Allan Zhou

About Me

I am a PhD student in computer science (artificial intelligence) at Stanford University, advised by Chelsea Finn. I am supported by the NSF Graduate Research Fellowship.

My research interests include meta-learning, reinforcement learning, and applied machine learning for robotics.

Previously I was a Google AI resident researching machine learning and robotics. I received a B.S. in Electrical Engineering and Computer Science from UC Berkeley.


  1. Discriminator Augmented Model-based Reinforcement Learning. Preprint. [arXiv]
    B. Haghgoo*, A. Zhou*, A. Sharma, C. Finn.
  2. Meta-Learning Symmetries by Reparameterization. ICLR 2021. [arXiv]
    A. Zhou, T. Knowles, C. Finn.
  3. Watch, Try, Learn: Meta-Learning from Demonstrations and Reward. ICLR 2020. [arXiv]
    A. Zhou, E. Jang, D. Kappler, A. Herzog, M. Khansari, P. Wohlhart, Y. Bai, M. Kalakrishnan, S. Levine, C. Finn.
  4. Cost functions for robot motion style. IROS 2018. [arXiv]
    A. Zhou, A. Dragan.
  5. Expressive Robot Motion Timing. HRI 2017. [arXiv]
    A. Zhou, D. Hadfield-Menell, A. Nagabandi, A. Dragan.

*Equal contribution.


  1. City2City: Restyling cities with Google streetview.