Rui Chen

I am a Ph.D. student in the Robotics Institute at CMU, advised by Dr. Changliu Liu. I received my master's degree in Electrical & Computer Engineering and bachelor's degree in Computer Engineering from the University of Michigan, Ann Arbor. I also recieved a bachelor's degree in ECE from the Joint Institute at Shanghai Jiao Tong University.

My current research focuses on adaptable approaches to provably safe control and human-robot interaction. I used to work on connected and automated vehicles with both hardware (e.g., Lincoln MKZ platform) and software (e.g., auto map generation for Carla).

Email / CV / Google Scholar / Github

News

2024/03/10: Two papers accepted to TMLR.
2024/01/22: Three papers accepted to ACC 2024.
2023/06/01: Our paper at ICRA 2023 won the Outstanding Interaction Paper award!
2023/04/20: One paper accepted to IV 2023.
2023/04/20: One paper accepted to RA-L.
2023/01/16: One paper accepted to ICRA 2023.
2022/12/02: Our paper at CPHS22 won the best student paper award.
2022/08/15: One paper accepted to 4th IFAC Workshop on Cyber-Physical & Human-Systems, 2022.
2022/07/01: Presented at RSS22 workshop in Close-Proximity HRC.
2022/06/30: One paper accepted to IROS 2022.
2022/05/03: One paper accepted to AIM 2022.
2022/04/07: One paper accepted to ISFA 2022.
2022/01/28: Demonstrated lab work to the U.S. President at Mill 19. [CMU news]
2021/11/01: One peper accepted to Bayesian Deep Learning workshop, NeurIPS.

Research

See the following list for my work, with the latest on top.

	Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence Weiye Zhao, Feihan Li, Yifan Sun, Rui Chen, Tianhao Wei, Changliu Liu Submitted to International Conference on Machine Learning, 2024 [OpenReview]
	State-wise Constrained Policy Optimization Weiye Zhao, Rui Chen, Yifan Sun, Feihan Li, Tianhao Wei, Changliu Liu Transactions on Machine Learning Research, 2024 [OpenReview]
	GUARD: A Safe Reinforcement Learning Benchmark Weiye Zhao, Rui Chen, Yifan Sun, Ruixuan Liu, Tianhao Wei, Changliu Liu Transactions on Machine Learning Research, 2024 [OpenReview]
	Real-time Safety Index Adaptation for Parameter-varying Systems via Determinant Gradient Ascend Rui Chen, Weiye Zhao, Changliu Liu American Control Conference, 2024 [arXiv]
	Safety Index Synthesis with State-dependent Control Space Rui Chen, Weiye Zhao, Ruixuan Liu, Weiyang Zhang, Changliu Liu American Control Conference, 2024 [arXiv]
	Robust and Context-Aware Real-Time Collaborative Robot Handling via Dynamic Gesture Commands Rui Chen, Alvin Shek, Changliu Liu IEEE Robotics and Automation Letters, 2023 [paper][arXiv]
	Space-Time Conflict Spheres for Constrained Multi-Agent Motion Planning Anirudh Chari, Rui Chen, Changliu Liu IEEE Intelligent Vehicles Symposium, 2023 [arXiv]
	Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method Alvin Shek, Rui Chen, Changliu Liu IEEE International Conference on Robotics and Automation (ICRA), 2023 Outstanding Interaction Paper award [arXiv]
	A Composable Framework for Policy Design, Learning, and Transfer Toward Safe and Efficient Industrial Insertion Rui Chen, Chenxi Wang, Tianhao Wei, Changliu Liu IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022 [paper]
	Task-Agnostic Adaptation for Safe Human-Robot Handover Ruixuan Liu, Rui Chen, Changliu Liu 4th IFAC Workshop on Cyber-Physical & Human-Systems, 2022 Best student paper award [arXiv]
	Jerk-bounded Position Controller with Real-Time Task Modification for Interactive Industrial Robots Ruixuan Liu, Rui Chen, Yifan Sun, Yu Zhao, Changliu Liu IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2022 [paper]
	Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm Ruixuan Liu, Rui Chen, Changliu Liu International Symposium on Flexible Automation (ISFA), 2022 [paper]
	Latent Goal Allocation for Multi-Agent Goal-Conditioned Self-Supervised Imitation Learning Rui Chen, Peide Huang, Laixi Shi* NeurIPS Workshop on Bayesian Deep Learning, 2021 [paper]
	How to Evaluate Proving Grounds for Self-Driving? A Quantitative Approach Rui Chen, Mansur Arief, Weiyang Zhang, Ding Zhao IEEE Transactions on Intelligent Transportation Systems, 2021 [paper][arXiv]
	GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments Xiaotong Chen, Rui Chen, Zhiqiang Sui, Zhefan Ye, Yanqi Liu, R. Iris Bahar, Odest Chadwicke Jenkins IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019 [paper][arXiv][video]
	Active Learning for Risk-Sensitive Inverse Reinforcement Learning Rui Chen, Wenshuo Wang, Zirui Zhao, Ding Zhao arXiv, 2019 [arXiv]