College of Engineering - University of Wisconsin-Madison

ME 903 Graduate Seminar: Professor Sam Kriegman
2025-03-13 16:00 - 17:00 (America/Chicago) | 3M Auditorium, rm 1106 Mechanical Engineering Building, 1513 University Ave, Madison, 53711
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 Sam Kriegman is a professor at Northwestern University.

BME Seminar Series: Wei Qiu
2025-03-13 12:00 - 13:00 | 2188 Mechanical Engineering Building, 1513 University Avenue, Madison, WI, 53706, United States
Understanding Aging at Multi-scale Using Explainable AI

Wei QiuPhD CandidateComputer Science and Engineering DepartmentUniversity of Washington

Abstract:As human lifespans continue to extend, it becomes increasingly critical to understand the aging process not only to increase lifespan but also to enhance healthspan. This talk explores how Artificial Intelligence (AI), coupled with Explainable AI (XAI), can illuminate the complex mechanisms of aging at multiple scales, enhancing our ability to predict and explain these processes transparently.

First, I will introduce my work in AI for personalized health insights. I will present the ENABL Age framework, which integrates AI and XAI to provide precise and interpretable assessments of biological aging. This model not only estimates biological age but also explicates the factors contributing to aging, offering insights for personalized health strategies.

Second, I will discuss my AI innovations in omics data analysis, with a focus on cancer as an age-related disease. I have designed DeepProfile, which analyzes large-scale cancer datasets to identify key biomarkers and pathways, enhancing our approach to precision oncology. Additionally, I have developed StrastiveVI, which further isolates aging-related signals from single-cell transcriptomic data, revealing universal aging patterns and facilitating targeted anti-aging interventions.

Third, the discussion will turn to our pioneering work in the automated generation of plain language, democratizing access to complex biomedical findings and enhancing public health literacy. This work advances biomedical communication by enabling more comprehensible health-related information.

In conclusion, I will outline a vision for future directions in integrating transparent AI with aging research. This effort requires extensive collaboration across biology, clinical science, AI research, public health, and data science. Emphasizing a multidisciplinary approach, we aim to address the complex challenges associated with aging, paving the way for innovative solutions that not only enhance the precision but also the accessibility of healthcare.

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NEEP Seminar: Sébastien Philippe, Princeton University
2025-03-13 12:00 - 13:00 | Wisconsin
Thursday, March 13 12:00 – 1:00pmERB 106Remote Participation: Please contact office@ep.wisc.edu for the Zoom link.

Title: Reducing Global Nuclear Risks Through Science, Engineering, and Policy

Abstract: Global nuclear risks—including nuclear weapons use, proliferation, and arms racing—are growing amid renewed geopolitical tensions. Addressing these challenges requires an interdisciplinary framework that integrates scientific modeling, engineering innovation, and policy analysis. In this talk, I will discuss how nuclear weapon effects modeling and verification technologies can guide risk-reduction strategies. I will present recent work using atmospheric transport and dispersion methods to model fallout from nuclear explosions—including historical tests like Trinity—and assess the humanitarian and environmental consequences of nuclear war. I will also highlight how integrating radiation detection, remote sensing, and cryptographic protocols can overcome verification challenges and enable new strategic arms control initiatives. Finally, I will outline a research agenda integrating space-based sensors and robotics to enhance nuclear safeguards and monitoring as well as advancing engineering level-code to support the safe deployment of fusion energy and next-generation nuclear technologies.

Speaker: Sébastien Philippe, Princeton University

Bio: Dr. Sébastien Philippe is a Research Scholar and Co-Principal Investigator at Princeton University’s Program on Science and Global Security (SGS), where he develops technical solutions to assess and reduce nuclear weapon risks. He earned his Ph.D. in Mechanical and Aerospace Engineering from Princeton and completed his postdoctoral training at Harvard. Before his academic career, he worked as a nuclear weapon system safety engineer for the French Ministry of Armed Forces. Dr. Philippe is the author of an award-winning book on the legacy of French nuclear testing in the Pacific, as well as two dozen peer-reviewed publications and major technical and policy reports on fissile materials and nuclear weapons issues. He regularly briefs policymakers and speaks at the United Nations, where he currently serves as a scientific advisor. His work has been featured in The New York Times, CNN, Science, Nature and other major media outlets worldwide. This year, Dr. Philippe is receiving the 2025 Joseph A. Burton Forum Award from the American Physical Society, recognizing “outstanding contributions to the public understanding and resolution of issues at the interface of physics and society.”

