Tongzhou Mu 木同舟 (original) (raw)
Tongzhou Mu
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About me
I study video world models for robotics at Rhoda AI.
I earned my Ph.D. from the University of California San Diego, where I was fortunate to be advised by Prof. Hao Su. My academic background also includes a B.Eng. from Zhejiang University, and an M.Sc. from UC San Diego. I previously interned at 1X Technologies, NVIDIA Robotics Lab, and Microsoft Research Asia.
I am the primary developer of the first ManiSkill benchmark, and a key contributor to its succeeding generations, ManiSkill 2 and ManiSkill 3. ManiSkill has become one of the most widely adopted open-source simulation frameworks for robot learning.
Publications & Preprints
Papers sorted by years. Representative papers are highlighted.
* indicates equal contribution.
2026
2025
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**ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI**Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Viswesh Nagaswamy Rajesh, Yong Woo Choi, Yen-Ru Chen, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, Hao Su Robotics: Science and Systems (RSS) 2025 [Project Page] [arXiv] [Code] |
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2024
2023
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**ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills**Jiayuan Gu, Fanbo Xiang, Xuanlin Li*, Zhan Ling*, Xiqiang Liu*, Tongzhou Mu* , Yihe Tang*, Stone Tao*, Xinyue Wei*, Yunchao Yao*, Xiaodi Yuan, Pengwei Xie, Zhiao Huang, Rui Chen, Hao Su * equally contributed authors are ordered by alphabets International Conference on Learning Representations (ICLR) 2023 [Project Page] [arXiv] [Code] [Challenge Website] |
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**Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation**Xiaoshuai Zhang, Rui Chen, Fanbo Xiang, Yuzhe Qin, Jiayuan Gu, Zhan Ling, Minghua Liu, Peiyu Zeng, Songfang Han, Zhiao Huang, Tongzhou Mu, Jing Xu, Hao Su IEEE Transactions on Robotics (T-RO) 2023 [arXiv] |
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2022
2021
2020
Before 2019
Talks
- Modeling the Physical World for Data-Centric Robotics
Invited Talk at Stanford Vision and Learning Lab, Jul 2024 - Modeling the Physical World for Embodied AI: Environments and Algorithms
Invited Talk at Microsoft Research Asia, Apr 2023 - Learning Neural Structrued Policy via Policy Refactorization
Ph.D. Thesis Proposal at UC San Diego, Mar 2023 - Boosting Reinforcement Learning and Planning with Demonstrations
Ph.D. Research Exam at UC San Diego, Jan 2023 - On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline
Pre-training Robot Learning Workshop at CoRL 2022, Dec 2022 - Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrations
Invited Talk at UC Berkeley Robot Learning Lab, Nov 2021
Invited Talk at Stanford Vision and Learning Lab, Dec 2021 - Task-driven Entity Abstraction from Visual Observations
Invited Talk at Qualcomm AI Lab, Mar 2020
Awards
- ACM-ICPC (International Collegiate Programming Contest) Asia Regional Contest Gold Medal, 2015
- China Computer Federation Elite Collegiate Award (top 108 in China), 2016
Misc
- I love powerlifting, tennis, golfing, and surfing in my free time.