Papers
9
Total Citations
134
H-Index
6
About
Pankaj Singhal is a researcher whose work bridges surgical robotics, computer-assisted surgery, and clinical outcomes, with particular focus on robotic minimally invasive surgery (rMIS) and its applications in gynecology. His research spans two interconnected domains: the clinical evaluation of robotic surgical outcomes and the development of computational tools to assess and enhance surgical performance. Among his most significant contributions is his investigation of robotic-assisted gynecologic surgery in high-risk populations. His 2014 study on morbidly obese patients (39 citations) demonstrated that robotic surgery offers comparable outcomes regardless of obesity, providing important guidance for surgical decision-making. Complementing this clinical work, Singhal has pioneered quantitative, video-analysis-based frameworks for evaluating surgical skill, recognizing the limitations of subjective assessment methods. His 2012 paper on automated motion-based skill assessment (35 citations) helped establish reproducible performance metrics for robotic surgeons. Singhal has also advanced computer-vision-driven decision support systems to improve safety in robotic laparoscopic procedures, addressing sensor limitations and planning deficiencies that contribute to procedural failures. His 2015 work in this area (19 citations) reflects a forward-looking integration of artificial intelligence with surgical practice. Collectively, his research has meaningfully shaped how surgical competency is measured and how robotic surgery can be made safer and more accessible.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Computer-Vision-Based Decision Support in Surgical Robotics19 citations · 2015
- 4
- 5
- 6
- 7Surgical Performance Assessment6 citations · 2015
- 8
- 9