I'm an Assistant Professor of Computer Science at Princeton University. I received my Ph.D. in Computer Science from UC Berkeley, advised by Trevor Darrell, and B.S. in Computer Science from Yao Class, Tsinghua University. Before joining Princeton, I was a research scientist at Meta FAIR, New York. I also conducted research at Cornell, Intel, and Adobe.

My research areas are deep learning and computer vision, with an emphasis on understanding how models work and behave. My work spans vision and language, unified by a focus on deep learning methods, representations, and architectures. I explore simple approaches to gain empirical insights into how deep learning works.

Research intern / visiting positions: please fill out this form to get in touch.
Prospective PhD students: please apply to Princeton's CS PhD program and mention my full name in your application.
Prospective Postdocs: please consider applying to and working with me through the PLI Postdoctoral Fellow positions.