bias, privacy, and others, affect people worldwide.\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e8deef437bb9d4bc7603f80d7941693b3\u0022\u003E\u003Cstrong\u003ECS 3751 \u2013 Intro to User Interface Design - \u003C\/strong\u003EStudents will explore culturally situated approaches to design and, through the course project, create an inventive design artifact.\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ENo questions and ready to go? Apply\u003C\/strong\u003E \u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fatlas.gatech.edu%2Findex.cfm%3FFuseAction%3DPrograms.ViewProgramAngular%26id%3D10313\u0026amp;data=05%7C02%7Ctara.berry%40cc.gatech.edu%7Ccba551394cb34f2cdb7a08de1ca899c8%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C638979708276911681%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=gc10GYpcKVWl%2BqV%2FEfTCL%2FDw76OC7CLpt3S0d8AHOkY%3D\u0026amp;reserved=0\u0022 id=\u0022OWA42e19520-ca26-f5dc-96d2-f08de680adc6\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/atlas.gatech.edu\/index.cfm?FuseAction=Programs.ViewProgramAngular\u0026amp;id=10313. Click or tap if you trust this link.\u0022\u003E\u003Cstrong\u003EHERE.\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E \u003C\/strong\u003EEmail contact: indiaprogram@cc.gatech.edu. To learn more about available virtual meeting opportunities, visit \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/india\u0022\u003Ecc.gatech.edu\/india\u003C\/a\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDrop in during our Virtual Office Hour (over \u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_YWI1MWZmYzEtNTUxNy00MDlkLWE0ZmMtYzhiODEyMTg2Nzll%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%221f4e064b-0d3f-4bac-85b9-1ea00c689fe7%22%7d\u0022\u003ETeams\u003C\/a\u003E), \u003Cstrong\u003EWednesday, November 4, \u0026nbsp;6 to 7 pm. \u003C\/strong\u003E\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_YWI1MWZmYzEtNTUxNy00MDlkLWE0ZmMtYzhiODEyMTg2Nzll%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%221f4e064b-0d3f-4bac-85b9-1ea00c689fe7%22%7d\u0022\u003E\u003Cstrong\u003EJOIN HERE\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E.\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAsk questions about the CoC\u0027s newest program, \u0022Technology Design and Ethics in India,\u0022 \u003C\/strong\u003Ea 6-week program (May 17 - June 25, 2027), with 4 weeks of online instruction\u003Cstrong\u003E followed by\u0026nbsp;2 weeks of continued GT instruction in Mumbai, India.\u003C\/strong\u003E Drop in for a few minutes to ask your question or stay the whole hour and hear what other students are asking.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Join us for a November 4 for a virtual office hour (Teams) to answer questions about the College of Computing\u0027s newest embedded program."}],"uid":"27393","created_gmt":"2026-10-08 16:44:09","changed_gmt":"2026-10-08 16:52:46","author":"TaraBerry","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-04T18:00:00-05:00","event_time_end":"2026-11-04T19:00:00-05:00","event_time_end_last":"2026-11-04T19:00:00-05:00","gmt_time_start":"2026-11-04 23:00:00","gmt_time_end":"2026-11-05 00:00:00","gmt_time_end_last":"2026-11-05 00:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online over Teams","extras":[],"hg_media":{"680927":{"id":"680927","type":"image","title":"Mumbai.jpeg","body":null,"created":"1787159252","gmt_created":"2026-08-19 17:07:32","changed":"1787159252","gmt_changed":"2026-08-19 17:07:32","alt":"Sunset near Mumbai landmark.","file":{"fid":"265260","name":"Mumbai.jpeg","image_path":"\/sites\/default\/files\/2026\/08\/19\/Mumbai.jpeg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/08\/19\/Mumbai.jpeg","mime":"image\/jpeg","size":921612,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/08\/19\/Mumbai.jpeg?itok=dzcgu7Ka"}}},"media_ids":["680927"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"322011","name":"College of Computing Events"},{"id":"660383","name":"College of Computing International Programs"}],"categories":[],"keywords":[{"id":"193388","name":"Education Abroad, OIE, Office of International Education, Study Abroad, Scholarship, Fellowship"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"194684","name":"Free"},{"id":"1788","name":"Other\/Miscellaneous"},{"id":"26411","name":"Training\/Workshop"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003ETara Berry, indiaprogram@cc.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"691533":{"#nid":"691533","#data":{"type":"event","title":"Machine Learning Seminar Series | Story of 3 D\u2019s: Deep Image Prior, Diffusion Models, and Deep Linear Networks","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EIn this talk, first, I will dive into a purely unsupervised approach for inverse problems called deep image prior (DIP) that recovers images from limited\/corrupted measurements by learning neural networks at reconstruction time with no training data. Classical DIP suffers from severe overfitting and spectral bias effects. We present an analysis of when and how DIP recovers images from limited\/corrupted data by studying its learning dynamics in the kernel regime. We then propose a self-guided DIP that significantly outperforms classical DIP and is competitive against supervised and diffusion models (DMs) trained with a lot of data. Second, DMs, when exhibiting strong image reconstruction performance, often rely on domain-matched pretraining and large training sets. We propose TRACE, a trajectory-constrained reconstruction framework that replaces the pretrained DM with an untrained network optimized like in DIP and organizes reconstruction as a sequence of intermediate states. At each step, TRACE enforces stochastic