Ryan Tsang
Papers
1
Total Citations
17
H-Index
1
About
Ryan Tsang is a researcher at the intersection of surgical education and human–machine interaction, with a primary focus on improving technical skill acquisition through real-time, data-driven feedback. His most cited work, "Using Real-time Feedback To Improve Surgical Performance on a Robotic Tissue Dissection Task" (2022, 17 citations), addresses a critical gap in surgical training: the lack of standardized feedback from attending surgeons. By designing and administering structured, real-time feedback to a cohort of 45 medical students performing robotic tissue dissection, Tsang demonstrated that objective performance metrics can significantly enhance learning outcomes compared to traditional, variable instruction. This contribution has implications for reducing variability in surgical teaching and accelerating competency in robotic surgery. Though early in his career, Tsang’s work is already shaping how educators think about feedback loops in high-stakes environments, bridging the gap between subjective mentorship and quantifiable skill development. His research is particularly relevant for trainees and educators in minimally invasive and robotic-assisted surgery.
Research Focus
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Top Papers
- 1