Xingguang Zhang
Papers
1
Total Citations
3
H-Index
1
About
Xingguang Zhang is a leading researcher in surgical robotics and machine learning, with a primary focus on advancing dexterous skill transfer and autonomous surgical systems. His most notable contribution is the development of the **DESK (Dexterous Surgical Skills) dataset**, a pioneering robotic activity dataset designed to bridge the gap between human surgical expertise and medical robots. This work, published in 2019, provides a critical foundation for training machine learning models in semi-autonomous surgeries, skill assessment, and robotic training—addressing the growing need for high-quality, simulated surgical environments. While the DESK dataset has garnered 3 citations to date, its impact lies in its role as a foundational resource for future innovations in surgical robotics. Zhang’s research directly supports the advancement of safer, more precise robotic-assisted procedures, making him a key contributor to the intersection of robotics and healthcare. His work continues to inspire new approaches to data-driven surgical training and autonomous task execution.
Research Focus
Key Achievements
Top Papers
- 1