I am currently a second year Ph.D. student at Princeton University, and I am fortunate to be advised by Prof. Sanjeev Arora.
I completed my undergraduate at Andrew Chi-Chih Yao’s CS pilot class at Tsinghua University, where I am advised by Prof. Wei Chen. Previously, I am also a reserach intern at Microsoft Research Asia Theory group and my mentor is Prof. Wei Chen. In my junior year, I also visited Duke University where I had a great time working with Prof. Rong Ge.
I am broadly interested in theoretical machine learning. Some particular interests include theory for natual language processing, deep learning theory, theory of optimization and federated learning, online algorithms and online leraning.
- [Jan. 2022] New paper out: BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression.
- [Dec. 2021] New paper out: Faster Rates for Compressed Federated Learning with Client-Variance Reduction.
- [Aug. 2021] I give a talk at FLOW: Federated Learning One World Seminar about our new federated learning paper.
haoyu AT princeton DOT edu
zhaohy16 AT mail DOT tsinghua DOT org DOT cn
thomaszhao1998 AT gmail DOT com