proximal consistency (SPC) by inferring the reconstruction from a stochastically perturbed predecessor under measurement consistency, while proximally constraining the resulting estimate to its predecessor. A local Jacobian analysis characterizes how SPC regularizes the reconstruction. TRACE demonstrates strong performance against both untrained and pretrained neural-priors with the trajectory constraint improving even pretrained DM-based inverse solvers. Lastly, deep neural networks trained using gradient descent with fixed learning rate often operate in the regime of edge of stability (EOS), where the largest Hessian eigenvalue equilibrates about a stability threshold. Here, we analyze the learning dynamics of deep linear networks (DLNs) in deep matrix factorization beyond EOS, and show that loss oscillations follow a period-doubling route to chaos. Oscillations occur within a small subspace, whose dimension depends on the learning rate. The results help explain two key phenomena in deep networks: shallow models and simple tasks do not always exhibit EOS; and oscillations occur within top features.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E 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.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWhile we prefer you join in person, if you are unable to attend, join online at:\u003Cbr\u003E\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F98109284552%3Fpwd%3DCrXDIye86vmEtCywAV7wmjjz1LqEY8.1\u0026amp;data=05%7C02%7Cchrista.ernst%40research.gatech.edu%7Cf855c30755864c2523ed08df247a0fbe%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639269778791005773%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=yQ9gk2JiMi%2Fu9%2FzGYEznhF6Yu3n%2FivGY%2Ffv2FvYjC5g%3D\u0026amp;reserved=0\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/gatech.zoom.us\/j\/98109284552?pwd=CrXDIye86vmEtCywAV7wmjjz1LqEY8.1. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/98109284552?pwd=CrXDIye86vmEtCywAV7wmjjz1LqEY8.1\u003C\/a\u003E\u003Cbr\u003E\u003Cstrong\u003EMeeting ID: \u003C\/strong\u003E981 0928 4552\u003Cbr\u003E\u003Cstrong\u003EPasscode: \u003C\/strong\u003E947902\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;\u003Cstrong\u003EAll Seminars Held 12pm - 1pm in CODA\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Saiprasad Ravishankar - Departments of Computational Mathematics, Science and Engineering and Biomedical Engineering at Michigan State University"}],"uid":"27863","created_gmt":"2026-08-07 14:17:23","changed_gmt":"2026-10-07 16:48:55","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-15T12:00:00-04:00","event_time_end":"2026-10-15T13:00:00-04:00","event_time_end_last":"2026-10-15T13:00:00-04:00","gmt_time_start":"2026-10-15 16:00:00","gmt_time_end":"2026-10-15 17:00:00","gmt_time_end_last":"2026-10-15 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Building 9th floor Atrium \u0026 Virtual","extras":["free_food"],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"693133":{"#nid":"693133","#data":{"type":"event","title":"Machine Learning Center Special Seminar: Advancing Data-driven Science of Meditation for Improved Mental Health  ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EIn this talk, I will present some of our recent studies from the data-driven neuroscience of meditation (DANSOM) Lab. Our studies have helped quantify how meditation techniques impact human brain and health. The studies were conducted on new meditators over six weeks of practice with multiple meditation techniques including breath-focus and mantra-based meditation. Results showed improvements in various subjective stress and psychological measures and latencies in objective P300 speller tests (tied to cognitive performance) for meditating groups relative to a control group. Studies of neural dynamics for mantra-based meditation using Electroencephalography (EEG) revealed marked differences in alpha oscillatory dynamics for different mantras used during training. Complex mantras such as Hare Krishna may generate higher cognitive demands and induce more activating, attentionally focused meditative states with oscillatory patterns persisting after meditation, whereas simple mantras and breath-focus meditation promote more relaxed states. We also show the capability of machine learned models to distinguish cognitive\/meditative states as well as different types of meditation techniques over time across many subjects, which can enable future neurofeedback applications for improving mental health. Along with presenting results, we will also have a hands-on experience of the studied meditation techniques.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u0026nbsp;\u003C\/strong\u003E 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.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EWhile we prefer you join in person, if you are unable to attend, join online at\u003Cbr\u003E\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F93328955144%3Fpwd%3DqepbKpZ2pV9Jl0ocrT6JGbHCX169qw.1\u0026amp;data=05%7C02%7Cchrista.ernst%40research.gatech.edu%7Cf855c30755864c2523ed08df247a0fbe%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639269778791024803%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=IQVf9Frnh3m8HSMiPLpPyf2bapUF22WZksLpoGD%2FCy0%3D\u0026amp;reserved=0\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/gatech.zoom.us\/j\/93328955144?pwd=qepbKpZ2pV9Jl0ocrT6JGbHCX169qw.1. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/93328955144?pwd=qepbKpZ2pV9Jl0ocrT6JGbHCX169qw.1\u003C\/a\u003E\u003Cbr\u003E\u003Cstrong\u003EMeeting ID:\u003C\/strong\u003E 933 2895 5144\u003Cbr\u003E\u003Cstrong\u003EPasscode:\u003C\/strong\u003E 331085\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn this talk, I will present some of our recent studies from the data-driven neuroscience of meditation (DANSOM) Lab.