Hi! I’m Chen, a Postdoctoral scholar in Mechanical Engineering at UC Berkeley. I am a member of the Mechanical Systems Control Lab supervised by Prof. Masayoshi Tomizuka. Prior to this, I obtained my PhD in Mechanical Engineering at UC Berkeley, and my bachelor degree in Mechanical Engineering from Hong Kong University of Science and Technology (HKUST). I have also spent time in Honda Research Institute and Waymo as intern.
The goal of my research is to develop trustworthy and safe intelligent autonomous systems interacting with humans (e.g., autonomous vehicles). I am interested in improving the transparency and robustness of learning-based autonomous systems, by incorporating domain knowledge and other techniques (e.g., model-based control, explainable AI) with deep learning models in a principled manner. Applications of my research include multi-agent trajectory prediction, interaction modeling, motion planning, and vehicle control.
For more information, please refer to my CV. Please feel free to contact me for research discussion and collaboration!
I am on the 2022-2023 academic job market.
- 07/2022: We are organizing the workshop on Progress and Challenges in Building Trustworthy Embodied AI at NeurIPS 2022!
- 07/2022: One paper on trajectory prediction pretraining is accepted by ECCV 2022.
- 06/2022: Selected for DSCD Rising Stars Invited Talks at MECC 2022.
- 06/2022: Three papers are accepted by IROS 2022.
- 06/2022: One paper on hierarchical offline RL is accepted by RA-L.
- 05/2022: Successfully defended my dissertation titled “Designing Explainable Autonomous Driving System for Trustworthy Interaction”.
- 05/2022: Associate editor of IEEE Intelligent Transportation Systems Conference 2022.
- 09/2021: One paper on behavior prediction is accepted by NeurIPS 2021.
- 09/2021: One paper on conservative offline RL is accepted by CoRL 2021.
- 05/2021: Associate editor of IEEE Intelligent Transportation Systems Conference 2021.
- 05/2021: Co-organizing IROS MAIR2 Workshop on Multi-Agent Interaction and Relational Reasoning.