Hailin Li

Communication University of China, Yanshan University

Papers

Total Citations

H-Index

About

Hailin Li is a researcher advancing the frontiers of soft robotics and surgical AI. His work bridges two critical domains: enhancing robotic dexterity in medical procedures and developing untethered, high-load soft gripping systems. In his 2020 paper on symmetric dilated convolution for surgical gesture recognition (31 citations), Li introduced a novel deep learning architecture that significantly improves the accuracy of recognizing complex surgical maneuvers, a key step toward autonomous robotic surgery. Complementing this, his comprehensive review of untethered, high-load soft gripping robots (3 citations) tackles a fundamental challenge in soft robotics: the trade-off between mobility and payload capacity. Li systematically analyzes innovations in untethered actuation and system integration, highlighting how soft grippers can now achieve remarkable load-bearing capabilities without being tethered to external power sources. This work is pivotal for expanding soft robots into real-world applications like underwater exploration and aerial manipulation. By combining computational methods with mechanical design, Li is shaping a future where robots are both intelligent and physically autonomous.