Kaiwen Xiao

Papers

Total Citations

H-Index

About

Kaiwen Xiao is a rising researcher in robot-assisted surgery, with a focus on advancing the analysis and assessment of surgical skill. His work critically examines the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a foundational dataset in the field, to uncover its limitations and implications for developing robust, generalizable models. By exploring how kinematic and video data can classify operator skill levels, Xiao contributes to the broader goal of improving surgical training and patient outcomes through automated feedback. His 2024 paper, "Exploring the Limitations and Implications of the JIGSAWS Dataset for Robot-Assisted Surgery," has already garnered 4 citations, signaling its early impact in a rapidly evolving domain. This work underscores his commitment to refining the tools and methodologies that underpin modern surgical robotics, addressing critical gaps in dataset reliability and model transferability. As a researcher, Xiao is positioned at the intersection of machine learning, robotics, and healthcare, driving innovations that promise to make robot-assisted surgery safer and more effective. His contributions are particularly valuable for students and researchers seeking to understand the challenges and opportunities in surgical skill assessment.