About

Michael Yu Wang is a pioneering researcher at the intersection of soft robotics, computational design, and human-machine interaction, whose work has fundamentally advanced how robots are designed, controlled, and deployed in real-world settings. His most significant contributions center on topology optimization for soft robotic systems — developing systematic frameworks that automatically synthesize and fabricate soft grippers and multimaterial fingers with superior performance, work that has each garnered over 130 citations. Wang has been equally influential in variable stiffness technologies, pioneering hybrid jamming and electrostatic layer jamming mechanisms that enable soft robots to dynamically modulate their rigidity, accumulating nearly 300 combined citations across related publications. His 2020 state-of-the-art review on soft robot design optimization, with 153 citations, has become an essential reference for the field. Beyond mechanical design, Wang has expanded into tactile sensing — developing vision-based sensors like FingerVision and DelTact — and multimodal human-machine interfaces that integrate EEG, EMG, and EOG signals to control soft robotic hands for rehabilitation applications. His work on agricultural robotics, including a robust soft gripper for apple harvesting, further demonstrates the remarkable breadth and real-world impact of his research program.

Research Focus

Key Achievements

26
H-Index
81
Papers
2,396
Total Citations
30
Avg Citations/Paper
🏆 Most Cited Paper
Design Optimization of Soft Robots: A Review of the State of the Art
153 citations · 2020
📈 Most Prolific Year: 2022 (12 Papers)
🤝 Key Collaborators: 161
🏛 Institutions: Hong Kong University of Science and Technology, Monash University, National University of Singapore, Applied Science and Technology Research Institute, HKUST Shenzhen Research Institute, Chinese University of Hong Kong

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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