Past events

Abstract

Generative AI is shaping the future of work, but unevenly. Although AI tool use is becoming increasingly common, assessment and learning practitioners remain split between enthusiasm and horror. In this talk, we'll first explore how pre-employment assessment is being transformed by the proliferation of generative AI, including both the innovative psychometric assessments being developed and the growing worries about new avenues for applicant cheating. Second, we'll explore how these same assessment challenges are influencing learning and development professionals, initially through similar concerns about cheating, but increasingly through innovative uses of generative AI to provide ongoing developmental support to workers. This section will include discussion of an ongoing DoD-funded project at the United States Naval Academy.

Biography

Richard N. Landers, Ph.D., is the John P. Campbell Distinguished Professor of Industrial-Organizational Psychology at the University of Minnesota and Principal Investigator of TNTLAB (Testing New Technologies in Learning, Assessment and Behavior). His research is interdisciplinary and concerns the use of innovative technologies like artificial intelligence, games, and gamification to improve psychometric assessment, employee selection, adult learning, and research methods. He is a Fellow of the Society for Industrial and Organizational Psychology (SIOP), American Psychological Association, and Association for Psychological Science, as well as President-Elect (2025-2026) of SIOP. He is the incoming editor of Technology, Mind, and Behavior (2025 IF 3.2), an interdisciplinary gold open access journal published by the American Psychological Association at the intersection of psychology and computer science.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Molly Steenson (American Swedish Institute), will be giving a talk titled "How Architects Generated Generativity"

Abstract

How can we understand generative AI through the lens of architectural history? Beginning in the 1960s, architects collaborated with AI researchers and engineers, referencing writings about AI in their work on systems that generate systems. In this talk, Molly Wright Steenson traces the conceptual roots of generative AI in the 1960s–80s work of Christopher Alexander, Sara Ishikawa, Nicholas Negroponte, Cedric Price, and others, in work that draws from archival research in architecture and AI. How might our approach to building generative systems change if we understand them as part of a longer conversation between architecture and AI?

Biography

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During each session, the graduate staff will review:

• Requirements (general)
• Applying
• Prerequisite requirements
• What makes a strong applicant
• Funding
• Resources
• Common questions
• Questions from attendees

Students considering the following programs should attend:

• Computer Science M.S.
• Computer Science M.C.S.
• Computer Science Ph.D.
• Data Science M.S.
• Data Science Post-Baccalaureate Certificate

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Jon Froehlich (University of Washington), will be giving a talk titled "Human-AI for Physical World Accessibility"

Abstract

“Does the café entrance look accessible? Are there curb ramps along my route?” Digital maps have revolutionized how people move about the physical world but fail to support individual needs—routing wheelchair users along non-traversable paths, showing maps without screenreader support, or recommending inaccessible activities. In my lab, we create Human-AI systems that leverage human insight with computer vision and emerging GeoAI methods to transform physical world accessibility. I will describe our ambitious vision to map and assess every sidewalk in the world via remote crowdsourcing and computer vision (Project Sidewalk, RampNet), to make street-level imagery accessible via multimodal LLMs (StreetReaderAI), and to support complex physical tasks like cooking and sports via real-time visual augmentations in AR headsets (CookAR, ARSports). We envision a new class of interactive accessibility agents that sense, understand, and reason about physical spaces in real-time, providing personalized guidance adapted to each user's unique abilities and preferences.

Biography

Jon is a Professor in the Allen School of Computer Science at the University of Washington (UW), a part-time Visiting Faculty Researcher at Google Research, and co-founder of projectsidewalk.org, a Crowd+AI platform for urban accessibility analytics. His research in Human-Centered AI and Accessibility has produced 140+ scientific publications; 23 have received awards, including seven Best Papers at CHI and ASSETS—the top venues in their respective areas—and a 10-Year Impact Award at UbiComp. His work has been honored with the Sloan Fellowship, Google Faculty Award (3x), NSF CAREER Award, UW College of Engineering Outstanding Faculty Award, and the PacTrans Outstanding Researcher Award. At UW, he directs the Makeability Lab under the broad mission “to build and study interactive technology for a social purpose.”
 

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Thyaga Nandagopal (Samsung Research America), will be giving a talk titled "Shaping the Future: 6G Networks and AI-Native Innovations for Seamless Connectivity"

Abstract

The evolution of wireless communication has consistently delivered transformative "WoW" experiences, from 1G voice to 5G broadband. As we transition to 6G, the focus shifts toward AI-native networks, energy efficiency, and new revenue opportunities. This talk explores key advancements, including eXtreme MIMO, Sub-Band Full Duplex (SBFD), and Non-Terrestrial Networks (NTN), ensuring ubiquitous coverage. It also highlights the role of AI in optimizing network performance, reducing pilot overhead, and enabling distributed inference. With 3GPP discussions on 6G beginning in 2025, this talk provides insights into spectral efficiency, energy-saving designs, and the integration of Intelligent Sensing and Communication (ISAC) – with the ultimate goal of enhancing your understanding of how 6G will redefine user experiences, and pave the way for a smarter, more sustainable future.

Biography

Dr. Thyaga Nandagopal heads the Emerging Technologies Group at Samsung Research America, the research division of Samsung Electronics. His team is responsible for identifying new technology trends, sourcing external innovations to benefit Samsung products and incubating novel product concepts. Prior to joining Samsung in 2025, he was the inaugural Division Director of the Division of Innovation and Technology Ecosystems in the new Directorate of Technology, Innovation and Partnerships at the National Science Foundation. In this role, with an annual budget of over $350M, he oversaw NSF investments in convergent and translational research in emerging technologies and in building inclusive innovation ecosystems around the country. Dr. Nandagopal served as the co-chair of the NSF-wide Quantum Leap Steering Committee, and served on the NSF-wide Semiconductor Steering Committee. He held various leadership roles within the NSF Directorate of Computer & Information Science and Engineering (CISE), where he oversaw the annual budgets of nearly $200M and initiated over 18 public-private partnership programs spanning research, testbed infrastructure, and workforce development in emerging technology areas, bringing in over $150M from external partners into NSF-funded research programs. He started at NSF as a Program Director in the Networking Technologies and Systems (NeTS) program, and spent a decade at Bell Labs in New Jersey. He holds over 30 patents on software-defined networks and wireless technologies. He is an IEEE Fellow, and holds a Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Aniket Kittur (Carnegie Mellon University), will be giving a talk titled "Scaling Serendipity: A SMART Framework for AI-Augmented Innovation"

Abstract

Finding novel ideas and translating them into viable, impactful solutions is critical to solving the many complex problems faced by society today. However, this process of innovation is frequently impeded by cognitive and computational bottlenecks ranging from searching for ideas in distant fields to derisking and evaluating the viability of those ideas. This talk presents a framework that accelerates this process by strategically augmenting human ingenuity with artificial intelligence. Drawing upon over a decade of research in computational and crowd-augmented creativity, I will discuss approaches for: (1) decomposing analogical ideation to scale it beyond individual limits; (2) advances in exploring distant conceptual spaces, including using crowds, embeddings, and LLMs; and (3) going beyond ideation to transferring and evaluating early-stage concepts by partnering AI tools with deep, tacit knowledge from experts. I will present empirical results from studies in the lab as well as industry deployments demonstrating significant increases in the novelty and viability of generated concepts for individuals and teams. This work moves towards a future of accelerating innovation through systematized serendipity: a validated, scalable model for building a more predictable and disruptive R&D engine.

Biography

Aniket "Niki" Kittur is a Professor in the Human-Computer Interaction Institute at Carnegie Mellon University. His research on AI-augmented cognition looks at how we can accelerate knowledge acquisition and innovation by partnering human and machine intelligence. He has authored and co-authored over 100 papers, 17 of which have received best paper awards or honorable mentions. Dr. Kittur has been inducted into the CHI Academy, has received an NSF CAREER award, the Allen Newell Award for Research Excellence, major research grants from NSF, NIH, Google, Microsoft, Bosch, and Toyota, and his work has been reported in venues including Nature News, The Economist, The Wall Street Journal, NPR, TechCrunch, and the Chronicle of Higher Education. He received a BA in Psychology and Computer Science at Princeton, and a PhD in Cognitive Psychology from UCLA.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Darren Cofer (Collins), will be giving a talk titled "AI for Safety-Critical Systems"

Abstract

Biography

Darren Cofer is a Principal Fellow at Collins Aerospace. He earned his PhD in Electrical and Computer Engineering from The University of Texas at Austin.  His area of expertise is developing and applying advanced analysis methods and tools for verification and certification of high-integrity systems. He is currently leading the Collins team on DARPA’s PROVERS program, developing and applying formal methods for verification of safety and security properties in autonomous air vehicles. He served on RTCA committee SC-205 developing new certification guidance for airborne software (DO-178C) and was one of the developers of the Formal Methods Supplement (DO-333). He is currently a member of SAE committee G-34 developing certification guidance for the use of machine learning technologies onboard aircraft. 
 

