Papers

4

Total Citations

151

H-Index

4

About

May Liu is a leading researcher in the field of robotic surgery, with a focus on skill assessment, training, and simulation for the da Vinci Surgical System. Her work has been instrumental in defining core skill sets and developing validated metrics for evaluating technical performance in robot-assisted surgery. Liu’s 2015 review on training research and virtual reality simulators for the da Vinci system, cited 67 times, provides a comprehensive synthesis of the field, highlighting the need for standardized skill measurement. She developed the Assessment of Robotic Console Skills (ARCS) scale, a novel global rating tool with proven construct validity (33 citations), which has become a key resource for objectively assessing surgical proficiency. Her research also explores integrating task information into automated skill assessment using motion and video data (23 citations), advancing the use of simulation environments for training. Liu’s contributions are shaping how surgeons are trained and evaluated, with direct implications for patient safety and surgical education. Her work continues to drive innovation in robotic surgery training, making her a pivotal figure in this rapidly evolving discipline.

Research Focus

Key Achievements

4
H-Index
4
Papers
151
Total Citations
38
Avg Citations/Paper
🏆 Most Cited Paper
A Review of Training Research and Virtual Reality Simulators for the da Vinci Surgical System
67 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Intuitive Surgical (Switzerland), Intuitive Surgical (United States), Johns Hopkins University

Top Papers

  1. 1
  2. 2
  3. 3
    The da Vinci Surgical System
    28 citations · 2019
  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago