Marco Bombieri

About

Marco Bombieri is a leading researcher at the intersection of natural language processing, robotics, and surgical data science. His work focuses on enabling autonomous robotic surgical systems by bridging the gap between human-readable procedural knowledge and machine-executable logic. Bombieri’s major contributions include developing methods to automatically extract procedural knowledge from surgical texts, such as his 2021 paper on detecting procedural sentences (16 citations), and creating the AUTOMATE pipeline to map natural language instructions into linear temporal logic templates (9 citations). He also introduced the Robotic-Surgery Proposition Bank (9 citations), a structured linguistic resource for surgical interventions. In the domain of surgical gesture analysis, Bombieri proposed joints-space metrics for automatic classification of robotic surgical gestures (6 citations), advancing objective skill assessment. His opinion piece on the need for common sense in autonomous surgical systems (6 citations) highlights his forward-looking perspective on achieving higher levels of robotic autonomy. With a growing citation record and a clear focus on practical, knowledge-driven automation, Bombieri is shaping the future of intelligent surgical assistance.

Research Focus

Key Achievements

Top Papers

1. 1
   Automatic detection of procedural knowledge in robotic-assisted surgical texts

   16 citations · 2021
2. 2
   Mapping natural language procedures descriptions to linear temporal logic templates: an application in the surgical robotic domain

   9 citations · 2023
3. 3
   The robotic-surgery propositional bank

   9 citations · 2023
4. 4
   Joints-Space Metrics for Automatic Robotic Surgical Gestures Classification

   6 citations · 2020
5. 5
   Autonomous Robotic Surgical Systems: Needing Common Sense to Achieve Higher Levels of Autonomy [Opinion]

   6 citations · 2023

Key Collaborators

Contact & Links