Ph.D. Students on the Job Market

X.Y. Han

X.Y. Han is a PhD Candidate supervised by Adrian S. Lewis at Cornell ORIE; previously, he earned an MS from Stanford Statistics---where he conducted still-ongoing research under David L. Donoho---and a BSE from Princeton ORFE. He discovered the now-widely-studied Neural Collapse phenomenon in deep neural network training and invented the Survey Descent method for nonsmooth optimization. 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.

Email: xh332@cornell.edu

Website : https://xyhan.me 

Billy Jin

Billy Jin is a fifth-year PhD student in ORIE at Cornell University, advised by David Williamson. His research centers around data-driven decision making; in particular, in incorporating more realistic models of uncertainty, and designing algorithms that are robust to model errors. His recent contributions include work on pareto-optimal prediction-augmented algorithms, equity and fairness in online resource allocation, and better approximation algorithms for structured instances of the traveling salesman problem. Billy is a recipient of the NSERC graduate fellowship, and his work has appeared in venues such as NeurIPS, SODA, and IPCO. He graduated from the University of Waterloo in 2018 with a B.Math in Combinatorics & Optimization and Computer Science, where he was the recipient of the Alumni Gold Medal. 

Email: bzj3@cornell.edu

Website : https://people.orie.cornell.edu/bzj3/