Mingrui YU

Mingrui YU

A robotics learner

Mingrui YU / 于铭瑞 / Harry YU

I am Mingrui YU, a robotics researcher. I’m now pursuing the Ph.D. degree in the Intelligent Manipulation Lab, Department of Automation, Tsinghua University, supervised by Prof. Xiang Li. From 10/2023 to 03/2024, I was a visiting student at the MSC Lab in UC Berkeley, supervised by Prof. Masayoshi Tomizuka.

Research Interest: I’m interested in machine learning, planning, and control with their applications to robotic dexterous manipulation of various objects, including in-hand manipulation and deformable object manipulation.

I am leading an NSFC Youth Student Research Project (for PhD students) / 首批国家自然科学基金青年学生基础研究项目（博士生项目）entitled “Visual-tactile dexterous manipulation of deformable linear objects with a dual-arm robot”.

Future Opportunities: I am open to potential academic and industry job opportunities following my graduation in June 2026. Please feel free to contact me.

Email: mingruiyu98@gmail.com (recommended); ymr20@mails.tsinghua.edu.cn (国内使用).

Education

Department of Automation, Tsinghua University (Beijing, China)   08/2020 - 06/2026 (expected)
Ph.D. Student in Control Science and Engineering
GPA: 3.95/4.0, Ranking: 3/84

Department of Automation, Xi’an Jiaotong University (Xi’an, China)   08/2016 - 07/2020
B.Eng. in Automation (Honors Engineering Program, 钱学森班)
GPA: 4.09/4.3, Ranking: 1/35

Research Experience

Robotics X, Tencent (Shenzhen, China)   06/2024 - 09/2024
Advisor: Dr. Yu Zheng
Topic: Dexterous grasping and manipulation

Mechanical Systems Control Lab, University of California, Berkeley   10/2023 - 03/2024
Advisor: Prof. Masayoshi Tomizuka
Topic: Dexterous manipulation of (deformable) objects

Institute of Automation, Chinese Academy of Sciences (Beijing, China)   07/2018 - 06/2019
Advisor: Prof. Yisheng Lv
Topic: Reinforment learning for intelligent transportation system

Publications

Journal Papers

  1. M. Yu, K. Lv, C. Wang, Y. Jiang, M. Tomizuka, and X. Li, “Generalizable whole-body global manipulation of deformable linear objects by dual-arm robot in 3-D constrained environments”, The International Journal of Robotics Research, 2024. [Paper] [Website]
  2. M. Yu, K. Lv, H. Zhong, S. Song, and X. Li, “Global Model Learning for Large Deformation Control of Elastic Deformable Linear Objects: An Efficient and Adaptive Approach,” IEEE Transactions on Robotics, 2022. [Paper] [Website]
  3. 于铭瑞, 李翔, “面向线状柔性物体的机器人操作研究进展与展望”, 机器人, 2024.

Conference Papers

  1. M. Yu, B. Liang, X. Zhang, X. Zhu, L. Sun, C. Wang, X. Li, M. Tomizuka, “In-Hand Following of Deformable Linear Objects Using Dexterous Fingers With Tactile Sensing”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. (Oral, Top 12%) [Paper] [Website]
  2. Y. Jiang, M. Yu , X. Zhu, M. Tomizuka, X. Li, “Contact-Implicit Model Predictive Control for Dexterous In-hand Manipulation: A Long-Horizon and Robust Approach”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. [Paper] [Website]
  3. X. Yan, S. Luo, Y. Jiang, M. Yu, C. Chen, G. Huang, X. Li, “A Unified Interaction Control Framework for Safe Robotic Ultrasound Scanning with Human-Intention-Aware Compliance”, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. (Oral, Top 12%)
  4. M. Yu, K. Lv, C. Wang, M. Tomizuka, and X. Li, “A Coarse-to-Fine Framework for Dual-Arm Manipulation of Deformable Linear Objects with Whole-Body Obstacle Avoidance”, 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. (Best Paper Award at the ICRA 2023 Workshop on Representing and Manipulating Deformable Objects) [Paper] [Website]
  5. K. Lv, M. Yu, Y. Pu, and X. Li, “Learning to Estimate 3-D states of Deformable Linear Objects from Single-Frame Occluded Point Clouds”, 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. [Paper] [Video]
  6. M. Yu, H. Zhong, and X. Li, “Shape Control of Deformable Linear Objects with Offline and Online Learning of Local Linear Deformation Models,” 2022 IEEE International Conference on Robotics and Automation (ICRA), 2022. [Paper] [Website]
  7. 于铭瑞, 贾永奕, 李翔, “高危化工机器人研究与应用综述”, 2021 中国自动化大会 (CAC), 2021. [Paper]
  8. H. Zhong, Z. Xu, G. Ma, M. Yu, and X. Li, “Regressor-Based Model Adaptation for Shaping Deformable Linear Objects with Force Control,” 2023 IEEE Interational Conference on Robotics and Biomimetics (ROBIO), 2023. [Paper]
  9. F. Xiong, Y. Ding, M. Yu, W. Zhao, N. Zheng, P. Ren, “A lightweight sequence-based unsupervised loop closure detection,” 2021 International Joint Conference on Neural Networks (IJCNN), 2021. [Paper]
  10. M. Yu, J. Chai, Y. Lv and G. Xiong, “An effective deep reinforcement learning approach for adaptive traffic signal control,” 2020 Chinese Automation Congress (CAC), 2020. [Paper]

Patents

  1. 吕宜生, 柴嘉骏, 于铭瑞, 陈圆圆, 熊刚, 朱凤华, 王飞跃. 基于深度强化学习单路口交通信号控制方法、系统、装置. 申请号：2019106294891, 申请日：2019.07.12. 授权公告号：CN110428615B，授权公告日：2021.06.22.

  2. 孙宏滨, 南智雄, 于铭瑞,  魏平, 徐林海, 郑南宁. 一种车辆的车道保持控制方法. 申请号：2018100047576, 申请日：2018.01.03. 授权公告号：CN108297866B, 授权公告日：2019.10.15.

Competitions

Awards & Honors

Projects

Project Page

Academic Service