\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Saiprasad Ravishankar - Departments of Computational Mathematics, Science and Engineering and Biomedical Engineering at Michigan State University"}],"uid":"27863","created_gmt":"2026-10-07 16:22:08","changed_gmt":"2026-10-07 16:27:26","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-15T15:00:00-04:00","event_time_end":"2026-10-15T16:00:00-04:00","event_time_end_last":"2026-10-15T16:00:00-04:00","gmt_time_start":"2026-10-15 19:00:00","gmt_time_end":"2026-10-15 20:00:00","gmt_time_end_last":"2026-10-15 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA C1315 Grant Park Conference Room \u0026 Zoom","extras":[],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"}],"categories":[],"keywords":[{"id":"187023","name":"go-data"},{"id":"172970","name":"go-neuro"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692815":{"#nid":"692815","#data":{"type":"event","title":"School of CSE Seminar Series: Eric C. Cyr","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Eric C. Cyr, distinguished scientist at Sandia National Laboratories\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 16, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Qi Tang\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EApplying Scientific Computing Perspectives to Neural Network Training\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EMachine 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.\u0026nbsp;\u003Cbr\u003E\u003Cbr\u003EThis 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 \u201coperator-split\u201d 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.\u003C\/p\u003E\u003Col\u003E\u003Cli data-list-item-id=\u0022e444084b295c08274aac2ae5c89867c46\u0022\u003EDash, et al., Optimizing distributed training on frontier for large language models. In ISC High Performance 2024 Research Paper Proceedings (39th Intl. Conference), 2024.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e12a4700cdf02da468ce75ef9de1295e8\u0022\u003ECyr, et al., Robust training and initialization of deep neural networks: An adaptive basis viewpoint, Mathematical and Scientific Machine Learning, 2020.\u0026nbsp;\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e38186f901128ae0f6e47b8ded42b379e\u0022\u003ESouthworth, et al. Multilevel Training for Kolmogorov Arnold Networks, arXiv:2603.04827, 2026 (submitted to SISC)\u003C\/li\u003E\u003C\/ol\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E 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.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Eric C. Cyr, distinguished scientist at Sandia National Laboratories\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 16, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Qi Tang\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003EApplying Scientific Computing Perspectives to Neural Network Training\u003C\/em\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"School of CSE hosts a seminar from Eric C. Cyr, distinguished scientist at Sandia National Laboratories"}],"uid":"36319","created_gmt":"2026-09-24 18:28:54","changed_gmt":"2026-10-07 15:54:24","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-16T14:00:00-04:00","event_time_end":"2026-10-16T15:00:00-04:00","event_time_end_last":"2026-10-16T15:00:00-04:00","gmt_time_start":"2026-10-16 18:00:00","gmt_time_end":"2026-10-16 19:00:00","gmt_time_end_last":"2026-10-16 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda, Room 114","extras":[],"hg_media":{"681372":{"id":"681372","type":"image","title":"Eric-Cyr.jpg","body":null,"created":"1791380754","gmt_created":"2026-10-07 13:45:54","changed":"1791380754","gmt_changed":"2026-10-07 13:45:54","alt":"CSE Seminar Eric Cyr","file":{"fid":"265753","name":"Eric-Cyr.jpg","image_path":"\/sites\/default\/files\/2026\/10\/07\/Eric-Cyr.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/07\/Eric-Cyr.jpg","mime":"image\/jpeg","size":30241,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/07\/Eric-Cyr.jpg?itok=4dij_dRj"}}},"media_ids":["681372"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"166983","name":"School of Computational Science and Engineering"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EQi Tang (qtang@gatech.edu)\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"692872":{"#nid":"692872","#data":{"type":"event","title":"SCS Colloquium - Zvi Galil ","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn January 2014, Georgia Tech launched an online Master of Science in Computer Science for under $7,000 \u2014 a fraction of the $40,000 charged by comparable public universities and $70,000 at private institutions. What began with 5 courses and 380 students has become, by every measure, the largest academic degree program in the world in any subject:\u0026nbsp;52\u0026nbsp;courses, 19,000 enrolled students, and 16,500 graduates \u2014 more than 7,000 in the last three years alone. Applications\u0026nbsp;doubled\u0026nbsp;in\u0026nbsp;the last 4 years\u0026nbsp;to\u0026nbsp;over\u0026nbsp;11,000\u0026nbsp;and are still climbing after more than a decade.\u003C\/p\u003E\u003Cp\u003EHarvard researchers concluded that OMSCS is the first rigorous evidence that an online degree program can increase educational attainment, projecting it will raise the number of annual MS CS graduates in the United States by at least 7%. The program has catalyzed more than 50 similar programs at over 30 universities worldwide. In November 2023, Forbes called it the best degree program ever.