Hello, welcome

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Currently, I’m a Ph.D. student in Computer Science at ETH Zurich, advised by Prof. Niao He. Before that, I was a Ph.D. student in Computer Science at University of Illinois at Urbana–Champaign (UIUC), advised by Prof. Nan Jiang. I completed my B.E. in Computer Science at Beihang University.

My research mainly focus on reinforcement learning, and I’ve also got involved in projects related to computer vision. Besides, I’m also interested in other machine learning topics, such as optimization, deep learning theory and etc.



Selected Publications


Multi-Agent RL

  1. Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL
    Jiawei Huang, Niao He, and Andreas Krause
    Preprint 2024
  2. On the Statistical Efficiency of Mean Field Reinforcement Learning with General Function Approximation
    Jiawei Huang, Batuhan Yardim, and Niao He
    AISTATS 2024

Transfer RL

  1. Robust Knowledge Transfer in Tiered Reinforcement Learning
    Jiawei Huang, and Niao He
    NeurIPS 2023
  2. Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret
    Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, and Tie-Yan Liu
    NeurIPS 2022

Others

  1. Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality
    Jiawei Huang, Jinglin Chen, Li Zhao, Tao Qin, Nan Jiang, and Tie-Yan Liu
    ICLR 2022 (Spotlight)