This seminar is presented by the Institute for Nuclear Energy Systems and the Nuclear Engineering & Engineering Physics Department.

ISyE- Make pins for Pi(e) day!
2025-03-12 18:00 - 19:00 | 2255 Engineering Hall, 1415 Engineering Drive, Madison, 53711
2255 Engineering Hall

Have you ever wanted a customized pin to put on your backback, hat, or totebag? Now you can with IISE! We will have all the supplies for you to create designs of your choice to make your very own pins for an early Pi Day celebration! Speaking of Pi, we will have FREE PIE at this event! Come by for an exciting Pin Social with Pi(e).

Artificial Intelligence in Research: Ethical Challenges and Considerations
2025-03-12 16:00 - 17:00 | Wisconsin
Wednesday, March 12 at 4:00pmEngineering Hall 2309

Host: Dr. Carolina Quintana-Kuether

Guest Speaker: Laura Grossenbacher, Director of Undergraduate Program Review and Director of Technical Communication Program in the College of Engineering

Title: Artificial Intelligence in Research: Ethical Challenges and Considerations

Abstract: As AI tools become more available and essential in modern engineering, it is crucial for students and professionals alike to understand not only the benefits but also the ethical challenges that arise. Whether you are a student new to AI or an experienced researcher, this discussion will deepen your understanding of the ethical considerations and impact of AI technologies in society, research integrity, and the future of engineering. Join us for this compelling session and take away practical insights that will guide you as you navigate this exciting, yet complex, world of AI in your work.

Bio: Laura Grossenbacher is Director of Undergraduate Program Review and Director of the Technical Communication Program in the College of Engineering at the University of Wisconsin-Madison. She holds a Ph.D. from the University of Texas at Austin and has been teaching courses in engineering communication and ethics for over twenty-five years to both undergraduates and graduate students in the UW Madison College of Engineering.

Since year 2012 she has been developing ethics cases for use with a variety of different Professional Engineering groups, including engineers working for the Wisconsin Department of Transportation, the Wisconsin Department of Natural Resources, American Transmission Company, Madison Gas and Electric, WE Energies, Realtime Utility, the Milwaukee Metropolitan Sewerage District, and the American Water Resources Administration. She has also held ethics workshops for the Wisconsin Structural Engineering Code Refresher Annual Conference, the Wisconsin Concrete Pavement Association, the Wisconsin Society for Landscape Architects, and the American Society for Heating, Refrigerating and Air Conditioning Engineers.

Her ethics workshops are designed to engage engineers and other professionals in discussing and applying codes of ethics, moral theory, and behavioral science to practical cases. She is a member of the Association for Practical and Professional Ethics (APPE), and a current co-chair, with Rider Foley, of the Online Ethics Center Community of Practice in Teaching Engineering Ethics. Her most recent conference workshops have been for the annual ABET Symposium and at the American Society for Engineering Education on using applied ethics cases to interrogate challenges with power and inclusivity.

ME Faculty Candidate Seminar
2025-03-12 12:00 - 13:00, 2025-03-10 12:00 - 13:00, 2025-03-05 12:00 - 13:00 | 2188 Mechanical Engineering Building, 1513 University Avenue, Madison, WI, 53706, United States
Join the Department of Mechanical Engineering for Faculty Candidate Seminars during the Spring 2025 semester.

These will take place on Mondays and Wednesdays of each week from 12-1pm in room 2188 ME Building.

