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About

Yun‐Kyu An is a leading researcher in structural health monitoring and robotic inspection for civil infrastructure. His work centers on integrating robotics, computer vision, and deep learning to automate crack detection and lifecycle management of bridges and large-scale structures. An’s most influential contribution is the development of a ring-type climbing robot for automated crack evaluation on high-rise bridge piers, a paper that has garnered 137 citations. He further advanced the field by proposing SrcNet, a deep super-resolution crack network that significantly improves computer vision–based crack detectability in real-world bridges, even under challenging conditions like motion blur from unmanned robots. This work, with 93 citations, has become a key reference for enhancing the reliability of automated inspections. An also contributed to the Infrastructure BIM Platform for Lifecycle Management, addressing the growing need for efficient infrastructure management systems from design through operation. His recent achievement includes RAIBO2, a highly efficient quadruped robot that completed a full marathon on a single battery charge, showcasing his innovative approach to robotic endurance and practical field deployment. Through these contributions, An has demonstrated a sustained impact on making infrastructure inspection safer, faster, and more accurate.