HDSI Distingushed Seminar – Yisong Yue

TITLE Design, Measure, Interpret: Foundation Models in the Scientific Loop

ABSTRACT “As foundation models become powerful scientific priors, a central question emerges: how can they drive the full cycle of discovery—from designing experiments to interpreting results? This talk presents a probabilistic framework that unites experiment design and inverse problems under a common foundation model. I will highlight recent progress in adaptive design algorithms and diffusion-based inversion methods, and discuss how these ideas point toward an AI-driven ecosystem for science.”

BIO Yisong Yue is a Professor of Computing and Mathematical Sciences at the California Institute of Technology. He was previously a research scientist at Disney Research. Before that, he was a postdoctoral researcher in the Machine Learning Department and the iLab at Carnegie Mellon University. He received a Ph.D. from Cornell University and a B.S. from the University of Illinois at Urbana-Champaign. Yisong previously served as Senior Program Chair of ICLR 2024 and General Chair of ICLR 2025, and currently serves on the ICLR board. Yisong’s research interests are centered around machine learning and artificial intelligence, particularly in getting AI to work in high-stakes and high-expertise domains. To that end, his research agenda spans both fundamental and applied pursuits, from novel learning frameworks all the way to deployment in autonomous driving on public roads. His work has been recognized with multiple paper awards and nominations, including in robotics, computer vision, sports analytics, machine learning for health, and information retrieval. During his time in industry, Yisong worked on machine learning approaches to behavior modeling and motion planning for autonomous driving.