Papers
12
Total Citations
632
H-Index
12
About
Ge Fang is a pioneering robotics researcher whose work sits at the compelling intersection of medical robotics, soft robotics, and MRI-guided intervention. His research focuses on developing intelligent robotic systems for minimally invasive surgical procedures, with particular emphasis on designing MRI-compatible platforms and advancing control strategies for soft and continuum robots. Among his most influential contributions is the development of a soft robotic manipulator for intraoperative MRI-guided transoral laser microsurgery (144 citations), which demonstrated how compliant robotic systems can be seamlessly integrated into high-stakes clinical environments. His pioneering work on vision-based online learning kinematic control using local Gaussian process regression (115 citations) has significantly advanced the precision of soft robot motion control, bridging the longstanding gap between compliance and accuracy. Fang has also made substantial contributions to MRI-guided cardiac catheterization, needle-based percutaneous interventions, and focused ultrasound navigation, collectively demonstrating his breadth across multiple therapeutic domains. His fusion of visual and strain-based sensing for continuum robot control reflects a sophisticated, multi-modal approach to surgical robotics. With over 596 cumulative citations across his top works, Fang's research is shaping the future of autonomous, image-guided robotic surgery, offering transformative potential for safer and more precise clinical outcomes.
Research Focus
Key Achievements
Top Papers
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- 7Task Autonomy of a Flexible Endoscopic System for Laser-Assisted Surgery34 citations · 2022
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- 9A Robotic Platform to Navigate MRI-guided Focused Ultrasound System27 citations · 2021
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