Information Theory, Machine Learning Theory, Distributed Computing
Qian received his Ph.D. from the Department of Electrical and Computer Engineering at University of Southern California (USC). He received an M.Eng. degree in Electrical Engineering and a B.S. degree in Physics and EECS, both from Massachusetts Institute of Technology (MIT). Before joining UCSB, Qian was a postdoctoral researcher at Princeton University.
His research interests span information theory, machine learning theory, distributed computing, and many other problems math-related. His research goal is to establish the fundamental limits of physical systems, which involves inventing new mathematical tools to prove impossibility results, and algorithmic designs to achieve optimality. He received the Thomas M. Cover Dissertation Award in 2022 for his works on coded computation, and the Jack Keil Wolf ISIT Student Paper Award in 2017 for coded caching.