About Me

I am a PhD student at Stanford University, advised by Emma Brunskill. I was a PhD student at CMU, and moved to Stanford with Prof. Emma Brunskill in 2017. Previously I obtained my B.S. in Machine Intelligence from Peking University in 2016. As an undergraduate, I was interested in machine learning theory and optimization, and had the fortune of doing research under the supervision of Liwei Wang.


I am motivated by advancing reinforcement learning (RL) in real-world applications with provable guarantees where sample efficiency and safety would be huge challenges. Thus I am interested in RL algorithms that collect and use sample (provably) more efficiently, especially in off-line manner. The main problems I am interested in are also known as efficient exploration and off-policy RL. I am also attracted by other problems about learning and reasoning from interactions, including contextual bandits problem and causal inference. I am interested in applications of these methods in helping and augmenting more general people, for examples healthcare and education. Currently I'm working closely with Livongo Health on the application of reinforcement learning in applied health signals.



Workshop Papers


A collection of my interests out of reasearch area.