I am an AI/ML Engineer and Researcher at GSK AI. My research interests include compression and acceleration for deep neural networks (using quantization, pruning, and knowledge distillation), contrastive representation learning for images, generative models, and graph signal processing. Additionally, I am widely interested in the mathematical foundations of machine learning and deep learning, to explore their expressivity, learnability, and generalizability.

In 2023, I obtained my Ph.D. degree in applied mathematics at University of California San Diego (UCSD). Rayan Saab and Alexander Cloninger are my advisors. I got my M.S. degree in statistics at the University of Chicago in 2018 where I was supervised by Lek-Heng Lim. Before that, I received my B.S. degree in information and computation science at Beijing Jiaotong University (a.k.a. Northern Jiaotong University) in 2016.