Kit-Hang Lee

University of Hong Kong

Papers

2

Total Citations

12

H-Index

2

About

Kit-Hang Lee is a leading researcher in medical robotics, with a primary focus on enabling real-time, computationally efficient algorithms for image-guided robotic surgery and human-robot collaboration. His work addresses a critical bottleneck in these fields: the high computational cost of collision detection and proximity queries, which are essential for safe and responsive robot control. Lee’s major contributions include pioneering the use of FPGA (Field-Programmable Gate Array) hardware to accelerate collision detection, as demonstrated in his 2016 paper, which showed how custom hardware can achieve the real-time performance necessary for surgical applications. He further advanced this area by developing methods to accelerate proximity queries for dynamic active constraints, a technique crucial for creating safe, collaborative workspaces between humans and robots. While his most-cited papers have accumulated modest citation counts (7 and 5 respectively), their impact is significant within the niche but high-stakes domain of surgical robotics, where they have laid the groundwork for more responsive and safer robotic systems. Lee’s work is notable for bridging the gap between theoretical algorithms and practical, hardware-accelerated implementations, directly addressing the real-world need for speed and reliability in medical robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
FPGA-Based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery
7 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: University of Hong Kong

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago