Chun‐Fai Ng

University of Hong Kong

Papers

1

Total Citations

7

H-Index

1

About

Chun-Fai Ng is a researcher whose work sits at the critical intersection of computer graphics, robotics, and medical technology, with a particular focus on enabling real-time performance in safety-critical applications. His primary research areas include hardware-accelerated collision detection, field-programmable gate array (FPGA) architectures, and image-guided robotic surgery. Ng’s most notable contribution is his pioneering work on FPGA-based high-performance collision detection, a computationally intensive problem essential for determining the relative placement or configuration of multiple objects. His 2016 paper on this topic, which has garnered 7 citations, directly addresses a key bottleneck in image-guided robotic surgery: the need for instantaneous, reliable collision detection to ensure patient safety and procedural accuracy. By leveraging the parallel processing capabilities of FPGAs, Ng demonstrated a practical enabling technique for achieving the real-time responsiveness required in the operating room. This work is particularly significant for students and researchers in medical robotics, as it provides a hardware-oriented solution to a classic computational geometry problem, bridging the gap between theoretical algorithms and life-saving clinical applications.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
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: 7
🏛 Institutions: University of Hong Kong

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago