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About

Xiaowei Shan is a robotics researcher whose work centers on soft robotics, with a particular focus on the design, modeling, and analysis of soft robotic fingers and grippers. His research addresses one of the field's most persistent challenges: enabling robots to reliably grasp and manipulate objects in unstructured, real-world environments through compliant, adaptive mechanisms. Shan's most influential contribution is his 2020 paper on modeling soft robotic fingers using the fin ray effect, which has accumulated 107 citations and represents a significant advance in the accurate mechanical modeling of soft fingers — a problem that had long resisted rigorous analytical treatment. This work laid a strong foundation for subsequent research in adaptive grasping. Building on this, his 2023 study introduced a practical comparison of bistable stopper designs for precision and power grasps in industrial manipulation, bridging the gap between academic soft robotics research and real-world industrial deployment. His 2024 work on variable stiffness design further extends this trajectory, proposing novel methods for stiffness compensation and linearization to enhance gripper versatility. Collectively, Shan's research makes meaningful contributions to making soft robotic grippers more predictable, controllable, and industrially viable — a vital step toward broader adoption of soft robotics in manufacturing and automation.