Max Panoff
Papers
1
Total Citations
4
H-Index
1
About
Max Panoff is a rising researcher in the field of robot-assisted surgery, with a focus on the intersection of machine learning and surgical skill assessment. His work critically examines the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a foundational dataset for analyzing surgical performance. In his highly cited 2024 paper, Panoff explores the limitations and implications of JIGSAWS, highlighting how kinematic and video data can classify operators into distinct skill levels while cautioning against over-reliance on this benchmark. This contribution has already garnered 4 citations, signaling its growing impact in the community. By identifying dataset constraints, Panoff helps shape more robust methodologies for evaluating surgical proficiency, a key step toward safer, data-driven training tools. His research bridges engineering and clinical practice, offering insights that could improve how surgeons are trained and assessed. As an emerging voice in surgical robotics, Panoff’s work is paving the way for more reliable and generalizable skill analysis systems, making him a researcher to watch in this rapidly evolving domain.
Research Focus
Key Achievements
Top Papers
- 1