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DTSTART;TZID=America/Chicago:20250303T113000
DTEND;TZID=America/Chicago:20250303T123000
DTSTAMP:20250312T211752
CREATED:20250220T135945Z
LAST-MODIFIED:20250226T182151Z
UID:10001181-1741001400-1741005000@engineering.wisc.edu
SUMMARY:ISyE Engineering Robust & Scalable AI for Healthcare Systems
DESCRIPTION:Artificial intelligence (AI) is increasingly used in healthcare to enhance clinical decision-making\,optimize operations\, and improve patient outcomes. However\, real-world deployment of AIsystems presents fundamental engineering challenges\, including dataset shifts\, physician-AIteam dynamics\, and the need for continuous model validation and updating. These challengesthreaten the reliability and scalability of AI tools\, limiting their ability to provide consistent valuein clinical environments. \n\n\n\nIn this talk\, I will present engineering solutions that address these core challenges and enablethe development of AI systems that are both scalable and safe. First\, I will discuss techniquesfor integrating longitudinal patient data into predictive models\, improving their performanceover time. Second\, I will introduce methods to detect and mitigate dataset shifts\, ensuringmodels maintain accuracy when transitioning from development to real-world use. Finally\, I willdescribe a novel rank-based compatibility measure and optimization framework that improvesmodel updating while preserving physician trust and workflow stability. \n\n\n\nBy developing these foundational methods\, my work moves healthcare AI from an artisanal\,model-by-model approach to a scalable engineering discipline. I will conclude by discussingfuture research directions\, including AI personalization for individual physicians and thedevelopment of interactive AI validation systems that continuously adapt based on clinicianfeedback. \n\n\n\n\n\nBio: Erkin Ötleş\, MD\, PhD\, is an engineer with deep medical expertise\, specializing in developingmethods to create scalable and robust artificial intelligence systems for healthcare. Hisresearch addresses the core engineering challenges of AI deployment in real-world clinicalsettings—detecting and mitigating dataset shifts\, designing AI systems that integrateseamlessly into physician workflows\, and creating novel methods for continuous validation andmodel updating. \n\n\n\nDr. Ötleş has developed innovative machine learning techniques to model longitudinal patienttrajectories\, optimize human-AI collaboration in clinical decision-making\, and enhance thesafety and interpretability of AI tools in high-stakes environments. His work has been publishedin leading medical (JAMA Internal Medicine\, The BMJ) and engineering (Machine Learning forHealthcare\, Journal of the American Medical Informatics Association) venues\, demonstratinghis ability to bridge theoretical advancements with practical implementation. His research hasalso been widely covered by the lay press\, including NPR\, WIRED\, and STAT News\,underscoring its broad societal impact. \n\n\n\nAs an engineer and a physician\, Dr. Ötleş brings a unique systems perspective to AI inhealthcare. His work aims to transition healthcare AI development\, evaluation\, andimplementation from an artisanal\, model-by-model process to a scalable engineering discipline—ensuring that AI tools used in medicine are not only powerful and plentiful but also safe\,reliable\, and adaptable to dynamic clinical environments.