ECE RISE SEMINAR SERIES: Clean Energy Technologies - Dr. Dorsa Talebi
2025-03-12 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Electrical Drive Systems: Lightweight and Scalable Propulsion for Aerospace and Sustainable Energy

Abstract:As AI and machine learning revolutionize software and computing, as our transportation is being electrified, global energy needs are growing dramatically. At the core of energy conversion and motion systems, electrical drive systems are the unsung heroes—powering everything from the wheels of electric cars to the propellers that lift air taxis into the sky to the emerging humanoid robots. This presentation will outline the developments to shape the next era of electric drive systems for air vehicle electrification and sustainable energy.Join this talk to explore how non-traditional axial flux machines are pushing the boundaries of electric powertrain technology, achieving an unprecedented 14.8 kW/kg power-to-mass ratio—nearly three times the state-of-the-art 5 kW/kg benchmark of commercial systems today. This breakthrough is made possible through amultidisciplinary integration of electric machine design, advanced thermal management, and next-generation manufacturing techniques, delivering over 94% efficiency at the takeoff for an aircraft flight profile and redefining what’s possible for electric transportation in the future.Beyond aviation, electrification of transportation presents new challenges, including geopolitical concerns surrounding rare-earth materials. This talk will introduce the development of rare-earth-free motors, a transformative step toward sustainable electrification—impacting not only traction motors but also renewable energy applications like wind turbine generators. This innovation builds upon conventional wound-field synchronous machines but eliminates the need for additional mechanical or electrical exciters. Instead, by leveraging existing stationary coil sets and systematic harmonic injection, the excitation magnetic field is generated on the rotor without the use of brushes or permanent magnets. This novel approach merges the fundamentals of conventional electric machines with a modern harmonic excitation approach and simple and robust rotating power electronics.The presentation will conclude with a summary of upcoming research trends and opportunities.

Bio:Dorsa Talebi earned her Ph.D. in Electrical and Computer Engineering from Texas A&M University in 2024 under the supervision of Prof. Toliyat. Her research focuses on advancing unconventional electric machine designs, with integrated cooling systems, particularly axial flux machines, to enable hyper-efficient,lightweight solutions for aircraft propulsion, drones, robotics, and more. During her graduate studies, Dorsa gained industry experience in powertrain R&D through internships at Tesla and Lucid Motors and co-invented a rare-earth-free electric machine, addressing material sustainability challenges while achieving high-performance electric drive systems for electric traction and renewable energy applications, supported by Texas A&M’s Advancing Discovery to Market (ADM) funding. Her expertise spans electric machine design and the multidisciplinary co-design of power electronic converter, thermal management systems, and structural components.Dorsa holds multiple issued U.S. patents and patent applications and has authored multiple papers published in various IEEE conferences and journals. Her achievements include several awards and scholarships, such as the Texas A&M Energy Institute Graduate Fellowship. Dorsa is currently a postdoctoral fellow at the Advanced Electrical Machines & Power Electronics (EMPE) Lab at Texas A&M University.

NEEP Seminar: Ashish Avachat, University of Pittsburgh
2025-03-11 12:00 - 13:00 | Wisconsin
Tuesday, March 1112:00-1:00pmERB 106Remote Participation: Please contact office@ep.wisc.edu for the Zoom link.

