I am a PhD student of Computer Science at University of Texas at Austin. I am very honored to be advised by Prof. Peter Stone and Prof. Qiang Liu. I have a broad interest in reinforcement learning, continual learning, imitation learning and their applications in robotics. Before coming to UT, I was a master student of Computer Science at Stanford University, where I was fortunate to work with Prof. Fei-Fei Li and Prof. Yuke Zhu on planning under uncertainty, and Prof. Jure Leskovec on massive data mining. I finished my undergraduate study at the Johns Hopkins University, where I was fortunate to work with Prof. Jason Eisner on generative syntactic parsing.
APPLD: Adaptive Planner Parameter Learning from DemonstrationRA-L / IROS 2020
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPsIJCAI 2020
Predicting pregnancy using large-scale data from a women’s health tracking mobile applicationWWW 2019
Paper review on "Learning from Untrusted Data"
Winter 2019 | Stanford, CA, USA
CS 234: Reinforcement Learning
Fall 2016 | Baltimore, MD, USA
EN 601.465/665: Natural Language Processing
Fall 2015 | Baltimore, MD, USA
EN 600.363/463: Algorithms I
Research Engineer Intern
Jun - Sept 2018 | Sunnyvale, CA, USA
Software Engineer & Engineer Practicum Intern
May - Aug 2015/2016 | Los Angeles, CA, USA