I am a postdoctoral research fellow in the Berkeley AI Research (BAIR) Lab, the Department of Electrical Engineering and Computer Sciences, UC Berkeley, working with Prof. Kurt Keutzer and Prof. Trevor Darrell. My research interests cover deep learning, computer vision, and reinforcement learning, especially on machine learning with limited training data, including low-shot learning, domain adaptation, and meta-learning, which enables the learning system to automatically adapt to real-world variations and new environments. I was one of the “2018 Rising Stars in EECS” (a highly selective program launched at MIT in 2012, which has since been hosted at UC Berkeley, Carnegie Mellon, and Stanford annually). I have also been selected for the Qualcomm Innovation Fellowship (QInF) Finalist Award and Chiang Chen Overseas Graduate Fellowship. I received her Ph.D. from Carnegie Mellon University in 2018.



Label efficient learning

2013 - 2018

Carnegie Mellon University

Advised by Prof. Jose M.F. Moura, and Joao P. Costeira.

Domain adaptation

Few shot learning

Meta learning

2010 - 2013

Peking University

Advised by Prof. Wen Gao and Xiaodong Xie.

2006 - 2010

Southeast University