Title: Radiation-based Computational Imaging and Ontology

Abstract: In recent years, the modern smart phone cameras have leapfrogged the traditional cameras by employing the principles of computational imaging. Similar to the distinctions between such computational photography and the traditional photography, the radiation-based computational imaging and its traditional counterpart have two major distinctions. One, radiation-based computational imaging systems utilize a tight integration of instrumentation, for example, radiation source and image acquisition system, with the computer algorithms that are used for image formation, reconstruction, and analyses. And, two, radiation-based computational imaging systems use joint-optimization of the said instrumentation and algorithms to improve the image quality. By using this twofold philosophy of computational imaging comprising tight integration and joint-optimization–wherein we apply computational methods to the noisy, incomplete, and perhaps distorted raw measurements that are acquired at a minimum costs of time and radiation–we can reconstruct a “true image” with the best possible image quality for a given imaging task, for example, nuclear fuel characterization for fuel qualification. Given the surge of interest in nuclear energy and development of new generation of nuclear reactors, at the core of which are the nuclear test fuels and materials, I believe that the nuclear fuel and materials characterization is the cornerstone of a resilient and sustainable energy future. Because of the complexity of the nuclear fuels, especially during and after irradiation, they are considered to be one of the most challenging objects for imaging and analysis. Overcoming these challenges will not only deepen our understanding of nuclear fuels but also stimulate the development of imaging and analysis techniques that are applicable to a broader spectrum of objects across various engineering and scientific disciplines. And, the lessons learned from the development and optimization of these imaging and analysis techniques for non-nuclear applications will directly benefit nuclear fuel and materials characterization. Therefore, research on nuclear fuel characterization and on development of radiation-based imaging systems exist in a mutualistic symbiosis. In this seminar, I will present my contributions to the fields of radiation-based computational imaging and nuclear fuel characterization. With these past contributions as a backdrop, I will then discuss my future research thrusts, which are directed at capitalizing the mutualist symbiosis between nuclear fuel and materials characterization and development of innovative imaging and analysis techniques to contribute significantly to nuclear engineering and engineering physics and beyond.

Speaker: Ashish Avachat, University of Pittsburgh

Bio: Ashish Avachat is a research assistant professor in the Department of Mechanical Engineering and Materials Science at the University of Pittsburgh. His research is dedicated to developing radiation-based computational imaging systems and noise-robust ontology techniques for better characterizing objects—in their natural states—from nuclear engineering and other engineering and science disciplines. Prior to joining the University of Pittsburgh, Ashish was a postdoctoral research fellow at the University of Illinois Urbana-Champaign. Ashish received his M.S. and Ph.D. in Nuclear Engineering from the Missouri University of Science and Technology.

This seminar is presented by the Institute for Nuclear Energy Systems and the Nuclear Engineering & Engineering Physics Department.

ECE Seminar Series in Advanced Semiconductor Materials and Devices - Dr. Bei Shi
2025-03-11 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Monolithic Integration of III-V Optoelectronic Devices on Silicon by SelectiveArea Heteroepitaxy

Abstract:Silicon photonics is a cornerstone of next-generation data communications, heterogeneous computing, and quantum technologies, enabling large-scale photonic integration. On-chip optical interconnects in photonic integrated circuits (PICs) overcome the limitations of electronic interconnects, providing higher transmission speeds and bandwidth. However, silicon’s indirect bandgap restricts its optoelectronic performance, necessitating the heterogeneous integration of III-V compound semiconductors to enhance PIC functionality, reduce energy consumption, and enable scalable applications. In this seminar, I will present my research on wafer-scale monolithic integration of III-V optoelectronic devices on silicon photonic chips leveraging advanced heteroepitaxy techniques. This includes high-quality III-V heteroepitaxy on silicon, with a focus on quantum dot (QD) lasers and indium gallium arsenide (InGaAs) shortwave infrared photodetectors. I will also introduce selective area heteroepitaxy of QD lasers on large- scale silicon photonic wafers and their monolithic integration with silicon nitride waveguides for low-loss facet coupling. Finally, I will discuss future perspectives on novel III-V/Si heteroepitaxy and integration architectures for energy-efficient AI and quantum information processors.

Bei Shi

Bio:Bei Shi is a Principal Scientist at Aeluma, Inc., a Santa Barbara-based startup commercializing large-scale III-V materials and devices integration on silicon, and a Research Specialist at University of California, Santa Barbara (UCSB). He earned his Ph.D. from The Hong Kong University of Science and Technology (HKUST) in 2018, advised by Prof. Kei May Lau, and later joined UCSB as a postdoctoral scholar under Prof. Jonathan Klamkin. His research focuses on heterogeneous integration of silicon photonics via advanced heteroepitaxy, quantum dot lasers for AI hardware and data centers, and shortwave infrared avalanche photodetectors for LiDAR, sensing, and quantum applications. Dr. Shi has authored 70+ journal and conference papers (Optica, ACS Photonics, APL), delivered three invited talks and served as a session chair/committee member at major international conferences. Additionally, Dr. Shi filed six U.S. patents, served as a Guest Editor for MDPI Crystals/Sensors, and received the 2019 Charles Kao Best Paper Award in Industry Innovation. He is also a Principal Investigator leading DoD- and NASA-funded projects to develop monolithic integration of quantum dot lasers on scalable silicon photonics platforms for diverse cutting-edge applications.

