Yikang Shen

Papers

Total Citations

173

H-Index

About

Dr. Yikang Shen is a pioneering researcher at the intersection of advanced materials science and artificial intelligence, with key contributions spanning covalent adaptable networks and diffusion-based robotic planning. In materials chemistry, Shen’s landmark 2021 work on "Covalent Adaptable Liquid Crystal Networks Enabled by Reversible Ring-Opening Cascades of Cyclic Disulfides" (171 citations) introduced a groundbreaking approach to creating self-healing, reprogrammable liquid crystal actuators. By integrating dynamic covalent bonds into liquid crystal networks, this research enables soft robotic devices that can autonomously repair damage and reversibly alter their shape—a critical advance for adaptive, durable soft robotics. On the AI frontier, Shen’s 2023 paper "Adaptive Online Replanning with Diffusion Models" (2 citations) tackles a fundamental challenge in data-driven planning: determining when and how to regenerate plans in dynamic environments. This work bridges generative modeling and real-time decision-making, offering novel frameworks for robotic control and reinforcement learning. Shen’s dual expertise in synthetic chemistry and machine learning exemplifies a rare interdisciplinary talent, pushing boundaries in both self-healing materials and intelligent autonomous systems.