Vitaly Feldman
Vitaly Feldman (Apple)
Title: TBD
Abstract: TBD
Bio: Vitaly Feldman is a research scientist at Apple working on foundations of machine learning and privacy-preserving data analysis. His recent research interests include the role of memorization in learning, distributed privacy-preserving learning, privacy-preserving optimization, tools for analysis of generalization, and adaptive data analysis
Vitaly holds a Ph.D. from Harvard (2006, advised by Leslie Valiant) and was previously a research scientist at Google Research (Brain team) and IBM Research – Almaden (Theory group). His work on understanding of memorization in learning was recognized by the 2021 Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies. His research on foundations of adaptive data analysis was recognized by the ACM STOC 2025 Test of Time award. His works were also recognized by COLT Best Student Paper Award in 2005 and 2013 (student co-authored) and by the IBM Research Best Paper Award in 2014, 2015 and 2016. He served as a program co-chair for COLT 2016 and ALT 2021 conferences and as a co-organizer of the Simons Institute Program on Data Privacy in 2019.
Surbhi Goel
Surbhi Goel (University of Pennsylvania)
Title: TBD
Abstract: TBD
Bio: Surbhi Goel is the Magerman Term Assistant Professor of Computer and Information Science at University of Pennsylvania. She is affiliated with the Theory group, the ASSET center on safe, explainable, and trustworthy AI systems, and the Warren Center for network and data sciences. She is the co-founder of Learning Theory Alliance (LeT-All), a community building and mentorship initiative and recently co-organized the Special Year of Large Language Models at the Simons Institute for the Theory of Computation. She is the recipient of the Schmidt Sciences AI2050 Early Career Fellowship, an Amazon Research Award, the Bert Kay Dissertation award from UT Austin, a JP Morgan AI Fellowship, a Simons-Berkeley Research Fellowship, and Rising Star recognition in both ML and EECS. Her research interests lie at the intersection of theoretical computer science and machine learning, with a focus on developing theoretical foundations for safe, reliable, and trustworthy AI.
Aaron Roth
Aaron Roth (University of Pennsylvania)
Title: TBD
Abstract: TBD
Bio: Aaron Roth is the Henry Salvatori Professor of Computer and Cognitive Science, in the Computer and Information Sciences department at the University of Pennsylvania, with a secondary appointment in the Wharton statistics department. He is affiliated with the Warren Center for Network and Data Science, and co-director of the Networked and Social Systems Engineering (NETS) program. He is also an Amazon Scholar at Amazon AWS. He is the recipient of the Hans Sigrist Prize, a Presidential Early Career Award for Scientists and Engineers (PECASE), an Alfred P. Sloan Research Fellowship, an NSF CAREER award, and research awards from Yahoo, Amazon, and Google. His research focuses on the algorithmic foundations of data privacy, algorithmic fairness, game theory, learning theory, and machine learning. Together with Cynthia Dwork, he is the author of the book “The Algorithmic Foundations of Differential Privacy.” Together with Michael Kearns, he is the author of “The Ethical Algorithm”.
Ohad Shamir
Ohad Shamir (UC Berkeley)
Title: TBD
Abstract: TBD
Bio: Ohad Shamir is a professor at the Weizmann Institute of Science, and a visiting professor at the University of Toronto, with previous research roles at Microsoft and Google. His work focuses on theoretical machine learning, in areas such as theory of deep learning, the intersection of machine learning and optimization, and learning under information and communication constraints. He served as a program co-chair of the Conference on Learning Theory (COLT), as well as a member of its steering committee, and as an action editor of the Journal of Machine Learning Research (JMLR). His honors include the inaugural 2024 Prize in the Mathematics of Artificial Intelligence, several best paper awards, the Hebrew University’s PhD thesis prize, and a €1.5 million ERC grant.