Mattia Ballo
Papers
4
Total Citations
12
H-Index
3
About
Mattia Ballo is a rising leader at the intersection of robotic surgery, computer vision, and surgical education. His research focuses on developing artificial intelligence and deep learning systems to automate the analysis of surgical performance, aiming to standardize training and improve patient outcomes. Ballo’s most cited work, “Monocular 3D Tooltip Tracking in Robotic Surgery,” addresses the critical challenge of accurately tracking surgical instruments from single-camera video, a foundational step for automated feedback and enhanced safety in robotic-assisted procedures. He further advances the field by creating AI models that automatically assess trainee proficiency in robotic suturing, as demonstrated in his work on dry-lab simulation. Ballo’s contributions extend to predicting postoperative outcomes from intraoperative video, as seen in his study on sleeve gastrectomy, where he explores how visual cues correlate with surgical success. With a growing body of work accumulating over a dozen citations in 2025 alone, Ballo is establishing himself as a key innovator in using computer vision to transform surgical training and practice.
Research Focus
Key Achievements
Top Papers
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