Yong Won Seo

University at Buffalo, State University of New York

Papers

Total Citations

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About

Yong Won Seo is a researcher whose work lies at the critical intersection of surgical robotics, health economics, and haptic feedback systems. His most impactful contribution is a landmark 2013 study on simulation-based robot-assisted surgical training, which conducted a rigorous health economic evaluation of the Robotic Surgical Simulator (RoSS). This highly cited paper (54 citations) demonstrated the cost-effectiveness of structured simulation training, providing a foundational economic argument for integrating virtual reality into surgical curricula. Beyond economics, Seo has advanced the safety and precision of tele-surgery through his work on predictive modeling. He developed a novel Prediction from Expert Demonstration (PED) methodology, which encodes force, torque, and penetration trajectories from expert clinicians to provide intelligent haptic assistance during critical procedures like trocar insertion. This work aims to reduce the risk of tissue damage by guiding surgeons with learned haptic cues. By blending economic analysis with cutting-edge haptic and predictive algorithms, Seo’s research directly addresses two of the most pressing challenges in modern surgery: cost containment and the enhancement of intraoperative safety.