URL:/event/engineering-robust-scalable-ai-for-healthcaresystems/
LOCATION:1153 Mechanical Engineering\, 1513 University Ave\, Madison\, WI\, 53706\, United States
CATEGORIES:Colloquium,Industrial & Systems Engineering
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250303T120000
DTEND;TZID=America/Chicago:20250303T130000
DTSTAMP:20250312T211752
CREATED:20250204T171959Z
LAST-MODIFIED:20250211T191336Z
UID:10001143-1741003200-1741006800@engineering.wisc.edu
SUMMARY:BME Seminar Series: Jacob Witten\, PhD
DESCRIPTION:Artificial intelligence for state-of-the-art gene therapy\n\n\n\n\n\n\n\nJacob Witten\, PhDPostdoctoral FellowAnderson LabMassachusetts Institute of Technology \n\n\n\nAbstract:Lipid nanoparticles (LNPs) for RNA delivery have exploded onto the biomedical research scene with the success of mRNA vaccines for COVID-19. In addition to their promise as mRNA vaccines for infectious disease and cancer\, LNPs have the potential to treat or cure patients with deadly lung diseases such as cystic fibrosis. However\, gene therapy in the lung is a notoriously difficult challenge that has frustrated decades of researchers. Here\, I take two approaches to identifying LNPs capable of addressing this challenge. First\, I developed an in vitro primary cell platform to screen LNPs for lung mRNA delivery and identify two state-of-the-art LNPs for respiratory tract delivery to mice. Second\, I developed Lipid Optimization using Neural networks (LiON)\, a deep learning strategy for LNP design. Using LiON I evaluated 1.6 million possible LNPs and identified two\, FO-32 and FO-35\, with mRNA delivery matching that of LNPs in ongoing clinical trials. Overall\, this work shows the potential of deep learning to bring gene therapy to patients suffering from genetic disease. \n\n\n\nPrint PDF
URL:/event/bme-seminar-series-jacob-witten-phd/
LOCATION:1003 (Tong Auditorium) Engineering Centers Building\, 1550 Engineering Drive\, Madison\, WI\, 53706\, United States
CATEGORIES:Biomedical Engineering,Seminar
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ORGANIZER;CN="Department of Biomedical Engineering":MAILTO:bmehelp@bme.wisc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250303T120000
DTEND;TZID=America/Chicago:20250303T130000
DTSTAMP:20250312T211752
CREATED:20250225T204331Z
LAST-MODIFIED:20250227T164335Z
UID:10001190-1741003200-1741006800@engineering.wisc.edu
SUMMARY:ECE RISE SEMINAR SERIES: Trustworthy AI – Dr. Lydia Zakynthinou
DESCRIPTION:2534 Engineering Hall \n\n\n\nAlgorithmic Stability for Trustworthy Machine Learning and Statistics\n\n\n\nAbstract:Data-driven systems hold immense potential to positively impact society\, but their reliability remains a challenge. Their outputs are often too brittle to changes in their training data\, leaving them vulnerable to data poisoning attacks\, prone to leaking sensitive information\, or susceptible to overfitting. Establishing fundamental principles for designing algorithms that are both stable—to mitigate these risks—and efficient in their use of resources is essential for enabling trustworthy data-driven systems.In this talk\, I will focus on statistical estimation under differential privacy—a rigorous framework that ensures data-driven system outputs do not reveal sensitive information about individuals in their input. I will present algorithmic techniques that take advantage of beneficial structure in the data to achieve optimal error for several multivariate tasks without requiring any prior information about the data\, by building on robustness against data poisoning attacks. Lastly\, I will highlight the deeper connection between differential privacy and robustness that underpins these results. \n\n\n\n\n\n\n\nBio:Lydia Zakynthinou is a FODSI postdoctoral research fellow in the Simons Institute for the Theory of Computing at UC Berkeley\, hosted by Michael I. Jordan. She earned her Ph.D. in Computer Science from Northeastern University under the supervision of Jonathan Ullman and Huy Nguyen. Her research lies in trustworthy machine learning and statistics\, with a focus on data privacy and generalization\, and has been recognized with a Meta PhD fellowship and a Khoury PhD Research Award. She holds a diploma in Electrical and Computer Engineering from NTUA and a MSc in Logic\, Algorithms\, and Theory of Computation from NKUA in Greece.
URL:/event/ece-rise-seminar-series-trustworthy-ai-dr-lydia-zakynthinou/
LOCATION:2534 Engineering Hall\, 1415 Engineering Drive\, Madison\, Wisconsin\, 53706\, United States
CATEGORIES:Electrical & Computer Engineering,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250303T180000
DTEND;TZID=America/Chicago:20250303T190000
DTSTAMP:20250312T211752
CREATED:20250226T181755Z
LAST-MODIFIED:20250226T181951Z
UID:10001192-1741024800-1741028400@engineering.wisc.edu
SUMMARY:ISyE - An evening with industry - GRAINGER x IISE
DESCRIPTION:Grainger representatives are excited to share the various career paths and opportunities that they have to offer. They will also be sharing their experiences working for Grainger and would be happy to answer any questions. This evening is hosted by the Institute of Industrial and Systems Engineering (IISE) student chapter. \n\n\n\nThere will also be a case study to apply your engineering skills. Case studies are accounts of real engineering situations and projects that provide a context for you to practice your problem-solving skills.