\u003C\/p\u003E\u003Cp\u003EThis talk describes how OMSCS came about, what Georgia Tech has learned from twelve years of running it, and what it reveals about the future of higher education \u2014 a future in which online learning plays a far larger and more consequential role than most institutions have yet imagined.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThis talk describes how OMSCS came about, what Georgia Tech has learned from twelve years of running it, and what it reveals about the future of higher education\u2014a future in which online learning plays a far larger and more consequential role than most institutions have yet imagined.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Professor Zvi Galil\u0027s talk will focus on Georgia Tech\u0027s online Master of Science in Computer Science (OMSCS). "}],"uid":"36532","created_gmt":"2026-09-28 18:35:23","changed_gmt":"2026-10-02 15:49:47","author":"Morgan Usry","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-09T11:00:00-04:00","event_time_end":"2026-10-09T12:00:00-04:00","event_time_end_last":"2026-10-09T12:00:00-04:00","gmt_time_start":"2026-10-09 15:00:00","gmt_time_end":"2026-10-09 16:00:00","gmt_time_end_last":"2026-10-09 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"KACB 1447","extras":[],"hg_media":{"681336":{"id":"681336","type":"image","title":"head-shot.jpg.jpeg","body":null,"created":"1790956148","gmt_created":"2026-10-02 15:49:08","changed":"1790956148","gmt_changed":"2026-10-02 15:49:08","alt":"Headshot of man","file":{"fid":"265712","name":"head-shot.jpg.jpeg","image_path":"\/sites\/default\/files\/2026\/10\/02\/head-shot.jpg.jpeg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/02\/head-shot.jpg.jpeg","mime":"image\/jpeg","size":11053484,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/02\/head-shot.jpg.jpeg?itok=wrRX16_c"}}},"media_ids":["681336"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"322011","name":"College of Computing Events"},{"id":"50875","name":"School of Computer Science"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"194683","name":"Talk"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692976":{"#nid":"692976","#data":{"type":"event","title":"IDEaS over Coffee: How Dangerous are Runaway AI Agents?  A Discussion about the OpenAI \/ HuggingFace Hacking Incident","body":[{"value":"\u003Cp\u003EIn July, OpenAI launched tens of thousands of agents as part of an experiment.\u0026nbsp; Many of them had been given an impossible task, and 1200 agents started communicating with each other about how to cheat.\u0026nbsp; 700 of them launched a coordinated attack against HuggingFace, a popular site for hosting AI models.\u0026nbsp; \u0026nbsp; An independent report of the incident is available from METR \u003Ca href=\u0022https:\/\/metr.org\/blog\/2026-08-26-openai-hugging-face-incident-investigation\/#~1200-agents-sent-%3E70,000-messages-and-files-on-an-unsanctioned-message-board,-and-~700-attacked-hugging-face\u0022\u003Ehere\u003C\/a\u003E.\u003C\/p\u003E\u003Cp\u003EPlease join us for coffee and an informal discussion of this incident and what it implies about AI safety and security.\u0026nbsp; We will be joined by members of the AI Safety Initiative, who hosted an event about this incident last month.\u003C\/p\u003E\u003Cp\u003EGeorgia 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.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EWe will be joined by members of the AI Safety Initiative, who hosted an event about this incident last month.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Please join us for coffee and an informal discussion of this incident and what it implies about AI safety and security."}],"uid":"27863","created_gmt":"2026-10-02 12:46:25","changed_gmt":"2026-10-02 12:49:23","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-26T14:00:00-04:00","event_time_end":"2026-10-26T15:30:00-04:00","event_time_end_last":"2026-10-26T15:30:00-04:00","gmt_time_start":"2026-10-26 18:00:00","gmt_time_end":"2026-10-26 19:30:00","gmt_time_end_last":"2026-10-26 19:30:00","rrule":null,"timezone":"America\/New_York"},"location":"IDEaS Suite CODA 12th Flr.","extras":["free_food"],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"545781","name":"Institute for Data Engineering and Science"}],"categories":[],"keywords":[{"id":"187023","name":"go-data"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"},{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EFor questions please contact \u003Ca href=\u0022mailto:ashley.edwards@gatech.edu\u0022\u003Eashley.edwards@gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"692814":{"#nid":"692814","#data":{"type":"event","title":"School of CSE Seminar Series: Pinar Yanardag Delul","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Pinar Yanardag Delul, assistant professor at Virginia Tech\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 9, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Polo Chau\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003ERethinking Memory: From Long-Horizon Video to Interactive World Models\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Video generation has made remarkable progress in visual quality, yet turning short clips into continuously evolving, controllable experiences remains a fundamental challenge. A model must preserve what matters from the past while allowing new events to unfold, respond to user input, and remain computationally efficient as generation unfolds. In this talk, I will explore these challenges through a central question:\u0026nbsp;What should a video model remember, and how should it use that memory?\u003Cbr\u003E\u003Cbr\u003EI will present three complementary approaches to rethinking memory in autoregressive video generation. First, Infinity-RoPE (CVPR\u201926) revisits how temporal context is organized, enabling longer video generation and more responsive control through inference-time interventions. Next, AdaState (NeurIPS\u201926) replaces a frozen anchor frame with an evolving latent state, balancing temporal consistency with dynamic scene progression. Finally, VideoMLA (NeurIPS\u201926) rethinks how video models store and access past context, substantially compressing their memory while preserving generation quality.\u003Cbr\u003E\u003Cbr\u003EI will close with broader directions toward controllable world models (SPAWN, NeurIPS\u201926), physically grounded (HiPhy, NeurIPS\u201926) and diverse (DPP-GRPO, CVPR\u201926) video generation models. This research advances a broader vision for generative cinematography, supported by an NSF CAREER\u201926 award, toward generative worlds that remember the past, respond to our choices, and evolve as we interact with them.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Pinar Yanardag is an Assistant Professor of Computer Science at Virginia Tech, where she leads GEMLAB (Generative Modeling Lab). Her research focuses on controllable and personalized generative AI, with an emphasis on video generation and interactive world models. Her goal is to build systems that give people greater creative control over generated content and experiences. Since joining Virginia Tech in Fall 2023, her lab has produced over 25 publications at venues including CVPR, ICCV, and NeurIPS. She completed her PhD at Purdue as a Fulbright Fellow and was a postdoctoral researcher at the MIT Media Lab, where her generative AI projects attracted over one million participants and coverage from TIME, The Washington Post, and CNN. She is a recipient of the NSF CAREER award for her research on generative cinematography, and her research has received support from industry partners including Google, Adobe, and Snap.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003ESpeaker:\u003C\/strong\u003E\u0026nbsp;Pinar Yanardag Delul, assistant professor at Virginia Tech\u003Cbr\u003E\u003Cstrong\u003EDate and Time:\u003C\/strong\u003E\u0026nbsp;October 9, 2:00-3:00 p.m.\u0026nbsp;\u003Cbr\u003E\u003Cstrong\u003ELocation:\u003C\/strong\u003E\u0026nbsp;Coda Building, Room 114\u003Cbr\u003E\u003Cstrong\u003EHost:\u003C\/strong\u003E\u0026nbsp;Polo Chau\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E\u0026nbsp;\u003Cem\u003ERethinking Memory: From Long-Horizon Video to Interactive World Models\u003C\/em\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"School of CSE hosts a seminar from Pinar Yanardag Delul, assistant professor at Virginia Tech"}],"uid":"36319","created_gmt":"2026-09-24 18:22:49","changed_gmt":"2026-10-01 14:31:17","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-09T14:00:00-04:00","event_time_end":"2026-10-09T15:00:00-04:00","event_time_end_last":"2026-10-09T15:00:00-04:00","gmt_time_start":"2026-10-09 18:00:00","gmt_time_end":"2026-10-09 19:00:00","gmt_time_end_last":"2026-10-09 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda, Room 114","extras":[],"hg_media":{"681321":{"id":"681321","type":"image","title":"Pinar-Yanardag.png","body":null,"created":"1790865045","gmt_created":"2026-10-01 14:30:45","changed":"1790865045","gmt_changed":"2026-10-01 14:30:45","alt":"CSE Seminar Pinar Yanardag","file":{"fid":"265696","name":"Pinar-Yanardag.png","image_path":"\/sites\/default\/files\/2026\/10\/01\/Pinar-Yanardag.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/10\/01\/Pinar-Yanardag.png","mime":"image\/png","size":148072,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/10\/01\/Pinar-Yanardag.png?itok=Jg-LGaGt"}}},"media_ids":["681321"],"groups":[{"id":"47223","name":"College of Computing"},{"id":"50877","name":"School of Computational Science and Engineering"}],"categories":[],"keywords":[{"id":"166983","name":"School of Computational Science and Engineering"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EPolo Chau (polo@gatech.edu)\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"692939":{"#nid":"692939","#data":{"type":"event","title":"Frontiers of Artificial Intelligence Seminar: CSLib: The Lean Computer Science Library ","body":[{"value":"\u003Cdiv\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Following Mathlib\u0027s success in building a shared foundation for formalized mathematics, CSLib is a community-oriented effort to build a similar infrastructure for computer science and software in the Lean theorem prover.\u003C\/p\u003E\u003Cp\u003EIn this talk, I will present CSLib\u0027s current state, including its architecture, governance, organization, and how to contribute. Rather than giving only a high-level overview, I will use minimal working examples to illustrate the library\u0027s current API. I will showcase abstractions and definitions already available, ranging from computational paradigms to modeling and programming languages, logics, algorithms, and infrastructure to verify their properties.\u003C\/p\u003E\u003C\/div\u003E\u003Cp\u003EI will also introduce the CSLib Initiative, supported by Renaissance Philanthropy, which aims to coordinate and accelerate the development of the library and its surrounding ecosystem. I will discuss the CSLib Initiative roadmap\u003C\/p\u003E\u003Cp\u003EFinally, I will show how CSLib is already being used beyond the library itself, through community projects, textbooks, courses, and large-scale verification efforts. These include Software Foundations in Lean, the Functional Algorithms Design and Computational Semantics with Lean, and the port of Amazon\u0027s s2n-bignum formal proofs to Lean.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio:\u003C\/strong\u003E Alexandre Rademaker is the Director of the CSLib Initiative at Renaissance Philanthropy. CSLib is a global open-source effort to build a library of formalized computer science in Lean. He also cooperates with NYU in DARPA\u0027s ExpMath program, which aims to accelerate mathematics research with AI.\u003C\/p\u003E\u003Cp\u003EAlexandre is also a professor at EMAp\/FGV (Applied Mathematics School, Getulio Vargas Foundation), where he has been teaching for about 20 years. He worked at IBM Research for 12 years until April 2025, when he left to lead the Specification IDE project at Atlas Computing, part of the Formal Verification of Software initiative funded by Schmidt Sciences under their Science of Trustworthy AI program.\u003C\/p\u003E\u003Cp\u003EDuring his PhD, he held research fellowships at Microsoft Research, working with the Z3 SMT solver team, and at SRI International. He has published more than 100 papers and spent much of his career leading open-source research collaborations with international communities, working with computational linguistics and building language resources. He was publication chair of the Language Resources and Evaluation Conference (LREC) and has served on the boards of research associations in Brazil and internationally.\u003C\/p\u003E\u003Cp\u003EAlexandre received a PhD in Computer Science from PUC-Rio, where his thesis on proof theory for description logics was published by Springer, and is based in Rio de Janeiro.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EIn this talk, I\u0026nbsp;will\u0026nbsp;present\u0026nbsp;CSLib\u0027s\u0026nbsp;current\u0026nbsp;state,\u0026nbsp;including\u0026nbsp;its\u0026nbsp;architecture,\u0026nbsp;governance,\u0026nbsp;organization,\u0026nbsp;and\u0026nbsp;how to contribute. Rather than giving only a high-level overview, I will use minimal working examples to illustrate the library\u0027s current API.\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Alexandre Rademaker - Professor, EMAp\/FGV (Applied Mathematics School, Getulio Vargas Foundation) "}],"uid":"27863","created_gmt":"2026-09-30 15:47:28","changed_gmt":"2026-09-30 16:08:59","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-05T15:00:00-04:00","event_time_end":"2026-10-05T16:00:00-04:00","event_time_end_last":"2026-10-05T16:00:00-04:00","gmt_time_start":"2026-10-05 19:00:00","gmt_time_end":"2026-10-05 20:00:00","gmt_time_end_last":"2026-10-05 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Classroom 2456 @ Klaus Advanced Computing Building and Virtual","extras":[],"related_links":[{"url":"https:\/\/gatech.zoom.us\/j\/99195619305?pwd=5vH1cHNyTRPP3vE9Dtlf48qA04laHM.1","title":"Access Via Zoom"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"545781","name":"Institute for Data Engineering and Science"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692780":{"#nid":"692780","#data":{"type":"event","title":" IDEaS Open House","body":[{"value":"\u003Cp\u003EMeet and mingle with old colleagues and make new ones at the IDEaS Open House.\u003C\/p\u003E\u003Cp\u003EJoin us for an informal gathering, tour our space and and learn more about our IRI and the latest in ML and AI research. This event is open to faculty, students, staff, and research professionals\u003C\/p\u003E\u003Cp\u003EThere will be refreshments and swag for all.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMeet and mingle with old colleagues and make new ones at the IDEaS Open House.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"October 8th | 1pm - 3pm "}],"uid":"27863","created_gmt":"2026-09-23 18:42:09","changed_gmt":"2026-09-23 18:44:40","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-08T13:00:00-04:00","event_time_end":"2026-10-08T15:00:00-04:00","event_time_end_last":"2026-10-08T15:00:00-04:00","gmt_time_start":"2026-10-08 17:00:00","gmt_time_end":"2026-10-08 19:00:00","gmt_time_end_last":"2026-10-08 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA: 12th floor IDEaS suite","extras":["free_food","freebies"],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"}],"categories":[],"keywords":[{"id":"187023","name":"go-data"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"691532":{"#nid":"691532","#data":{"type":"event","title":"Machine Learning Seminar Series Fall 2026 | Machine Learning with Hard Constraints","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EHow can we harness the expressive power of modern machine learning while ensuring that its outputs respect non-negotiable physical, safety, and operational constraints? Penalizing violations during training encourages compliance but does not guarantee it at deployment. In this talk, I will present a principled approach to incorporating hard constraints into both learning architectures and generative sampling. I will begin with hard-constrained neural networks (HardNets), which satisfy input-dependent constraints by construction while retaining universal approximation of feasible functions. I will then show how these ideas enable various applications, from learned models of chaotic dynamics with provably bounded trajectories through energy-constrained operator learning to scalable safe reinforcement learning and learning-based control with formal guarantees. Finally, I will turn to generative models, namely flow-matching and diffusion models, with hard inference-time constraints. By recasting constrained generation as a trajectory optimization problem, we can use receding-horizon control to steer pretrained models toward feasible outputs without unnecessarily restricting their sampling dynamics or requiring retraining. Applications spanning fluid dynamics, robotic control and planning, PDE control, and language-guided image editing illustrate a unifying principle: hard constraints should define what a model is allowed to do without unnecessarily limiting what it can learn or generate.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003ENavid Azizan is the Alfred H. (1929) and Jean M. Hayes Associate Professor at MIT, where he holds dual appointments in the Department of Mechanical Engineering (in Control, Instrumentation \u0026amp; Robotics) and the Schwarzman College of Computing\u0027s Institute for Data, Systems \u0026amp; Society (IDSS), and is a Principal Investigator in the Laboratory for Information \u0026amp; Decision Systems (LIDS). His research interests broadly lie in machine learning, systems and control, and mathematical optimization. His research lab focuses on various aspects of reliable AI systems, with applications to high-stakes and safety-critical settings. He obtained his PhD in Computing and Mathematical Sciences (CMS) from the California Institute of Technology (Caltech) in 2020, his MSc in electrical engineering from the University of Southern California in 2015, and his BSc in electrical engineering and physics from Sharif University of Technology in 2013. Prior to joining MIT, he completed a postdoc at Stanford University in 2021. Additionally, he was a research scientist intern at Google DeepMind in 2019. He is a recipient of several awards, including the National Science Foundation CAREER Award, research awards from Amazon, Google, and MathWorks, among others, and the inaugural Information Theory and Applications (ITA) \u201cSun\u201d (Gold) Graduation Award. His work has been recognized with best paper awards at several venues, including Learning for Dynamics and Control (L4DC), the INFORMS Junior Faculty Paper Competition, and ACM Greenmetrics. He was named in the list of Outstanding Academic Leaders in Data by the CDO Magazine for two consecutive years in 2024 and 2023. His teaching and mentorship have been recognized with the Joseph A. Martore (1975) Excellence in Teaching Award, the Frank E. Perkins Award for Excellence in Graduate Advising (MIT Institute Award), and the UROP Outstanding Mentor Award.\u003C\/p\u003E\u003Cp\u003EWhile we prefer you join in person, if you are unable to attend, join online at \u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F91508317626%3Fpwd%3DWrbKsZaW2tcby2uQdVcAjsYaX0FL8l.1\u0026amp;data=05%7C02%7Cchrista.ernst%40research.gatech.edu%7C629739afa1ee4ffabde608df19646000%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639257591021155940%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=KUKCk9bETO%2B4BvOaOeRKxXeuUfplNbs4veqLfh0zc2U%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/gatech.zoom.us\/j\/91508317626?pwd=WrbKsZaW2tcby2uQdVcAjsYaX0FL8l.1. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/91508317626?pwd=WrbKsZaW2tcby2uQdVcAjsYaX0FL8l.1\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003EMeeting ID: 915 0831 7626\u003Cbr\u003EPasscode: 647326\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAll Seminars Held 12pm - 1pm in CODA\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Navid Azizan, Massachusetts Institute of Technology \u2013 Department of Mechanical Engineering and Schwarzman College of Computing\u2019s Institute for Data, Systems \u0026 Society"}],"uid":"27863","created_gmt":"2026-08-07 14:12:11","changed_gmt":"2026-09-23 12:46:03","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-30T12:00:00-04:00","event_time_end":"2026-09-30T13:00:00-04:00","event_time_end_last":"2026-09-30T13:00:00-04:00","gmt_time_start":"2026-09-30 16:00:00","gmt_time_end":"2026-09-30 17:00:00","gmt_time_end_last":"2026-09-30 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Building 9th floor Atrium \u0026 Virtual","extras":[],"related_links":[{"url":"https:\/\/meche.mit.edu\/people\/faculty\/azizan@mit.edu","title":"MIT Webpage"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[{"id":"9167","name":"machine learning"},{"id":"187023","name":"go-data"},{"id":"188087","name":"go-irim"},{"id":"654","name":"College of Computing"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"691828":{"#nid":"691828","#data":{"type":"event","title":"\u0022Technology Design and Ethics in India\u0022 In-Person Information Session 2 - Fall 2026","body":[{"value":"\u003Cp\u003EJoin us for an in-person\u003Cstrong\u003E\u0026nbsp;Info Session, Tuesday, October 27, 11 am in CCB 052 \u0026nbsp;\u003C\/strong\u003E(no registration required). The program will be a \u003Cstrong\u003E6-week program (May 17 - June 25, 2027)\u003C\/strong\u003E, with \u003Cstrong\u003E4 weeks of instruction online, followed by\u0026nbsp;2 weeks of continued GT instruction in Mumbai, India. \u003C\/strong\u003EThe 2 foundational Computer Science courses of the program will be taught by Georgia Tech CS faculty and Program Director, Naveena Karusala.\u003C\/p\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Ch3\u003E\u003Cstrong\u003EProgram Courses:\u003C\/strong\u003E\u003C\/h3\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e0c65d4fdcbe0bb8043059f45f05b46db\u0022\u003E\u003Cstrong\u003ECS 4001 \u2013 Computing \u0026amp; Society (Ethics Credit) -\u0026nbsp;\u003C\/strong\u003EStudents will critically examine how issues around technology, such as globalization, bias, privacy, and others, affect people worldwide.\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e8deef437bb9d4bc7603f80d7941693b3\u0022\u003E\u003Cstrong\u003ECS 3751 \u2013 Intro to User Interface Design - \u003C\/strong\u003EStudents will explore culturally situated approaches to design and, through the course project, create an inventive design artifact.\u003C\/li\u003E\u003C\/ul\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EJoin us to learn more details about this opportunity to earn credit for foundational courses while gaining intercultural experience.