陈建宇 - 清华大学 - 交叉信息研究院

个人简介

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.

研究领域

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.

近期论文

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Yujie Yang, Yuxuan Jiang, Yichen Liu, Jianyu Chen, Shengbo Eben Li (2023). Model-Free Safe Reinforcement Learning through Neural Barrier Certificate. In IEEE Robotics and Automation Letters (RAL), 2023. Hai Zhong, Yutaka Shimizu, Jianyu Chen (2023). Chance-Constrained Iterative Linear-Quadratic Stochastic Games. In IEEE Robotics and Automation Letters (RAL), 2023. Ziyu Lin, Jingliang Duan, Shengbo Eben Li, Haitong Ma, Jie Li, Jianyu Chen, Bo Cheng, Jun Ma (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. Yanjiang Guo, Jingyue Gao, Zheng Wu, Chengming Shi, Jianyu Chen (2022). Reinforcement learning with Demonstrations from Mismatched Task under Sparse Reward. In Conference on Robot Learning (CoRL), 2022. Zheyuan Jiang, Jingyue Gao, Jianyu Chen (2022). Unsupervised Skill Discovery via Recurrent Skill Training. In Conference on Neural Information Processing Systems (NeurIPS), 2022. Yao Mu, Yuzheng Zhuang, Fei Ni, Bin Wang, Jianyu Chen, Jianye Hao, Ping Luo (2022). Decomposed Mutual Information Optimization for Generalized Context in Meta-Reinforcement Learning. In Conference on Neural Information Processing Systems (NeurIPS), 2022. Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu (2022). An Adaptive Deep RL Method for Non-Stationary Environments with Piecewise Stable Context. In Conference on Neural Information Processing Systems (NeurIPS), 2022. Xiang Zhu, Shucheng Kang, Jianyu Chen (2022). A Contact-Safe Reinforcement Learning Framework for Contact-Rich Robot Manipulation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022. Xiaoyu Chen, Yao Mark Mu, Ping Luo, Shengbo Eben Li, Jianyu Chen (2022). Flow-based Recurrent Belief State Learning for POMDPs. In International Conference on Machine Learning (ICML), 2022. Dongjie Yu, Haitong Ma, Shengbo Eben Li, Jianyu Chen (2022). Reachability Constrained Reinforcement Learning. In International Conference on Machine Learning (ICML), 2022. Yao Mark Mu, Shoufa Chen, Mingyu Ding, Jianyu Chen, Runjian Chen, Ping Luo (2022). CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer. In International Conference on Machine Learning (ICML), 2022. Yuheng Lei, Jianyu Chen, Shengbo Eben Li, Sifa Zheng (2022). Performance-Driven Controller Tuning via Derivative-Free Reinforcement Learning. In IEEE Conference on Decision and Control (CDC), 2022. Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng, Jianyu Chen (2022). Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning. In Annual Conference on Learning for Dynamics and Control (L4DC), 2022 (Best Paper Award Finalists). Yujie Yang, Jianyu Chen, Shengbo Li (2022). Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study. In Annual Conference on Learning for Dynamics and Control (L4DC), 2022. Xinghao Zhu, Yefan Zhou, Yongxiang Fan, Lingfeng Sun, Jianyu Chen, Masayoshi Tomizuka (2022). Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Loss. In IEEE International Conference on Robotics and Automation (ICRA), 2022. Baiyu Peng, Jingliang Duan, Jianyu Chen, Shengbo Eben Li, Genjin Xie, Congsheng Zhang, Yang Guan, Yao Mu, Enxin Sun (2022). Model-Based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian. In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022. Qiushan Guo, Yao Mu, Jianyu Chen, Tianqi Wang, Yizhou Yu, Ping Luo (2022). Scale-Equivalent Distillation for Semi-Supervised Object Detection. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. Baiyu Peng, Yao Mu, Yang Guan, Shengbo Eben Li, Yuming Yin, Jianyu Chen (2021). Model-based Actor-Critic with Chance Constraint for Stochastic System. In IEEE Conference on Decision and Control (CDC), 2021. Yao Mu, Yuzheng Zhuang, Bin Wang, Guangxiang Zhu, Wulong Liu, Jianyu Chen, Ping Luo, Shengbo Li, Chongjie Zhang, Jianye Hao (2021). Model-Based Reinforcement Learning via Imagination with Derived Memory. In Conference on Neural Information Processing Systems (NeurIPS), 2021. Ziqing Gu, Yujie Yang, Jingliang Duan, Shengbo Eben Li, Jianyu Chen, Wenhan Cao, Sifa Zheng (2021). Belief State Separated Reinforcement Learning for Autonomous Vehicle Decision Making under Uncertainty. In IEEE International Intelligent Transportation Systems Conference (ITSC), 2021. Haitong Ma, Jianyu Chen, Shengbo Eben, Ziyu Lin, Yang Guan, Yangang Ren, Sifa Zheng (2021). Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. Jianyu Chen, Yutaka Shimizu, Liting Sun, Masayoshi Tomizuka, Wei Zhan (2021). Constrained Iterative LQG for Real-Time Chance-Constrained Gaussian Belief Space Planning. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. Baiyu Peng, Yao Mu, Jingliang Duan, Yang Guan, Shengbo Eben Li, Jianyu Chen (2021). Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning. In IEEE Intelligent Vehicles Symposium (IV), 2021 (Best Student Paper Award Finalists). Jinning Li, Liting Sun, Jianyu Chen, Masayoshi Tomizuka, Wei Zhan (2021). A Safe Hierarchical Planning Framework for Complex Driving Scenarios based on Reinforcement Learning. In IEEE International Conference on Robotics and Automation (ICRA), 2021. Long Xin, Yiting Kong, Shengbo Eben Li, Jianyu Chen, Yang Guan, Masayoshi Tomizuka, Bo Cheng (2021). Enable Faster and Smoother Spatio-Temporal Trajectory Planning for Autonomous Vehicles in Constrained Dynamic Environment. In Proceedings of the Institution of Mechanical Engineers, Part D：Journal of Automobile Engineering, 2021. Jianyu Chen, Shengbo Eben Li, Masayoshi Tomizuka (2021). Interpretable End-to-End Urban Autonomous Driving with Latent Deep Reinforcement Learning. In IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2021. Wenhan Cao, Jianyu Chen, Jingliang Duan, Shengbo Eben Li, Yao Lyu, Ziqing Gu, Yuhang Zhang (2021). Reinforced Optimal Estimator. In Modeling, Estimation and Control Conference (MECC), 2021 (Best Student Paper Award Finalists). Yutaka Shimizu, Wei Zhan, Liting Sun, Jianyu Chen, Shinpei Kato, Masayoshi Tomizuka (2020). Motion Planning for Autonomous Driving With Extended Constrained Iterative LQR. In Dynamic Systems and Control Conference (DSCC), 2020. Jianyu Chen, Zhuo Xu, Masayoshi Tomizuka (2020). End-to-End Autonomous Driving Perception with Sequential Latent Representation Learning. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020. Jianyu Chen, Bodi Yuan, Masayoshi Tomizuka (2019). Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019. Jianyu Chen, Bodi Yuan, Masayoshi Tomizuka (2019). Model-Free Deep Reinforcement Learning for Urban Autonomous Driving. In IEEE Intelligent Transportation Systems Conference (ITSC), 2019. Chen Tang, Jianyu Chen, Masayoshi Tomizuka (2019). Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network. In IEEE International Conference on Robotics and Automation (ICRA), 2019. Jianyu Chen, Wei Zhan, Masayoshi Tomizuka (2019). Autonomous Driving Motion Planning With Constrained Iterative LQR. In IEEE Transactions on Intelligent Vehicles (T-IV), 2019. Long Xin, Pin Wang, Ching-Yao Chan, Jianyu Chen, Shengbo Eben Li, Bo Cheng (2018). Intention-aware Long Horizon Trajectory Prediction of Surrounding Vehicles using Dual LSTM Networks. In IEEE Intelligent Transportation Systems Conference (ITSC), 2018. Jianyu Chen, Changliu Liu, Masayoshi Tomizuka (2018). FOAD: Fast Optimization-based Autonomous Driving Motion Planner. In Annual American Control Conference (ACC), 2018. Jianyu Chen, Zining Wang, Masayoshi Tomizuka (2018). Deep Hierarchical Reinforcement Learning for Autonomous Driving with Distinct Behaviors. In IEEE Intelligent Vehicles Symposium (IV), 2018. Jianyu Chen, Chen Tang, Long Xin, Shengbo Eben Li, Masayoshi Tomizuka (2018). Continuous Decision Making for On-Road Autonomous Driving under Uncertain and Interactive Environments. In IEEE Intelligent Vehicles Symposium (IV), 2018 (Oral Presentation). Bodi Yuan, Jianyu Chen, Weidong Zhang, Hung-Shuo Tai, Sara McMains (2018). Iterative Cross Learning on Noisy Labels. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2018. Jianyu Chen, Wei Zhan, Masayoshi Tomizuka (2017). Constrained Iterative LQR for On-Road Autonomous Driving Motion Planning. In IEEE Intelligent Transportation Systems Conference (ITSC), 2017. Wei Zhan, Jianyu Chen, Ching-Yao Chan, Changliu Liu, Masayoshi Tomizuka (2017). Spatially-Partitioned Environmental Representation and Planning Architecture for On-Road Autonomous Driving. In IEEE Intelligent Vehicles Symposium (IV), 2017. Changliu Liu, Jianyu Chen, Trong-Duy Nguyen, Masayoshi Tomizuka (2017). The Robustly-Safe Automated Driving System for Enhanced Active Safety. In SAE Technical Paper, 2017.