Qinghua Liu

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I am a Ph.D. candidate in the Department of Electrical and Computer Engineering at Princeton University. I am fortunate to be advised by Chi Jin. I develop learning-based approaches for sequential decision-making. In particular, my PhD research has focused on reinforcement learning (RL), spanning a diverse collection of areas including multi-agent RL (Stochastic Game), partially observable RL (POMDP, PSR), and RL with large state spaces (Function Approximation).

During summer 2022, I was a research scientist intern at DeepMind, working with Csaba Szepesvári and Gellért Weisz. Previously, I received a B.E. degree in Electrical Engineering and a B.S. degree in Mathematics from Tsinghua University in 2018.

[Google Scholar]


(α-β order) denotes alphabetical authorship ordering, and (*,+) denote equal contribution

Multi-Agent Reinforcement Learning

Partially Observable Reinforcement Learning

Reinforcement Learning with Large State Spaces

Other Works


Reviewers for COLT, NeurIPS, ICML, JMLR, ICLR, ALT, IEEE-TSP, IEEE-TAC, etc.