Papers
10
Total Citations
264
H-Index
8
About
Hee Chan Kim is a pioneering researcher in robotic surgery and medical robotics, with a primary focus on enhancing surgical safety and precision through advanced computer vision and augmented reality technologies. His major contributions include developing deep learning-based systems for automated surgical skill evaluation during robotic procedures, achieving 102 citations for his work on multi-instrument tracking that enables objective assessment of surgeon proficiency. Kim has made significant advances in vision-based tracking systems for augmented reality, particularly in localizing the recurrent laryngeal nerve during robotic thyroid surgery, a technique that has garnered 30 citations and demonstrates potential for reducing surgical complications. His research portfolio encompasses innovative solutions for surgical instrument tracking, haptic feedback systems, and force prediction models for the da Vinci surgical system. With notable work on developing a robot-assisted automatic laser hair removal system and Kalman-filter-based object detection for laparoscopic surgery, Kim has demonstrated versatility across multiple surgical applications. His cumulative citation impact exceeds 260 citations, reflecting the practical significance of his work in addressing critical challenges in robotic surgery, including limited operative views and lack of tactile feedback that particularly affect novice surgeons.
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