URL:/event/isye-an-evening-with-industry-grainger-x-iise/
LOCATION:1106 Engineering Hall\, 1415 Engineering Drive\, Madison\, 53711
CATEGORIES:Departments,Industrial & Systems Engineering,Information Session,Student Org Event
ATTACH;FMTTYPE=image/jpeg:/wp-content/uploads/2024/09/Student-Org-EVent-scaled.avif
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250304T122000
DTEND;TZID=America/Chicago:20250304T125000
DTSTAMP:20250312T211752
CREATED:20241227T220136Z
LAST-MODIFIED:20250123T221755Z
UID:10001077-1741090800-1741092600@engineering.wisc.edu
SUMMARY:ECE Discovery Panel: Semiconductor Engineering
DESCRIPTION:Engineering undergraduates! Join us in the Cheney Room (1413 Engineering Hall) as faculty members explore the technical area of Semiconductor Engineering! All undergraduate students are welcome as Assistant Professor Chirag Gupta\, Professor Umit Yusuf Ogras\, and Assistant Professor Eric Tervo talk about application ideas\, advanced course electives in this area\, and future job opportunities. It’s a great place to ask your questions about classes and career paths in this growing ECE field. \n\n\n\nCome for the insights\, stay for the pizza!
URL:/event/ece-discovery-panel-semiconductor-engineering/
LOCATION:1413 Engineering Hall – Cheney Room\, 1415 Engineering Drive\, Madison\, WI\, 53711\, United States
CATEGORIES:Electrical & Computer Engineering,Information Session
ATTACH;FMTTYPE=image/jpeg:/wp-content/uploads/2024/02/Web-GraphicECE-Discovery-Panel-Series-1-jpg.webp
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250305T120000
DTEND;TZID=America/Chicago:20250305T130000
DTSTAMP:20250312T211752
CREATED:20250220T173300Z
LAST-MODIFIED:20250220T173302Z
UID:10001182-1741176000-1741179600@engineering.wisc.edu
SUMMARY:ECE RISE SEMINAR SERIES: Trustworthy AI - Dr. Mahdi Haghifam
DESCRIPTION:4610 Engineering Hall \n\n\n\nThe Interplay of Generalization\, Memorization\, and Privacy in Trustworthy Machine Learning\n\n\n\nAbstract:Machine learning is transforming numerous aspects of modern society\, and its increasing use in high-stakes applications necessitates responsible development. In this talk\, I will present my research on the foundations and methodologies for building trustworthy ML\, focusing on three interconnected challenges: generalization\, memorization\, and privacy. First\, I will explore generalization: how can we ensure that ML models reliably predict on unseen data? I will discuss my work on developing novel information-theoretic measures to characterize and reason about generalization. Next\, I will examine data memorization\, showing how it can coexist with generalization and may even be necessary for accurate learning. Finally\, I will focus on differential privacy\, a rigorous framework for mitigating data memorization\, and present my work on designing differentially private optimization algorithms. I will conclude by discussing key open questions in the area of trustworthy ML. \n\n\n\nMahdi Haghifam\n\n\n\nBio:Mahdi Haghifam is a Distinguished Postdoctoral Researcher at Khoury College of Computer Sciences\, Northeastern University\, hosted by Jonathan Ullman. He received his PhD from the University of Toronto and the Vector Institute\, where he was advised by Daniel M. Roy. Mahdi’s research focuses on the foundations and algorithms of trustworthy machine learning\, particularly in the areas of privacy\, generalization\, and memorization. During his PhD\, he worked as a research intern at Google Brain and ServiceNow Research. His contributions have been recognized with a Best Paper Award at ICML 2024 and several fellowships from the University of Toronto.
URL:/event/ece-rise-seminar-series-trustworthy-ai-dr-mahdi-haghifam/
LOCATION:4610 Engineering Hall\, 1415 Engineering Drive\, Madison\, 53711
CATEGORIES:Electrical & Computer Engineering,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250305T120000
DTEND;TZID=America/Chicago:20250305T130000
DTSTAMP:20250312T211752
CREATED:20250304T213151Z
LAST-MODIFIED:20250304T213156Z
UID:10001198-1741176000-1741179600@engineering.wisc.edu
SUMMARY:ME Faculty Candidate Seminar
DESCRIPTION:Join the Department of Mechanical Engineering for Faculty Candidate Seminars during the Spring 2025 semester. \n\n\n\nThese will take place on Mondays and Wednesdays of each week from 12-1pm in room 2188 ME Building.
