Menglong Ye
Papers
7
Total Citations
157
H-Index
6
About
Menglong Ye is a leading researcher at the intersection of robotic surgery, computer vision, and autonomous systems. His work focuses on developing intelligent frameworks that enhance the precision and autonomy of minimally invasive surgical robots. Ye’s major contributions include pioneering autonomous scanning for endomicroscopic mosaicing and 3D fusion, which enables real-time, large-area tissue imaging during robot-assisted procedures. He also developed a multirobot cooperation framework for sewing personalized stent grafts, integrating vision-guided learning-by-demonstration to automate complex manufacturing tasks. His work on multiscale image fusion bridges macro and micro imaging modalities, improving surgical guidance. With over 150 citations across his most-cited papers, Ye’s impact is evident in advancing context-aware surgical systems. Notable achievements include his self-supervised Siamese learning approach for depth estimation in robotic surgery and a multi-task vision transformer for automatic biopsy tool recognition. Ye’s research is instrumental in moving robotic surgery toward greater autonomy, precision, and integration of AI-driven decision support.
Research Focus
Key Achievements
Top Papers
- 1Autonomous scanning for endomicroscopic mosaicing and 3D fusion41 citations · 2017
- 2A Multirobot Cooperation Framework for Sewing Personalized Stent Grafts36 citations · 2017
- 3From Macro to Micro: Autonomous Multiscale Image Fusion for Robotic Surgery22 citations · 2017
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