Nancy Hong

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About

Nancy Hong is a pioneering researcher in autonomous robotic surgery, with a focus on leveraging robotic parallelism and enhancing surgical skill assessment. Her key research areas include multi-task automation in robot-assisted surgery (RAS) and video-based performance evaluation. In her highly cited 2021 paper, "Parallelism in Autonomous Robotic Surgery" (14 citations), Hong demonstrated how robots can execute multiple surgical subtasks concurrently, developing execution models that significantly improve efficiency in simulated multilateral procedures—a foundational contribution to autonomous surgical workflows. Her 2022 work, "Orientation Matters: 6-DoF Autonomous Camera Movement for Video-based Skill Assessment in Robot-Assisted Surgery" (3 citations), addresses a critical limitation in RAS training by introducing autonomous camera control to optimize video perspectives for more accurate skill evaluation. This innovation enhances the reliability of assessment questionnaires used by expert reviewers. Hong’s research bridges robotics and surgical education, offering practical solutions for both automation and training. Her work is increasingly influential, shaping how surgeons and engineers approach the next generation of intelligent, adaptive surgical systems.