Biography

I am an assistant professor in Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University. Prior to that, I was working with Prof. Masayoshi Tomizuka at the University of California, Berkeley and received my Ph.D. degree in 2020. I received my Bachelor degree from Tsinghua University in 2015.

I run the Intelligent Systems and Robotics Laboratory (ISR Lab), where we are working at an intersection of artificial intelligence and robotics to build advanced robotic systems with high performance and high intelligence. My research interests include reinforcement learning, robotics, control, and autonomous driving. ​

News

  • We are actively recruiting Postdocs, Engineers, PhDs, Masters and RAs, please drop me an email with your resume via jianyuchen@tsinghua.edu.cn.
  • 2022-12: 1 papers accpeted to RAL!
  • 2022-11: 1 papers accpeted to RAL and one paper accepted to TNNLS!
  • 2022-09: 3 papers accpeted to NeurIPS 2022 and one paper accepted to CoRL 2022!
  • 2022-07: One paper received best paper finalist in L4DC 2022 and one paper accpeted to CDC 2022!
  • 2022-06: One paper accepted to IROS 2022!
  • 2022-05: 3 papers accepted to ICML 2022!
  • 2022-04: One paper accepted to TNNLS!
  • 2022-03: 2 papers accepted to L4DC 2022!
  • 2022-01: One paper accepted to ICRA 2022!

Recent Publications

(2023). Model-Free Safe Reinforcement Learning through Neural Barrier Certificate. In IEEE Robotics and Automation Letters (RAL), 2023.

(2023). Chance-Constrained Iterative Linear-Quadratic Stochastic Games. In IEEE Robotics and Automation Letters (RAL), 2023.

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(2022). Policy-Iteration-Based Finite-Horizon Approximate Dynamic Programming for Continuous-Time Nonlinear Optimal Control. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

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(2022). Reinforcement learning with Demonstrations from Mismatched Task under Sparse Reward. In Conference on Robot Learning (CoRL), 2022.

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(2022). Unsupervised Skill Discovery via Recurrent Skill Training. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning. In Conference on Neural Information Processing Systems (NeurIPS), 2022.

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(2022). A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.

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(2022). Flow-based Recurrent Belief State Learning for POMDPs. In International Conference on Machine Learning (ICML), 2022.

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(2022). Reachability Constrained Reinforcement Learning. In International Conference on Machine Learning (ICML), 2022.

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