Leonardo Borgioli

Papers

Total Citations

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About

Leonardo Borgioli is a pioneering researcher at the intersection of robotic surgery and machine learning, with a primary focus on automating minimally invasive surgical procedures. His most impactful work centers on cholecystectomy—the surgical removal of the gallbladder—where he has made significant contributions to both data infrastructure and surgical automation. Borgioli led the creation of the Comprehensive Robotic Cholecystectomy Dataset (CRCD), a novel resource integrating kinematics, pedal signals, and endoscopic videos from ex vivo porcine procedures. This dataset, already cited 6 times, provides a critical foundation for developing data-driven tools in robotic surgery. He also proposed a framework for automated dissection along tissue boundaries, aiming to enhance surgical precision, reduce surgeon stress, and lower healthcare costs. Additionally, Borgioli has explored novel human-robot interfaces, designing a sensory glove-based control system to replace bulky proprietary consoles, improving OR ergonomics and team coordination. His work, accumulating citations rapidly, positions him as a key contributor to the next generation of intelligent, accessible, and autonomous surgical systems.