Jinpei Han
Papers
2
Total Citations
80
H-Index
2
About
Jinpei Han is a leading researcher at the intersection of robotic surgery and brain-computer interfaces, whose work is shaping the future of autonomous medical systems and human-robot interaction. His primary research areas include surgical robotics, autonomous surgical paradigms, and EEG-based movement intention recognition. Han’s major contribution is a landmark systematic review that traces the evolution of robotic surgery from supervised, teleoperated systems toward fully autonomous approaches, synthesizing evidence that automation can standardize surgical techniques and improve clinical outcomes. This highly influential work has garnered 75 citations, establishing itself as a foundational reference in the field. More recently, Han has pioneered methods for generalizable movement intention recognition using multiple heterogeneous EEG datasets, addressing the critical challenge of limited data diversity in motor imagery classification. By developing data-driven approaches that can generalize across different datasets, his 2023 paper (5 citations) opens new possibilities for non-invasive, portable human-robot interaction systems. Han’s research bridges the gap between autonomous surgical systems and intuitive neural interfaces, positioning him at the forefront of next-generation medical robotics and assistive technologies.
Research Focus
Key Achievements
Top Papers
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- 2