URL:/event/me-faculty-candidate-seminar-3/
LOCATION:2188 Mechanical Engineering Building\, 1513 University Avenue\, Madison\, WI\, 53706\, United States
CATEGORIES:Mechanical Engineering
ATTACH;FMTTYPE=image/jpeg:/wp-content/uploads/2025/01/Faculty-Seminar-Promotion.avif
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250305T180000
DTEND;TZID=America/Chicago:20250305T210000
DTSTAMP:20250312T211752
CREATED:20250129T191118Z
LAST-MODIFIED:20250305T175344Z
UID:10000759-1741197600-1741208400@engineering.wisc.edu
SUMMARY:Event Cancelled: UW-Madison CEE Alumni Night in Minnesota
DESCRIPTION:Due to inclement weather moving through the region\, the Alumni Night at Mortenson scheduled for Wednesday\, March 5\, from 6:00-9:30 pm\, is cancelled. \n\n\n\nWe look forward to visiting our Minnesota Badger community another time and hope you can join us. \n\n\n\n\n\n\n\nThank you to our event sponsor!
URL:/event/uw-madison-cee-alumni-night-in-minnesota/
CATEGORIES:Alumni events,Civil & Environmental Engineering,Social Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250306T120000
DTEND;TZID=America/Chicago:20250306T130000
DTSTAMP:20250312T211752
CREATED:20250204T172126Z
LAST-MODIFIED:20250211T191659Z
UID:10001144-1741262400-1741266000@engineering.wisc.edu
SUMMARY:BME Seminar Series: Arash Farhad\, PhD
DESCRIPTION:Engineering multistate trackable cells for smart precision therapeutics\n\n\n\n\n\n\n\nArash Farhadi\, PhDPostdoctoral ScholarVoigt LabMassachusetts Institute of Technology \n\n\n\nAbstract:The engineering of immune cells and microbes into living therapeutics is emerging as a powerful approach for treating many diseases. However\, two key challenges must be addressed to unlock the full potential of living therapeutics: intricately programming cells to perform diverse therapeutic tasks\, and effectively monitoring them once administered to the body. My research provides the foundation to address these major challenges. In my presentation\, I will outline how cells can be engineered to differentiate into multistate communities with distributed functions\, using Synthetic Differentiation circuits. The biomolecular mechanism of Synthetic Differentiation circuits can be engineered to tune the community composition\, expand the number of unique states\, and replenish population imbalances in the community. I will highlight examples demonstrating the versatility of these circuits in applications spanning living therapeutics and agricultural biotechnology. Additionally\, I will demonstrate noninvasive methods for tracking the location and function of cells deep in the body. Most methods to image cells rely on light\, which has limited penetration depth. Conversely\, ultrasound can image deep in tissue but lacks genetic reporters. I will introduce the first acoustic reporter genes (ARGs)—a ‘GFP’ for ultrasound—that enable imaging of cells and their gene expression inside the living\, intact animal. Together\, these technologies will enable next-generation living therapeutics capable of simultaneously targeting many disease hallmarks while providing real-time feedback to scientists and clinicians. \n\n\n\nPrint PDF
URL:/event/bme-seminar-series-arash-farhad-phd/
LOCATION:2180 Mechanical Engineering\, 1513 University Ave\, Madison\, WI\, 53706\, United States
CATEGORIES:Biomedical Engineering,Seminar
ATTACH;FMTTYPE=image/jpeg:/wp-content/uploads/2024/11/Seminar-Graphic-Fall2024-1.avif
ORGANIZER;CN="Department of Biomedical Engineering":MAILTO:bmehelp@bme.wisc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250306T120000
DTEND;TZID=America/Chicago:20250306T130000
DTSTAMP:20250312T211752
CREATED:20250219T220011Z
LAST-MODIFIED:20250303T173344Z
UID:10001178-1741262400-1741266000@engineering.wisc.edu
SUMMARY:NEEP Seminar: Dean Price\, Idaho National Laboratory
DESCRIPTION:Thursday\, March 612:00-1:00pmERB 106Remote Participation: Please contact office@ep.wisc.edu for the Zoom link. \n\n\n\n\n\n\n\nTitle: AI Founded on Physics \n\n\n\nAbstract: The nuclear industry sits firmly between seeing the significant benefit of Artificial Intelligence (AI) technologies and guarding against the challenges these novel technologies could create. The path forward lies in the use of AI methods firmly grounded in the physical principles governing conventional physics-based simulations. This seminar will explore ways in which Physics-INformed (PIN) machine learning and AI models for the analysis of fission-based reactor systems can aid the rapidly growing industry in its pursuit of safe and economical reactor development. A special focus will be given to the formulation of some AI models under a PIN framework such that the discussed methods can be applied to a wide variety of scenarios. Practical applications of these models\, such as optimizing reactor performance and dynamics characterization\, will also be discussed. \n\n\n\n\n\n\n\nSpeaker: Dean Price\, Idaho National Laboratory \n\n\n\nBio: Dean Price is a Russell L. Heath distinguished postdoctoral associate at Idaho National Laboratory in the Reactor Physics Methods and Analysis Group. He holds a PhD in Nuclear Engineering and Radiological Science from the University of Michigan where he was awarded fellowships from both the National Science Foundation as well as the Nuclear Energy University Program. He has published 20 articles in peer-reviewed journals along with numerous conference papers and technical reports. His research interests focus on the integration of high fidelity multiphysics simulations with data driven methods to support the development and deployment of advanced reactors. \n\n\n\nThis seminar is presented by the Institute for Nuclear Energy Systems and the Nuclear Engineering & Engineering Physics Department.
