Yuhang Wen

Sun Yat-sen University, Wuhan University of Technology

Papers

Total Citations

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About

Yuhang Wen is a robotics researcher focused on advancing human-robot interaction, surgical robotics, and intelligent manipulation. His work bridges computer vision, force sensing, and world modeling to make robots more perceptive and autonomous. Wen’s most cited paper, “Interactive Spatiotemporal Token Attention Network for Skeleton-Based General Interactive Action Recognition” (2023, 29 citations), introduces a novel attention mechanism that outperforms late fusion and co-attention methods in recognizing multi-entity interactions—critical for collaborative robots. In surgical robotics, Wen developed an “Elliptical torus-based Six-axis FBG Force Sensor with In-situ Calibration” (2024), enabling real-time force feedback and drilling status monitoring for orthopedic surgery, reducing cognitive load on surgeons. His work “Surfer: Progressive Reasoning with World Models for Robotic Manipulation” (2023) tackles the challenge of translating fuzzy human instructions into physically consistent actions, integrating world knowledge for more reliable task execution. With contributions spanning interactive action recognition, sensor design, and reasoning for manipulation, Wen is shaping safer, more intuitive robotic systems for healthcare and industry.