Papers

19

Total Citations

879

H-Index

11

About

Dr. Tianliang Li is a leading researcher at the intersection of soft robotics, biomedical instrumentation, and intelligent sensing, whose work is fundamentally reshaping minimally invasive surgery (MIS) and human-machine interaction. His core contributions lie in developing bioinspired, fiber-optic-based tactile sensors and shape-sensing techniques for continuum robots. His landmark survey on shape sensing for continuum robots in MIS has garnered 403 citations, establishing a foundational reference for the field. Dr. Li’s innovative approach is exemplified by his development of a bioinspired analogous nerve (148 citations) and an AI-motivated skin-like optical fiber tactile sensor, which integrate distributed sensing with machine learning for high-fidelity force feedback. He has pioneered fault-tolerant, six-axis Fiber Bragg Grating (FBG) force/moment sensors for robotic interventions, including a notable design for orthopedic surgery robots with gravity self-compensation. His recent work on stretchable polymer-based sensors for AI-assisted disease monitoring and intelligent human-machine interfaces further demonstrates his versatility. By combining bioinspiration with robust engineering, Dr. Li’s highly cited research is enabling safer, more perceptive surgical robots and next-generation wearable technologies.

Research Focus

Key Achievements

11
H-Index
19
Papers
879
Total Citations
46
Avg Citations/Paper
🏆 Most Cited Paper
Shape Sensing Techniques for Continuum Robots in Minimally Invasive Surgery: A Survey
403 citations · 2016
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 66
🏛 Institutions: National University of Singapore, Wuhan University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago