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SUMMARY:ECE RISE-AI SEMINAR SERIES: Dr. Jingfeng Wu
DESCRIPTION:Towards a Less Conservative Theory of Machine Learning: Unstable Optimization and Implicit Regularization\n\n\n\n\n\n\n\nAbstract: Deep learning’s empirical success challenges the “conservative” nature of classical optimization and statistical learning theories. Classical theory mandates small stepsizes for training stability and explicit regularization for complexity control. Yet\, deep learning leverages mechanisms that thrive beyond these traditional boundaries. In this talk\, I present a research program dedicated to building a less conservative theoretical foundation by demystifying two such mechanisms:  \n\n\n\n1. Unstable Optimization: I show that large stepsizes\, despite causing local oscillations\, accelerate the global convergence of gradient descent (GD) in overparameterized logistic regression.  \n\n\n\nDr. Jingfeng Wu\n\n\n\n2. Implicit Regularization: I show that the implicit regularization of early-stopped GD statistically dominates explicit $\ell_2$-regularization across all linear regression problem instances. \n\n\n\nI further showcase how the theoretical principles lead to practice-relevant algorithmic designs (such as Seesaw for reducing serial steps in large language model pretraining). I conclude by outlining a path towards a rigorous understanding of modern learning paradigms. \n\n\n\nBio: Dr. Jingfeng Wu is a postdoctoral fellow at the Simons Institute for the Theory of Computing at UC Berkeley. His research focuses on deep learning theory\, optimization\, and statistical learning. He earned his Ph.D. in Computer Science from Johns Hopkins University. Prior to that\, he received a B.S. in Mathematics and an M.S. in Applied Mathematics\, both from Peking University. In 2023\, he was recognized as a Rising Star in Data Science by the University of Chicago and UC San Diego. \n\n\n\nLocation details: Discovery Building – Research’s Link\, 2nd floor of Discovery Building (access through glass doors behind information desk)
URL:https://engineering.wisc.edu/event/ece-rise-ai-seminar-series-dr-jingfeng-wu/
LOCATION:Discovery Building\, 330 N. Orchard St.\, Madison\, Wisconsin\, 53715
CATEGORIES:Electrical & Computer Engineering,Seminar
ATTACH;FMTTYPE=image/jpeg:https://engineering.wisc.edu/wp-content/uploads/2026/02/2026-Faculty-Recruiting-Seminars-Plain-for-website.avif
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260310T160000
DTEND;TZID=America/Chicago:20260310T170000
DTSTAMP:20260404T215416
CREATED:20260227T172358Z
LAST-MODIFIED:20260227T172400Z
UID:10001479-1773158400-1773162000@engineering.wisc.edu
SUMMARY:CBE Seminar Series: Alexandra Bayles
DESCRIPTION:Alexandra BaylesChemical and Biomolecular EngineeringUniversity of DelewareNewark\, Delaware \n\n\n\nAdvective processing strategies for architecting functional soft materials\n\n\n\n\n\n\n\nNatural and engineered soft materials often derive their functionality from the hierarchical arrangement of chemically distinct building blocks. Self- and directed-assembly strategies that organize nano- and microscale elements into mesoscopic architectures have transformed our ability to realize materials with macroscopic properties superior to those of their individual components. However\, challenges associated with adapting these processes across diverse chemistries and production volumes can limit their practical utility and deployment in advanced manufacturing. In this context\, our research group leverages principles of chaotic advection to continuously architect functional soft materials. \n\n\n\nIn this talk\, I will describe how we design modular fluidic devices to sculpt the spatial distribution of building blocks along laminar streamlines. Inspired by static mixers optimized to layer polymeric melts\, these devices incorporate junctions that split\, rotate\, and recombine serpentine flows. We demonstrate the ability to assemble an extensive library of geometric patterns by ordering junctions in deliberate sequences. Serial combinations of certain junctions multiply patterns while preserving their relative spacing and orientation. This implementation of the baker’s transformation rapidly thins the characteristic feature size in layered\, fibrous\, and dendritic architectures. Combining junctions in parallel breaks symmetry\, providing access to previously unattainable voxelated structures. Because organization is primarily governed by rheology rather than chemistry\, these advective assembly processes provide an adaptable framework for patterning long-range order in extruded materials with rheologically similar precursors. We illustrate this versatility by processing viscoplastic materials to advance emerging applications. For extrusion-based 3D printing\, we sculpt multimaterial filaments in advective assembly nozzles prior to deposition. Preassembling lower levels of the hierarchy in flow circumvents challenges of layer-by-layer deposition\, including maintaining high throughput while preserving resolution. For soft actuator fabrication\, we organize contrasting polymer solutions in flow and secure distributions after extrusion via UV polymerization. Including specific moieties induces swelling in response to light\, temperature\, and salt stimuli\, while the mesoscale arrangement directs motion without delamination. For synthetic tissue engineering\, we exploit the gentle laminar flows organize mammalian cells in biomimetic\, fine architectures while mitigating shear-induced damage. Overall\, the modular extrusion platform expands the assembly toolbox\, unlocking new opportunities in designing functional soft and living materials.