Mechanics Seminar Series: Professor Nicholas Boechler
2025-03-07 12:05 - 12:55 | 3M Auditorium, rm 1106 Mechanical Engineering Building, 1513 University Ave, Madison, 53711
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.

ECE RISE SEMINAR SERIES: Trustworthy AI - Chulin Xie
2025-03-07 12:00 - 13:00 | Wisconsin
Via Zoom

Improving Trustworthiness in Foundation Models: Assessing, Mitigating, and Analyzing ML Risks

AbstractAs 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.

Chulin Xie

BioChulin 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.

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ECE Research Seminar Series: Dr. Rich Mildren
2025-03-07 11:00 - 12:00 | 2239 Engineering Hall, 1415 Engineering Drive, Madison, 53711
2239 Engineering Hall

Sub-monolayer manipulation of diamond surfaces using a two-photon technique

Abstract: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.

Rich Mildren

Biography: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.

Dr. Mildren’s visit is hosted by ECE Dugald C. Jackson Assistant Professor Jennifer Choy.

Welcome Back, Badger - Jeff Roznowski
2025-03-07 09:55 - 10:45 | 1800 Engineering Hall, 1415 Engineering Drive, Madison, 53706
Please help us welcome Alumnus Jeff Roznowski (BSIE, MBA) as he shares insight from his professional journey since graduating from UW-ISyE.

All students are welcome!

Jeff Roznowski

Jeff 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.

ME 903 Graduate Seminar: Professor Deema Totah
2025-03-06 16:00 - 17:00 | 3M Auditorium, rm 1106 Mechanical Engineering Building, 1513 University Ave, Madison, 53711
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.

NEEP Seminar: Dean Price, Idaho National Laboratory
2025-03-06 12:00 - 13:00 | Wisconsin
Thursday, March 612:00-1:00pmERB 106Remote Participation: Please contact office@ep.wisc.edu for the Zoom link.

Title: AI Founded on Physics

Abstract: 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.

Speaker: Dean Price, Idaho National Laboratory

Bio: 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.

This seminar is presented by the Institute for Nuclear Energy Systems and the Nuclear Engineering & Engineering Physics Department.

BME Seminar Series: Arash Farhad, PhD
2025-03-06 12:00 - 13:00 | 2180 Mechanical Engineering, 1513 University Ave, Madison, WI, 53706, United States
Engineering multistate trackable cells for smart precision therapeutics

Arash Farhadi, PhDPostdoctoral ScholarVoigt LabMassachusetts Institute of Technology

Abstract: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.

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ECE RISE SEMINAR SERIES: Trustworthy AI - Dr. Mahdi Haghifam
2025-03-05 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

The Interplay of Generalization, Memorization, and Privacy in Trustworthy Machine Learning

Abstract: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.

Mahdi Haghifam

Bio: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.

ECE Discovery Panel: Semiconductor Engineering
2025-03-04 12:20 - 12:50 | 1413 Engineering Hall – Cheney Room, 1415 Engineering Drive, Madison, WI, 53711, United States
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.

Come for the insights, stay for the pizza!

ISyE - An evening with industry - GRAINGER x IISE
2025-03-03 18:00 - 19:00 | 1106 Engineering Hall, 1415 Engineering Drive, Madison, 53711
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.

There 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.

ECE RISE SEMINAR SERIES: Trustworthy AI – Dr. Lydia Zakynthinou
2025-03-03 12:00 - 13:00 | 2534 Engineering Hall, 1415 Engineering Drive, Madison, Wisconsin, 53706, United States
2534 Engineering Hall

Algorithmic Stability for Trustworthy Machine Learning and Statistics

Abstract: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.

