X.Y. Han

X.Y. Han is an assistant professor of Operations Management at the University of Chicago, Booth School of Business. Before that, he was a postdoctoral scholar with Prof. David L. Donoho. He received PhD in Operations Research from Cornell ORIE under the supervision of Prof. Adrian S. Lewis in 2023. Previously, he earned an MS from Stanford Statistics in 2018 and a BSE from Princeton ORFE in 2016. He discovered the now-widely-studied Neural Collapse phenomenon in deep neural network training (with V. Papyan and D. Donoho) and invented the Survey Descent method for nonsmooth optimization (with A. Lewis). For these works, he received the ICLR 2022 Outstanding Paper Award and was a finalist for the ICCOPT 2022 Best Paper Prize for Young Researchers. He maintains real-world collaborations with the Frick Art Reference Library in NYC, the USC Keck School of Medicine, and the Veolia North America utilities company. Broadly, his research on nonsmooth optimization and deep learning mathematically analyzes and builds new methods based on realistic phenomena observed in modern computational practices.