URL:https://engineering.wisc.edu/event/cbe-seminar-series-alexandra-bayles/
LOCATION:Wisconsin
CATEGORIES:Chemical & Biological Engineering,Seminar
ATTACH;FMTTYPE=image/jpeg:https://engineering.wisc.edu/wp-content/uploads/2023/02/2023_CBE-sem-series-web-header-scaled.webp
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260312T160000
DTEND;TZID=America/Chicago:20260312T170000
DTSTAMP:20260404T215416
CREATED:20260115T160546Z
LAST-MODIFIED:20260311T131902Z
UID:10001406-1773331200-1773334800@engineering.wisc.edu
SUMMARY:ME 903 Graduate Seminar: Professor Harley Johnson
DESCRIPTION:The ME 903: Graduate Student Lecture Series features campus and visiting speakers who present on a variety of research topics in the field of mechanical engineering. Professor Harley Johnson is a professor at the University of Illinois – Urbana Champaign. \n\n\n\nPresentation Title: Defects in Quantum Materials and Perspectives on the Future of Quantum Computing \n\n\n\nAbstract: Electronic and quantum materials\, which are central to the development of devices for future applications in quantum information science\, host a variety of crystalline defects that give rise to interesting properties. In order to harness these properties for new applications\, it is necessary to understand the mechanics and physics of the defects and their interactions. \n\n\n\nIn this talk\, I will first present results on defects in layered two-dimensional materials\, including dislocations either in-plane or out-of-plane with respect to the 2D layered structure. Recently\, twisted multilayer 2D material structures have been of interest due to the presence of flat bands and other emergent properties — including unconventional superconductivity — associated with moiré superlattices. Periodic regions of crystalline commensurability making up these superlattices are now understood to be separated by interlayer dislocations\, with Burgers vectors and line directions in the plane of the 2D material\, and having either edge or screw character. Using density functional theory and quantum Monte Carlo-fitted total energy tight-binding calculations\, I show that out-of-plane relaxation of the structures makes possible unique helical dislocations in bilayer graphene\, and that the presence of these helical dislocation lines coincides precisely with the so-called magic-angle condition at which unconventional superconductivity is observed. I then describe a different dislocation structure\, with line direction oriented out-of-plane\, but which also has a helical structure. Such a screw dislocation\, which adopts a double-helix dislocation core configuration in bilayer structures\, is expected to create conditions for exotic transport properties in certain classes of layered topological insulator materials. \n\n\n\nI will then take a broader perspective and briefly describe some major efforts to scale up quantum applications\, focusing on an historic new public-private partnership developing in Chicago – the Illinois Quantum and Microelectronics Park. This effort will be discussed in the context of university\, national lab\, and industry partnerships across the region\, with a goal of describing opportunities for engagement and targets for the scale-up of quantum computing hardware and algorithms over the next 5-10 years. \n\n\n\nBio: Harley T. Johnson is a Founder Professor in Mechanical Science and Engineering at the University of Illinois Urbana-Champaign\, where he has been a member of the faculty since 2001. He is the Executive Director and CEO of the Illinois Quantum and Microelectronics Park\, a $1B+ public-private partnership dedicated to scale-up of quantum computing\, located on 128 acres of the former US Steel Southworks site in Chicago. From 2019-2024 he served as the Associate Dean for Research in The Grainger College of Engineering\, a role in which he oversaw and supported the $320M annual research portfolio in Engineering at UIUC. In this position he supported faculty research\, led corporate relations\, and oversaw all major engineering partnerships with the federal funding agencies. \n\n\n\nJohnson’s research focuses on electronic and quantum materials\, addressing the role of defects and deformation in their functional properties. He served as PI and Director of the Illinois Materials Research Science and Engineering Center (I-MRSEC)\, an $18M NSF center (2023-2029) focused on fundamental research in electronic\, ionic\, and