Abstract

We all wear clothes, but most people don't think about what they do, how they are made, or how they are managed and sold. This talk will explore next generation clothing that learns from and responds to the wearer's body, as well as open questions where computational approaches can transform the clothing we currently wear, including sizing and fit, marketing and recommendation, and circularity of the fashion supply chain. 

Biography

Lucy E. Dunne, Ph.D., is a professor in the Department of Design, Housing, and Apparel in the College of Design at the University of Minnesota. She is also co-director of the Wearable Technology Lab. Dunne is a co-author (with Susan Watkins) of "Functional Apparel Design: From Sportswear to Space Suits" (Fairchild Books, 2015). Her research is focused on wearability and garment-based wearable technology, and explores new functionality in apparel, human-device interfaces, production and manufacture, and human factors of wearable products. Dunne has received the National Science Foundation’s CAREER award and the NASA Silver Achievement Medal for her work with functional clothing and wearable technology.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Pavlo Pylyavskyy (UMN School of Mathematics), will be giving a talk titled "Incidences and Tilings"

Abstract

Biography

Professor Pavlo Pylyavskyy is a mathematician at the University of Minnesota–Twin Cities whose research in algebraic combinatorics bridges geometry, representation theory, and combinatorics with applications spanning physics, statistics, and data science. Since joining the faculty in 2010, he has authored over 40 research papers on topics including geometric configurations, geometric crystals, and solitons, while mentoring fourteen graduate students and postdoctoral associates. His contributions to mathematics research and education have been recognized with a Sloan Fellowship (2013), an NSF CAREER Award (2014), and most recently a Simons Fellowship, making him the twelfth School of Mathematics professor at Minnesota to receive this prestigious honor since the program's inception in 2012.

The computer science colloquium takes place on Mondays from 11:15 a.m. - 12:15 p.m. This week's speaker, Stephen Wright (UW Madison), will be giving a talk titled "Optimization in Theory and Practice"

Abstract

Algorithms for continuous optimization problems have a rich history of design and innovation over the past several decades, in which mathematical analysis of their convergence and complexity properties plays a central role. Besides their theoretical properties, optimization algorithms are interesting also for their practical usefulness as computational tools for solving real-world problems. There are often gaps between the practical performance of an algorithm and what can be proved about it. These two facets of the field — the theoretical and the practical — interact in fascinating ways, each driving innovation in the other. This work focuses on the development of algorithms in two areas — linear programming and unconstrained minimization of smooth functions — outlining major algorithm classes in each area along with their theoretical properties and practical performance, and highlighting how advances in theory and practice have influenced each other in these areas.  In discussing theory, we focus mainly on non-asymptotic complexity, which are upper bounds on the amount of computation required by a given algorithm to find an approximate solution of problems in a given class.

Biography

Stephen J. Wright is the George B. Dantzig Professor of Computer Sciences, Sheldon Lubar Chair of Computer Sciences, and Hilldale Professor at the University of Wisconsin-Madison. He recently served a term as Chair of the Computer Sciences Department. His research is in computational optimization and its applications to data science and many other areas of science and engineering.

Prior to joining UW-Madison in 2001, Wright held positions at North Carolina State University (1986-1990) and Argonne National Laboratory (1990-2001). He has served as Chair of the Mathematical Optimization Society (MOS) from 2007-2010 and was elected to the Board of Trustees of SIAM for the maximum three terms, from 2005-2014. He was elected to the National Academy of Engineering in 2024. In the same year, he received the George B. Dantzig Prize, awarded jointly by MOS and SIAM, for "original research having a major impact on mathematical optimization."  He has been invited to give a plenary lecture at ICM 2026. In 2020, he was awarded the Khachiyan Prize by the INFORMS Optimization Society for "lifetime achievements in the area of optimization," and also received the NeurIPS Test of Time Award.  He became a Fellow of SIAM in 2011. In 2014, he won the W.R.G. Baker Award from IEEE for best paper in an IEEE archival publication during 2009-2011.

Wright is the author / coauthor of widely used text and reference books in optimization including "Primal Dual Interior-Point Methods" and "Numerical Optimization." He has published broadly on optimization theory, algorithms, software, and applications.

Wright served from 2014-2019 as Editor-in-Chief of the SIAM Journal on Optimization and previously served as Editor-in-Chief of Mathematical Programming Series B. He has also served as Associate Editor of Mathematical Programming Series A, SIAM Review, SIAM Journal on Scientific Computing, and several other journals and book series.