Papers
12
Total Citations
777
H-Index
6
About
Wan Shou is a versatile researcher whose work spans soft robotics, wearable sensing, smart materials, and human-robot interaction. His most celebrated contribution, "Learning Human–Environment Interactions Using Conformal Tactile Textiles" (2021, 375 citations), pioneered the integration of textile-based tactile sensors with machine learning to decode complex physical interactions — a landmark advance in wearable intelligence. Building on this foundation, Shou has developed cutting-edge flexible hydrogel sensors capable of operating under extreme conditions, including sub-zero temperatures and underwater environments, with his cold-resistant ionic hydrogel work (2023, 138 citations) demonstrating impressive strain sensitivity and durability for winter sports motion recognition. His self-powered sensing systems (2022, 114 citations) further highlight his commitment to autonomous, energy-efficient wearable technologies. Beyond sensing, Shou has made notable strides in computational materials design, using AI-driven methods to discover microstructured composites with optimal stiffness-toughness trade-offs. His more recent explorations into continuum robotics, opto-mechanical actuators, and tactile representation learning underscore a broadening research vision. With over 770 cumulative citations, Wan Shou represents an emerging leader bridging materials science, robotics, and intelligent systems.
Research Focus
Key Achievements
Top Papers
- 1Learning human–environment interactions using conformal tactile textiles375 citations · 2021
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- 3Self-powered sensing systems with learning capability114 citations · 2022
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- 6Dynamic Modeling of Hand-Object Interactions via Tactile Sensing19 citations · 2021
- 7Feedback regulated opto-mechanical soft robotic actuators5 citations · 2025
- 8Desktop-scale robot tape manipulation for additive manufacturing4 citations · 2024
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