URL:/event/neep-seminar-dean-price-idaho-national-laboratory/
CATEGORIES:Nuclear Engineering & Engineering Physics
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250306T160000
DTEND;TZID=America/Chicago:20250306T170000
DTSTAMP:20250312T211752
CREATED:20241226T153338Z
LAST-MODIFIED:20241226T160724Z
UID:10001061-1741276800-1741280400@engineering.wisc.edu
SUMMARY:ME 903 Graduate Seminar: Professor Deema Totah
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 Deema Totah is a professor at the University of Iowa.
URL:/event/me-903-graduate-seminar-professor-deema-totah/
LOCATION:3M Auditorium\, rm 1106 Mechanical Engineering Building\, 1513 University Ave\, Madison\, 53711
CATEGORIES:Mechanical Engineering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250307T095500
DTEND;TZID=America/Chicago:20250307T104500
DTSTAMP:20250312T211752
CREATED:20250220T213808Z
LAST-MODIFIED:20250220T213811Z
UID:10001183-1741341300-1741344300@engineering.wisc.edu
SUMMARY:Welcome Back\, Badger - Jeff Roznowski
DESCRIPTION:Please help us welcome Alumnus Jeff Roznowski (BSIE\, MBA) as he shares insight from his professional journey since graduating from UW-ISyE. \n\n\n\nAll students are welcome! \n\n\n\nJeff Roznowski\n\n\n\nJeff worked for many years in the telecommunications industry\, culminating in his leadership role as President & Co-Founder of the Wisconsin Wireless Association. He is a former adjunct professor at MSOE\, and is also a passionate public servant who has volunteered his leadership and expertise to several civic\, government and philanthropic organizations.
URL:/event/welcome-back-badger-jeff-roznowski/
LOCATION:1800 Engineering Hall\, 1415 Engineering Drive\, Madison\, 53706
CATEGORIES:Alumni events,Featured Guest Speaker,Industrial & Systems Engineering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250307T110000
DTEND;TZID=America/Chicago:20250307T120000
DTSTAMP:20250312T211752
CREATED:20250227T222200Z
LAST-MODIFIED:20250306T193623Z
UID:10001193-1741345200-1741348800@engineering.wisc.edu
SUMMARY:ECE Research Seminar Series: Dr. Rich Mildren
DESCRIPTION:2239 Engineering Hall \n\n\n\nSub-monolayer manipulation of diamond surfaces using a two-photon technique\n\n\n\nAbstract:Engineering the termination and defects of diamond surfaces are important for quantum computing and sensing\, and electronic applications. Techniques for manipulating the surface include processes based on plasma\, chemical\, electron and ion beams\, and laser treatments. Although laser writing offers a convenient technique for defining complex surface patterns\, its applications have been limited due to poor depth resolution and contamination via graphitization. We describe an unusual non-ablative UV laser direct-write technique for manipulating the surface chemistry and etching top-layers with sub-monolayer precision. This effect\, which appears to be unique to diamond\, is interesting from a surface physics perspective as well as applications in nano-scale engineering of diamond surfaces. The talk will describe the phenomenology of the process\, and provide an example of where the process can be used to enhance surface electronics.  \n\n\n\nRich Mildren\n\n\n\nBiography:Rich Mildren is a Professor of Physics in the School of Mathematical and Physical Sciences\, Macquarie University. His research is in the development of novel and versatile photonic sources\, instrumentation and applications. His PhD (1997) and early postdoctoral research (1998-2004) was in the plasma kinetics of high-power gas lasers. During this period\, he was a visiting fellow at the National Research Council in Pisa\, Italy. For 3 years (2005-2008) he led R&D for a University spin-off company in wavelength-switchable medical lasers\, during which time he brought several medical laser products through to the stage of medical device regulatory approval. His most recent focus\, conducted in the MQ Photonics Research Centre\, is in photonics using advanced materials such as diamond. He has six awarded patents and authored 150+ peer-reviewed journal articles. He was the recipient of the Australian Museum Eureka Award for Outstanding Science for Safeguarding Australia in 2017 and elected an OSA Fellow in 2018. \n\n\n\nDr. Mildren’s visit is hosted by ECE Dugald C. Jackson Assistant Professor Jennifer Choy.
