Max Robotics — Global Service Robot Directory + US Certification

About

Yuriko Harai is a leading researcher in surgical data science, with a primary focus on computer-assisted interventions and workflow recognition in robot-assisted surgery. Her work centers on developing and validating machine learning methods for surgical action recognition and tool segmentation—critical components for advancing skills assessment and intraoperative decision support. Harai has been instrumental in organizing and contributing to major surgical challenge benchmarks, including the PEg TRAnsfer Workflow Recognition Challenge and the SAR-RARP50 challenge, which evaluate how multi-modal data—such as video, kinematics, and system logs—can improve recognition accuracy. Her most-cited papers, including the 2022 and 2023 PEg TRAnsfer reports (12 and 5 citations, respectively) and the SAR-RARP50 study (11 citations), demonstrate her role in establishing standardized evaluation frameworks for surgical AI. Through these challenges, Harai has helped drive the field toward more robust, generalizable models that integrate diverse data streams, directly impacting the development of next-generation robotic surgical systems.