Yafei Ou
Papers
10
Total Citations
107
H-Index
6
About
Yafei Ou is a leading researcher in surgical robotics, specializing in autonomous robot-assisted surgery, reinforcement learning (RL), and human-robot interaction. His work focuses on automating complex surgical subtasks, such as indirect tissue manipulation, blood suction, and endoscopic camera control, using sim-to-real RL approaches. Ou’s major contributions include pioneering the use of deep RL for autonomous planning in soft-tissue surgeries, as demonstrated in his highly cited 2023 paper on sim-to-real surgical robot learning for internal tissue points manipulation (35 citations). He has also advanced the integration of multi-modal large language models (LLMs) into surgical autonomy, enabling reasoning and decision-making for tasks like blood suction (17 citations). His research on realistic surgical simulators for non-rigid and contact-rich manipulation (9 citations) and hands collaboration evaluation using information theory (9 citations) has provided critical tools for surgical skills assessment and training. With over 100 total citations, Ou’s work bridges the gap between simulation and real-world surgical applications, emphasizing safety and efficiency through human supervision and demonstration. His achievements include developing autonomous irrigation-suction systems for the da Vinci Research Kit, showcasing his impact on next-generation surgical automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8Iterative Learning for Gravity Compensation in Impedance Control5 citations · 2024
- 9
- 10