URL:/event/ece-research-seminar-series-dr-rich-mildren/
LOCATION:2239 Engineering Hall\, 1415 Engineering Drive\, Madison\, 53711
CATEGORIES:Electrical & Computer Engineering
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250307T120000
DTEND;TZID=America/Chicago:20250307T130000
DTSTAMP:20250312T211752
CREATED:20250218T155020Z
LAST-MODIFIED:20250228T180706Z
UID:10001169-1741348800-1741352400@engineering.wisc.edu
SUMMARY:ECE RISE SEMINAR SERIES: Trustworthy AI - Chulin Xie
DESCRIPTION:Via Zoom \n\n\n\nImproving Trustworthiness in Foundation Models: Assessing\, Mitigating\, and Analyzing ML Risks\n\n\n\nAbstractAs machine learning (ML) models continue to scale in size and capability\, they expand the surface area for safety and privacy risks\, raising concerns about model trustworthiness and responsible data use. My research uncovers and mitigates these risks. In this presentation\, I will focus on the three cornerstones of trustworthy foundation models and agents: safety\, privacy\, and generalization. For safety\, I will introduce our comprehensive benchmarks designed to evaluate trustworthiness risks in Large Language Models (LLMs) and LLM-based code agents. For privacy\, I will present a solution for protecting data privacy with a synthetic text generation algorithm under differential privacy guarantees. The algorithm requires only LLMs inference API access without model training\, enabling efficient safe text sharing. For generalization\, I will introduce our study on the interplay between the memorization and generalization of LLMs in logical reasoning during the supervised fine-tuning (SFT) stage. Finally\, I will conclude with my future research plan for assessing and improving trustworthiness in foundation model-powered ML systems. \n\n\n\nChulin Xie\n\n\n\nBioChulin Xie is a PhD candidate in Computer Science at the University of Illinois Urbana-Champaign\, advised by Professor Bo Li. Her research focuses on the principles and practices of trustworthy machine learning\, addressing the safety\, privacy\, and generalization risks of Foundation Models\, agents\, and federated (distributed) learning. Her work was recognized by an Outstanding Paper Award at NeurIPS 2023\, a Best Research Paper Finalist at VLDB 2024\, and press coverage like The Verge and TechCrunch. She was a recipient of 2024 Rising Star in Machine Learning and IBM PhD Fellowship. During her PhD\, she gained industry experience through research internships at NVIDIA\, Microsoft\, and Google. \n\n\n\n\nZoom Link
URL:/event/ece-rise-seminar-series-trustworthy-ai-chulin-xie/
CATEGORIES:Electrical & Computer Engineering,Seminar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250307T120500
DTEND;TZID=America/Chicago:20250307T125500
DTSTAMP:20250312T211752
CREATED:20241226T165228Z
LAST-MODIFIED:20241226T174558Z
UID:10001070-1741349100-1741352100@engineering.wisc.edu
SUMMARY:Mechanics Seminar Series: Professor Nicholas Boechler
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 Nicholas Boechler is a professor at the University of California San Diego.
URL:/event/mechanics-seminar-series-professor-nicholas-boechler/
LOCATION:3M Auditorium\, rm 1106 Mechanical Engineering Building\, 1513 University Ave\, Madison\, 53711
CATEGORIES:Mechanical Engineering
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