Yuqing Du

yuqing_du (at) berkeley (dot) edu

Hello! I am a fourth year PhD student at UC Berkeley advised by Professor Pieter Abbeel at the Berkeley Artificial Intelligence Research (BAIR) Lab. I received my B.A.Sc in Engineering Physics from the University of British Columbia, where I was advised by Professors Machiel Van der Loos and Elizabeth Croft at the Collaborative Advanced Robotics and Intelligent Systems (CARIS) Lab.

Currently I am interested in developing unsupervised reinforcement learning methods to reduce reliance on hand-crafted rewards and highly curated datasets. Some directions I am curious about: 1) understanding which objectives can successfully intrinsically motivate agents to learn emergent, useful behaviours, 2) how can we leverage human demonstrations, priors, and feedback to bootstrap exploration in open-ended environments, and 3) how can we use multi-agent interactions to automatically generate learning curricula. Specific applications I am interested in include real-world robotics and assistive software agents.


  1. ICML 2022
    Bayesian Imitation Learning for End-to-End Mobile Manipulation
    International Conference on Machine Learning (ICML) 2022
    july 2022
  2. ICLR 2022
    It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation
    Du, Yuqing, Abbeel, Pieter, and Grover, Aditya
    International Conference on Learning Representations (ICLR) 2022
    april 2022
  3. ICRA 2021
    Auto-Tuned Sim-to-Real Transfer
    (Best Cognitive Robotics Paper Finalist)
    2021 International Conference on Robotics and Automation (ICRA)
    june 2021
  4. NeurIPS 2020
    AvE: Assistance via Empowerment
    2020 Neural Information Processing Systems (NeurIPS)
    dec 2020
  5. ICRA 2019
    Group Surfing: A Pedestrian-Based Approach to Sidewalk Robot Navigation
    2019 International Conference on Robotics and Automation (ICRA)
    may 2019


  1. Practical Imitation Learning in the Real World via Task Consistency Loss
    Khansari, Mohi, Ho, Daniel, Du, Yuqing, Fuentes, Armando, Bennice, Matthew, Sievers, Nicolas, Kirmani, Sean, Bai, Yunfei, and Jang, Eric

    feb 2022
  1. Robust Reinforcement Learning using Adversarial Populations

    aug 2020