Jimmy Zhang

I am an assistant professor in the IE department at Purdue. I design efficient large-scale algorithms for function-constrained optimization, data-driven optimization, distributed optimization, risk-averse optimization, stochastic optimization, and reinforcement learning. These works are motivated by complex problems from machine learning and decision-making applications, where, in addition to a good performance, the solution is required to be robust to uncertainty, to be fair, and to respect privacy, etc. Though my development is based on rigorous theoretical complexity analysis, special attention has been paid to practice (see the figure attached below). More generally, I am interested in the broad area of machine learning and operations research.

Previously, I was a post-doc at MIT LIDS working with Dr. Suvrit Sra and Dr. Hand Paul at Northeastern, and I obtained my Ph.D. in Operations Research at Georgia Tech ISyE, advised by Professor Guanghui (George) Lan.

Before ISyE, I got a bachelor's degree (Magna Cum Laude) in Statistics and Mathematics from Rice University. I was fortunate to be advised by Professor Richard Tapia.