\u003C\/div\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ENo questions and ready to go? Apply\u003C\/strong\u003E \u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fatlas.gatech.edu%2Findex.cfm%3FFuseAction%3DPrograms.ViewProgramAngular%26id%3D10313\u0026amp;data=05%7C02%7Ctara.berry%40cc.gatech.edu%7Ccba551394cb34f2cdb7a08de1ca899c8%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C638979708276911681%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=gc10GYpcKVWl%2BqV%2FEfTCL%2FDw76OC7CLpt3S0d8AHOkY%3D\u0026amp;reserved=0\u0022 id=\u0022OWA42e19520-ca26-f5dc-96d2-f08de680adc6\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/atlas.gatech.edu\/index.cfm?FuseAction=Programs.ViewProgramAngular\u0026amp;id=10313. Click or tap if you trust this link.\u0022\u003E\u003Cstrong\u003EHERE.\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E \u003C\/strong\u003EEmail indiaprogram@cc.gatech.edu for questions. To find out more about available virtual meeting opportunities, go to \u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/india\u0022\u003Ecc.gatech.edu\/india\u003C\/a\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EJoin us for an in-person\u003Cstrong\u003E\u0026nbsp;Info Session, Tuesday, October 27, 11 am in CCB 052.\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EWe will be discussing CoC\u0027s newest program, \u0022Technology Design and Ethics in India.\u0022 \u003C\/strong\u003EThe program will be a \u003Cstrong\u003E6-week program (May 17 - June 25, 2027)\u003C\/strong\u003E, with \u003Cstrong\u003E4 weeks of instruction online, followed by\u0026nbsp;2 weeks of continued GT instruction in Mumbai, India.\u003C\/strong\u003E The 2 foundational Computer Science courses of the program, CS 4001 and CS 3751, will be taught by Georgia Tech CS faculty and Program Director, Naveena Karusala. 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His parents are originally from Barcelona, and he grew up mostly in Princeton, New Jersey. Before coming to Wharton, he earned a doctorate in electrical engineering and computer science from MIT.\u003C\/p\u003E\u003Cp\u003EBoix-Adsera studies the learning processes of artificial intelligence models, such as ChatGPT, with the goal of improving their efficiency and reliability.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Ch4\u003E\u0026nbsp;\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAll Seminars Held 12pm - 1pm in CODA\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Enric Boix, Wharton School at University of Pennsylvania \u2013 Department of Statistics and Data Science"}],"uid":"27863","created_gmt":"2026-08-07 14:31:32","changed_gmt":"2026-08-13 14:18:23","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-12-02T12:00:00-05:00","event_time_end":"2026-12-02T13:00:00-05:00","event_time_end_last":"2026-12-02T13:00:00-05:00","gmt_time_start":"2026-12-02 17:00:00","gmt_time_end":"2026-12-02 18:00:00","gmt_time_end_last":"2026-12-02 18:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Building 9th floor Atrium \u0026 Virtual","extras":[],"related_links":[{"url":"https:\/\/eboix.github.io\/","title":"PI Website"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[{"id":"9167","name":"machine learning"},{"id":"654","name":"College of Computing"},{"id":"187023","name":"go-data"},{"id":"188087","name":"go-irim"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"691535":{"#nid":"691535","#data":{"type":"event","title":"Machine Learning Seminar Series Fall 2026 | Session VI","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETBA\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u0026nbsp;\u003C\/strong\u003EHal Daum\u00e9 III is a professor of computer science with appointments in the Maryland Language Science Center and the University of Maryland Institute for Advanced Computer Studies, where he is also the director of TRAILS. In addition to fairness and natural language processing, his research focuses on understanding computational properties of learning and language as well as trustworthy AI.\u003C\/p\u003E\u003Ch4\u003E\u0026nbsp;\u003C\/h4\u003E\u003Ch4\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/h4\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAll Seminars Held 12pm - 1pm in CODA\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Featuring | Hal Daum\u00e9, University of Maryland \u2013 Department of Computer Science"}],"uid":"27863","created_gmt":"2026-08-07 14:25:42","changed_gmt":"2026-08-13 14:17:03","author":"Christa Ernst","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-11T12:00:00-05:00","event_time_end":"2026-11-11T13:00:00-05:00","event_time_end_last":"2026-11-11T13:00:00-05:00","gmt_time_start":"2026-11-11 17:00:00","gmt_time_end":"2026-11-11 18:00:00","gmt_time_end_last":"2026-11-11 18:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA Building 9th floor Atrium \u0026 Virtual","extras":[],"related_links":[{"url":"https:\/\/www.trails.umd.edu\/daume","title":"Lab Website"}],"groups":[{"id":"322011","name":"College of Computing Events"},{"id":"1278","name":"College of Sciences"},{"id":"545781","name":"Institute for Data Engineering and Science"},{"id":"142761","name":"IRIM"}],"categories":[],"keywords":[{"id":"9167","name":"machine learning"},{"id":"187023","name":"go-data"},{"id":"654","name":"College of Computing"},{"id":"188087","name":"go-irim"},{"id":"193860","name":"Artifical Intelligence"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Cstrong\u003EFor CODA guest access, please contact \u003C\/strong\u003E\u003Ca href=\u0022mailto:shatcher8@gatech.edu\u0022\u003E\u003Cstrong\u003Eshatcher8@gatech.edu\u003C\/strong\u003E\u003C\/a\u003E\u003Cstrong\u003E at least 2 business days prior to the event.\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}