Papers
23
Total Citations
477
H-Index
11
About
Xiaoliang Jin is a leading researcher in medical robotics, with a specialized focus on robot-assisted vascular interventional surgery (VIS). His work addresses one of the most pressing challenges in modern minimally invasive medicine: protecting surgeons from prolonged X-ray radiation exposure while maintaining the precision and safety required during complex endovascular procedures. Jin's most significant contributions center on developing intelligent robotic systems that integrate tactile sensing, haptic force feedback, and real-time safety mechanisms to replicate and enhance a surgeon's natural dexterity. His 2021 paper on tactile sensing robot-assisted systems has garnered 83 citations, while his force-visual feedback surgical platform (2019, 60 citations) and operational safety framework (2018, 59 citations) have become foundational references in the field. Collectively, his top publications have accumulated over 400 citations, reflecting substantial influence across surgical robotics and biomedical engineering communities. Beyond hardware development, Jin has contributed meaningfully to human-robot interaction design, collision protection algorithms, magnetically controlled haptic interfaces, and virtual reality training systems for interventional procedures. His body of work represents a comprehensive engineering approach to making vascular surgery safer, more precise, and more accessible — offering clear translational value for clinical adoption of next-generation surgical robotics.
Research Focus
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Top Papers
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- 10A Two-channel Haptic Force Interface for Endovascular Robotic Systems13 citations · 2020