I am a second-year Ph.D. student in Computer Science Department, UCLA, advised by Prof. Song-Chun Zhu. As a member of Center for Vision, Cognition, Learning and Autonomy (VCLA), I am also actively advised by Prof. Ying Nian Wu. I obtained BEng degree in Computer Science from The Hong Kong University of Science and Technology (HKUST), advised by Prof. Fangzhen Lin.
My current research focuses on learning generalizable representations of i) core cognitive knowledge such as objects and physics, ii) high-level concepts such as categories, relations, and magnitudes, and iii) task-oriented abstraction such as options, affordances and utility, for out-of-distribution reasoning and generalized planning. The ultimate goal is to endow embodied agents with a computational framework to develop environment-invariant knowledge from interaction and communication. I draw inspiration broadly from classical AI, cognitive science, computational neuroscience, and statistical learning, etc. Previously, I studied (Inverse) Reinforcement Learning and its application to Differentiable Neural Architecture Search.