Completed multiple papers as a core contributor, including:
- OmniDexGrasp: Generalizable Dexterous Grasping via Foundation Model and Force Feedback
- TypeTele: Releasing Dexterity in Teleoperation by Dexterous Manipulation Types
- TacCap: A Wearable FBG-Based Tactile Sensor for Seamless Human-to-Robot Skill Transfer
- AffordDexGrasp: Open-set Language-guided Dexterous Grasp with Generalizable-Instructive Affordance
- iManip: Skill-Incremental Learning for Robotic Manipulation
- Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework
- ChainHOI: Joint-based Kinematic Chain Modeling for Human-Object Interaction Generation
- Grasp as You Say: Language-guided Dexterous Grasp Generation
- Real-to-Sim Grasp: Rethinking the Gap between Simulation and Real World in Grasp Detection
Research Experience
Conducting research work at iSEE Lab.
Education
Third-year Ph.D. student in computer science at Sun Yat-Sen University, advised by Prof. Wei-Shi Zheng; M.S. in control science and engineering from Southeast University, advised by Prof. Dan Niu; B.S. in automation from Northeastern University.
Background
Research interests include robotics AI, particularly dexterous grasp and manipulation. Additionally, he maintains a strong interest in and active engagement with humanoid robotics, MLLM-driven manipulation, and dexterous hand hardware.