Bio: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.

BME Seminar Series: Jacob Witten, PhD
2025-03-03 12:00 - 13:00 | 1003 (Tong Auditorium) Engineering Centers Building, 1550 Engineering Drive, Madison, WI, 53706, United States
Artificial intelligence for state-of-the-art gene therapy

Jacob Witten, PhDPostdoctoral FellowAnderson LabMassachusetts Institute of Technology

Abstract: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.

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ISyE Engineering Robust & Scalable AI for Healthcare Systems
2025-03-03 11:30 - 12:30 | 1153 Mechanical Engineering, 1513 University Ave, Madison, WI, 53706, United States
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.

In 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.

By 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.

Bio: 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.

Dr. 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.

As 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.

Midwest Mechanics Seminar Series: Professor Ken Kamrin
2025-02-28 12:05 - 12:55 | 3M Auditorium, rm 1106 Mechanical Engineering Building, 1513 University Ave, Madison, 53711
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 Ken Kamrin is a professor at UC Berkeley.

ME 903 Seminar: Chris Tabor
2025-02-27 16:00 - 17:00 | 3M Auditorium, rm 1106 Mechanical Engineering Building, 1513 University Ave, Madison, 53711
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. Chris Tabor is a Team Lead for Polymer and Responsive Materials at the Air Force Research Lab (ARL).

MS&E Seminar Series: Dr. Kevin Gotrik
2025-02-27 13:00 - 14:00 | Wisconsin
UW-Madison Department of Materials Science and Engineering welcomes Dr. Kevin Gotrik. Their seminar on “Insights Into Innovation – The Surprising Versatility of Scotch Tape” will be on Thursday, Feb. 27 in MS&E 265 from 1 p.m. to 2 p.m.

Abstract

In this engaging talk, Kevin Gotrik will share his extensive experience working within innovation ecosystems, drawing from his impressive career in materials science and engineering, and touching upon technology ecosystem development encompassing World War II. He will delve into the practical aspects of fostering innovation ecosystems, offering insights on how to create environments that encourage interdisciplinary research and the free exchange of ideas. Kevin will discuss the importance of providing time and resources for exploratory projects, the role of collaboration across different fields, and the impact of a supportive organizational culture on driving innovation. This talk is geared towards graduate students, but all are welcome

Bio

Kevin Gotrik is the third graduate of the Engineering Physics undergraduate program at the University of Wisconsin-Madison. During his undergraduate studies, Kevin conducted research at the Leibniz Institute in Dresden, Germany, and the Fraunhofer Institute in Stuttgart, gaining valuable international experience early in his career.

In 2013, Kevin earned his PhD in Materials Science and Engineering from the Massachusetts Institute of Technology (MIT), where he focused on the topics of self-assembly and nanolithography applications in semiconductor manufacturing. Kevin’s professional journey led him to 3M, where he has specialized in vacuum thin film applications. At 3M, he has thrived in an innovative environment that encourages scientific exploration beyond one’s primary area of expertise, known as “15% time.” This unique culture has allowed Kevin to pursue diverse scientific interests, resulting in over 150 international patent applications.

Kevin Gotrik enjoys sharing his experience on the power of interdisciplinary research and how to foster a culture of innovation.

NEEP Seminar: Rabab Haider, University of Michigan
2025-02-27 12:00 - 13:00 | Wisconsin
Thursday, February 27 12:00 – 1:00pmERB 106 (Contact office@ep.wisc.edu for assistance with remote participation.)

