Yunxi TANG

Postdoctoral Researcher in Robotics & AI

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The Chinese University of Hong Kong

Multi-Scale Medical Robotics Center

Hong Kong SAR

I am a Postdoctoral Researcher in robotics and artificial intelligence at The Chinese University of Hong Kong (CUHK), affiliated with the Multiscale Robotics Center in Hong Kong SAR. Previously, I received my Ph.D. from the Bioinspired Robotics and Medical Technology (BMT) group at CUHK, where I worked with Prof. Samuel Au.

My research focuses on enabling robots to perceive, model, and manipulate deformable objects, with a particular emphasis on autonomous surgical systems. My work lies at the intersection of:

- Learning-based control and manipulation
- Vision-based reconstruction and perception
- Safety-aware autonomous surgical systems
- Deformable Object modeling, planning, and state estimation

I am particularly interested in bridging simulation and real-world deployment through high-fidelity simulation and digital twin technologies. My long-term goal is to build safe, reliable, and intelligent autonomous surgical systems that can operate robustly in complex, real-world environments.

news

May 01, 2026 CUHK MSc students with a strong interest in Robotics and AI are encouraged to contact me via email to explore research opportunities in embodied surgical intelligence within the BMT group, focusing on deformable object manipulation and surgical world action model.
Apr 24, 2026 One TMech paper, “Hierarchical Deformation Planning and Neural Tracking for DLOs in Constrained Environments,” has been accepted.
Oct 20, 2025 One RAL paper, “Generative 3D State Estimation for DLOs From Partial Observations,” has been accepted.
Jul 22, 2025 Successfully passed my Ph.D. defense at The Chinese University of Hong Kong. Thesis: Learning-based Deformable Linear Object Manipulation in Unstructured Environments.
Jul 14, 2024 One RSS paper, “Homotopic path set planning for robot manipulation and navigation,” has been accepted.

selected publications

  1. hdp.png
    Hierarchical Deformation Planning and Neural Tracking for DLOs in Constrained Environments
    Yunxi Tang, Tianqi Yang, Jing Huang, and 2 more authors
    IEEE/ASME Transactions on Mechatronics, 2026
  2. gen_dlo.png
    Generative 3D State Estimation for DLOs From Partial Observations
    Yunxi Tang, Tianqi Yang, Jing Huang, and 2 more authors
    IEEE Robotics and Automation Letters, 2025
  3. cdlom_ral.png
    Learning-based MPC with safety filter for constrained deformable linear object manipulation
    Yunxi Tang, Xiangyu Chu, Jing Huang, and 1 more author
    IEEE Robotics and Automation Letters, 2024
  4. tailed_quad.png
    Towards safe landing of falling quadruped robots using a 3-dof morphable inertial tail
    Yunxi Tang, Jiajun An, Xiangyu Chu, and 3 more authors
    In 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023