Papers
43
Total Citations
1,210
H-Index
18
About
Giulio Dagnino is a prominent researcher at the intersection of medical robotics, minimally invasive surgery, and autonomous systems, whose work has collectively amassed over 800 citations and is reshaping how clinicians approach complex interventional procedures. His research spans endovascular robotics, image-guided surgery, and the application of artificial intelligence to clinical automation — areas where he has made particularly influential contributions. Dagnino's most celebrated work includes a landmark 2019 review on the frontiers of medical robotics (190 citations), which has become a foundational reference for the field, alongside a 2021 exploration of robotics in combating infectious diseases like COVID-19 (114 citations). His pioneering integration of deep reinforcement learning and generative adversarial imitation learning into endovascular catheterization (107 citations) demonstrates a forward-thinking approach to surgical autonomy. He has also advanced haptic feedback systems and MRI-safe robotic platforms for endovascular procedures, addressing critical safety and precision challenges in cardiovascular interventions. Earlier in his career, Dagnino made significant strides in image-guided robotic systems for fracture surgery, developing navigation tools that improve outcomes in complex joint repairs. His sustained output across both hardware innovation and intelligent control systems marks him as a uniquely versatile figure in surgical robotics research.
Research Focus
Key Achievements
Top Papers
- 1Frontiers of Medical Robotics: From Concept to Systems to Clinical Translation190 citations · 2019
- 2Progress in robotics for combating infectious diseases114 citations · 2021
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- 7Robot-assistive minimally invasive surgery: trends and future directions59 citations · 2024
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