Yuhang Ye

University of British Columbia, South China University of Technology

Papers

Total Citations

H-Index

About

Yuhang Ye’s research sits at the intersection of soft robotics, human-machine interfaces, and advanced materials, with a focus on creating resilient, intelligent systems for rehabilitation and sensing. His most cited work, “Ultra‐Stretchable and Environmentally Resilient Hydrogels Via Sugaring‐Out Strategy for Soft Robotics Sensing” (2024, 66 citations), introduces a novel approach to overcoming the mechanical and environmental limitations of hydrogels. By modulating water states and intermolecular interactions, Ye’s “sugaring-out” strategy yields hydrogels that are both ultra-stretchable and durable—key for next-generation soft robotic sensors that must function reliably in diverse conditions. This work has quickly garnered attention for its practical, scalable solution to a long-standing materials challenge. Earlier, Ye contributed to the field of rehabilitation robotics with “Optimal Feature Selection for EMG-Based Finger Force Estimation Using LightGBM Model” (2019, 32 citations), demonstrating how machine learning can extract precise force predictions from electromyogram signals. This work advanced human-robot interfaces by optimizing feature selection, making prosthetic and assistive devices more responsive. With over 98 citations across his top papers, Ye’s research is shaping the future of soft, adaptive robotics and intelligent rehabilitation technologies.