X Y Han

X Y Han is an Assistant Professor of Operations Management & Applied AI at the Booth School of Business, University of Chicago. His research bridges Artificial Intelligence and Optimization to develop human-in-the-loop tools for enhancing productivity in automated systems.

• Education:
  • BSE in Operations Research and Financial Engineering, Princeton University
  • PhD in Operations Research and Information Engineering, Cornell University
  • M.S. in Statistics, Stanford University

His work focuses on two core areas: Artificial Intelligence (via large-scale experiments and mathematical geometry to understand AI systems) and Optimization (developing faster algorithms for nonsmooth, constrained, and nonconvex problems). Notably, he co-discovered the Neural Collapse phenomenon in deep learning and co-invented the Survey Descent method for optimization.

Collaborations include Frick Art Reference Library, Surgical Data Science Collective, and Veolia North America, applying state-of-the-art algorithms to real-world productivity challenges.

• Scientific Awards:
  • ICLR 2022 Outstanding Paper Award
  • ICCOPT 2022 Best Paper Prize for Young Researchers (Finalist)

Contact: xy.han@chicagobooth.edu