Speaker: Rabab Haider, University of Michigan

Title: Fast algorithms and equitable frameworks for renewable-rich power systems

Abstract: Power grids are rapidly decarbonizing to address climate challenges and expanding to meet increasing demand from electrification and AI growth. However, integrating increasing quantities of intermittent renewable generation presents a challenge to how we operate power grids, reducing decision-making timescales from days to minutes. Digit twins layered with AI applications can provide much needed real-time visibility and control, such as network reconfiguration. Reconfiguration is vital for rapidly integrating more renewable generation while maintaining grid reliability, yet its large-scale, nonlinear nature is challenging for traditional algorithms. We will introduce the specialized use of physics-informed machine learning for fast and accurate reconfiguration decisions. In the second part of the talk, we will explore the implications of the changing power grid on electricity affordability – a tenet of energy equity. We propose a new framework based on locational marginal burden, which provides an interface between energy burden and the optimal power flow problem by leveraging tools from differentiable optimization.

Bio: Dr. Rabab Haider is an Assistant Professor of Civil and Environmental Engineering at the University of Michigan. Her research is centered on designing future energy systems that provide green, reliable, and affordable energy for All. Her group develops optimization and AI algorithms that advance energy system operations, planning, and market under deep decarbonization. Dr. Haider’s portfolio also includes engagement with multiple global organizations to enable widespread access to STEMM education, mentorship, and leadership training. She received her Ph.D. and S.M. degrees at MIT, and B.A.Sc in Engineering Science at the University of Toronto. She was previously named a MIT Energy Fellow and MathWorks-MIT Mechanical Engineering Fellow. Dr. Haider is also an Affiliate Faculty at the Georgia Institute of Technology and NSF AI Institute for Advances in Optimization (AI4OPT).

This seminar is presented by the Institute for Nuclear Energy Systems and the Nuclear Engineering & Engineering Physics Department.

ECE RISE SEMINAR SERIES: Clean Energy Technologies - Dr. Noman Bashir
2025-02-27 12:00 - 13:00 | 4610 Engineering Hall, 1415 Engineering Drive, Madison, 53711
4610 Engineering Hall

Designing the Next Generation of Computer Systems for Sustainable AI

Abstract:Abstract: The key technology trend for the next decade is the transformative potential of artificial intelligence (AI), alongside its rapidly growing energy consumption and associated environmental impacts. However, our longstanding focus on energy efficiency alone will not solve the problem, and current computer systems powering AI applications are not designed to optimize carbon efficiency — that is, the amount of work performed per unit of carbon emitted. In this talk, I will present my work on rethinking how we design and operate computer systems for AI to enable carbon-aware optimizations. I will present my work on virtualizing the energy system to provide both visibility into, and software-defined control over, energy systems for computer applications. I will also describe how the proposed abstractions allow a wide range of AI applications to manage the variability of clean energy in software — accommodating diverse user and application requirements, goals, strategies, and tolerances for reducing carbon and energy. I will share my work on uncertainty- aware modeling of lifecycle carbon footprint, which helps stakeholders in computing and AI assess the discernibility of their decisions. Finally, I will outline my vision for enabling sustainable AI capabilities in a rapidly evolving landscape of AI hardware and software, and I will illustrate how these advances can drive broader societal decarbonization.

Noman Bashir

Bio:Noman Bashir is a Computing & Climate Postdoctoral Impact Fellow at the MIT Computer Science & Artificial Intelligence Laboratory (CSAIL) and the MIT Climate & Sustainability Consortium (MCSC). His research rethinks the design and operation of large-scale computer systems to address emerging challenges, including rapidly rising computing demand, increasing energy constraints, and unintended socio- environmental implications. His work on improving resource utilization — deployed across all Google datacenters — demonstrates significant real-world impact. He earned his Ph.D. from the University of Massachusetts Amherst in 2022.

ISyE - HFES Gen AI 101 with Python
2025-02-25 17:15 - 18:30 | 3210 Mechanical Engineering, 1513 University Avenue, Madison, 53706
Explore the basics of Generative AI with Python in this beginner-friendly workshop with the Human Factors & Ergonomics Society Student Chapter in UW-Madison. Learn concepts, practical skills, and get hands-on experience with Generative AI technologies and their APIs. No prior coding or AI experience needed, but it will be appreciated!

We are going to use Google Colab, thus no prior installation of any Python IDE is required.

Open to all, sign up here!
