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
Top Papers
- 1
- 2A bioinspired analogous nerve towards artificial intelligence148 citations · 2020
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- 5An Artificial Intelligence‐Motivated Skin‐Like Optical Fiber Tactile Sensor48 citations · 2023
- 6Fault-Tolerant Six-Axis FBG Force/Moment Sensing for Robotic Interventions29 citations · 2023
- 7AI-Assisted Disease Monitoring Using Stretchable Polymer-Based Sensors28 citations · 2023
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