quantum materials. In 2019 he founded the NSF “DIGI-MAT” Center on Materials and Data Science\, based in UIUC’s National Center for Supercomputing Applications (NCSA). He has received the NSF CAREER Award\, the ASME Thomas J. R. Hughes Young Investigator Award\, and is a former Fulbright US Scholar. Johnson has received numerous recognitions for his teaching\, and campus awards for his leadership in diversity\, and for outstanding faculty leadership. In 2021 he received the University of Illinois Presidential Medallion for his leadership efforts during the Covid-19 pandemic. He is a Fellow of ASME and a Fellow of the Society of Engineering Science (SES). He received his graduate degrees from Brown University\, and his undergraduate degree from Georgia Tech.
URL:https://engineering.wisc.edu/event/me-903-graduate-seminar-professor-harley-johnson/
LOCATION:3M Auditorium\, rm 1106 Mechanical Engineering Building\, 1513 University Ave\, Madison\, 53711
CATEGORIES:Mechanical Engineering,Seminar
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DTSTART;TZID=America/Chicago:20260313T120000
DTEND;TZID=America/Chicago:20260313T130000
DTSTAMP:20260404T215416
CREATED:20260120T211905Z
LAST-MODIFIED:20260311T132018Z
UID:10001422-1773403200-1773406800@engineering.wisc.edu
SUMMARY:Mechanics Seminar: Professor Xiaobo Tan
DESCRIPTION:The Mechanics Seminar Series is a weekly seminar given by campus and visiting speakers on topics across the spectrum of mechanics research (solids\, fluids\, and dynamics). Professor Xiaobo Tan is a professor at Michigan State University. \n\n\n\nPresentation Title: Control of Underwater Robots with Localization Constraints \n\n\n\nAbstract: A key challenge for underwater robots and vehicles is the difficulty in obtaining location measurements for them or for targets they are tasked to track. In this talk I will share a few examples of our recent work on control of underwater robots with localization constraints. I will first discuss a distributed estimation approach to cooperative localization\, where a group of robots need to track a moving target (e.g.\, an acoustically tagged fish) based on time-difference-of-arrivals (TDOAs) of a signal emitted by the target. Then I will introduce a control barrier function approach to the incorporation of observability constraints and show its application to target tracking with only the range measurement. Finally\, I will present the problem of adaptive sampling under localization uncertainties\, and discuss how a multi-fidelity Gaussian process model is instrumental for best utilizing the measurement data for the reconstruction of the environmental field being sampled. Experimental results will be shown to illustrate the approaches. \n\n\n\nBio: Dr. Xiaobo Tan is an MSU Research Foundation Distinguished Professor and the Richard M. Hong Endowed Chair in Electrical and Computer Engineering at Michigan State University. He received his Bachelor’s and Master’s degrees in automatic control from Tsinghua University\, Beijing\, China\, in 1995\, 1998\, respectively\, and his Ph.D. in electrical and computer engineering from the University of Maryland in 2002. His research interests include underwater robotics\, soft robotics\, smart materials\, and control systems. He has published over 300 papers and been awarded 7 US patents in these areas. Dr. Tan is a Fellow of IEEE and ASME. He was a recipient of the NSF CAREER Award (2006)\, MSU Teacher-Scholar Award (2010)\, MSU College of Engineering Withrow Distinguished Scholar Award (2018)\, Distinguished Alumni Award from the Department of Electrical and Computer Engineering at University of Maryland (2018)\, MSU William J. Beal Outstanding Faculty Award\, and multiple best paper awards. Dr. Tan is keen to integrate his research with educational and outreach activities\, and has served as the PI of an NSF Research Traineeship (NRT) program on addressing real-world water problems (2023-2028)\, Director of an NSF-funded Research Experiences for Teachers (RET) Site program (2009 – 2016)\, and Curator of a robotic fish exhibit at MSU Museum (2016-2017). He has served the professional community in different capacities\, including the Editor-in-Chief of IEEE/ASME Transactions on Mechatronics\, a member of ASME Dynamic Systems and Control Division Executive Committee\, and the general chair of 2018 ASME Dynamic Systems and Control Conference and 2023 American Control Conference.
URL:https://engineering.wisc.edu/event/mechanics-seminar-professor-xiaobo-tan/
LOCATION:1227 Engineering Hall\, 1415 Engineering Drive\, Madison\, WI\, 53706\, United States
CATEGORIES:Mechanical Engineering,Seminar
ATTACH;FMTTYPE=image/jpeg:https://engineering.wisc.edu/wp-content/uploads/2024/08/Event-Graphics-for-Calendar-11-jpg.avif
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260313T120000
DTEND;TZID=America/Chicago:20260313T130000
DTSTAMP:20260404T215416
CREATED:20260227T161039Z
LAST-MODIFIED:20260227T161338Z
UID:10001477-1773403200-1773406800@engineering.wisc.edu
SUMMARY:ECE RISE-AI SEMINAR SERIES: Kunhe Yang
DESCRIPTION:Designing and Evaluating AI Algorithms in Strategic Environments\n\n\n\n\n\n\n\nKunhe Yang\n\n\n\nAbstract: As AI models are increasingly deployed in environments shaped by complex human behaviors\, there is a critical need for algorithmic principles that account for human values and strategic incentives. In this talk\, I will introduce my research on the theoretical foundations for designing and evaluating AI in human-centered strategic environments. I will focus on two key representative lines of my research: first\, I will discuss incentive-aware evaluation\, with the goal of designing metrics that remain robust even when they become targets of optimization. I will illustrate this in the context of online probability forecasting and introduce algorithmic principles for designing calibration measures that incentivize truthful predictions. Second\, I will discuss AI alignment with heterogeneous human preferences by introducing a framework called the distortion of AI alignment. Within this framework\, I will characterize the information-theoretic limits of learning from sparse heterogeneous feedback\, and compare the robustness of different alignment approaches including RLHF and NLHF. I conclude by discussing future directions and a broader vision for integrating these algorithmic principles into the design of trustworthy\, human-centric AI. \n\n\n\nBio: Kunhe Yang is a fifth-year PhD candidate in Electrical Engineering and Computer Sciences at the University of California\, Berkeley\, where she is advised by Professor Nika Haghtalab. Her research focuses on the theoretical foundations of AI in human-centered environments by drawing on tools from machine learning theory and algorithmic economics. Her work has been recognized by several awards\, including EECS Rising Star\, invited speaker at the Cornell Young Researchers workshop\, finalist for the Meta Research PhD Fellowship in the Economics and Computation track\, and a SIGMETRICS best paper award. \n\n\n\nLocation details: Discovery Building – Research’s Link\, 2nd floor of Discovery Building (access through glass doors behind information desk)
URL:https://engineering.wisc.edu/event/ece-rise-ai-seminar-series-kunhe-yang/
LOCATION:Discovery Building\, 330 N. Orchard St.\, Madison\, Wisconsin\, 53715
CATEGORIES:Electrical & Computer Engineering,Seminar
ATTACH;FMTTYPE=image/jpeg:https://engineering.wisc.edu/wp-content/uploads/2026/02/2026-Faculty-Recruiting-Seminars-Plain-for-website.avif
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