Sing Chun Lee
Papers
3
Total Citations
166
H-Index
3
About
Sing Chun Lee is a pioneering researcher in medical robotics and computer-assisted intervention, whose work bridges the critical gap between planning, imaging, and real-time action. His most influential contribution, the "Dual-robot ultrasound-guided needle placement" system (64 citations), introduced a groundbreaking closed-loop framework that integrates robotic precision with live ultrasound feedback, dramatically improving the accuracy of percutaneous procedures. Lee further advanced the field by enabling machine learning for X-ray-based interventions through realistic simulation of image formation (61 citations), a methodology that allows deep learning models to be trained on synthetic data without the need for costly, radiation-exposed clinical datasets. Earlier in his career, he demonstrated his versatility in autonomous systems with a stereo-based obstacle avoidance system for mobile robots (41 citations), featuring an innovative active sensor re-calibration technique. This work showcased his ability to solve complex perception problems in dynamic environments. Lee’s research is characterized by its translational impact—taking fundamental robotics and computer vision principles and applying them to solve tangible, high-stakes problems in medicine, from needle guidance to intraoperative imaging.
Research Focus
Key Achievements
Top Papers
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