Ruizhe Chang

University of Science and Technology of China

Papers

Total Citations

H-Index

About

Ruizhe Chang is a pioneering researcher in soft robotics and intelligent prosthetic systems, with a focus on shape memory alloy (SMA) artificial muscles and liquid metal-based sensing technologies. His work addresses critical challenges in robotic manipulation and assistive devices, particularly the trade-offs between load capacity, response speed, and precision. In his highly cited 2022 paper (35 citations), Chang introduced a novel approach to equipping SMA artificial muscles with controllable magnetorheological fluid (MRF) exoskeletons, significantly enhancing load-holding ability and reducing cooling time—a breakthrough for robotic grippers and manipulators. More recently, his 2024 study (10 citations) developed a liquid metal composites-based real-time hand gesture recognizer, achieving superior recognition speed and accuracy for prosthetic hand control. This innovation promises to restore natural, intuitive functionality for individuals with hand loss or deformity. Chang’s work bridges materials science and robotics, offering practical solutions for soft actuators and human-machine interfaces. His contributions are shaping the future of adaptive, responsive robotic systems and next-generation prosthetics, with growing impact in both academic and applied engineering contexts.