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About

Marco Rospocher is a leading researcher at the intersection of natural language processing (NLP) and the surgical domain, with a primary focus on the automatic extraction of procedural knowledge from text. His work is pioneering the development of intelligent systems that can understand and formalize surgical instructions, a critical step toward building expert surgical assistants and autonomous robotic task planners. Rospocher’s major contributions include demonstrating the feasibility of automatically detecting procedural sentences in robotic-assisted surgical texts (16 citations), and developing the AUTOMATE pipeline, which maps natural language procedure descriptions to linear temporal logic templates for robotic planning (9 citations). He also created the Robotic-Surgery Proposition Bank, a foundational resource for semantic role labeling in this specialized domain (9 citations). By bridging computational linguistics and robotic surgery, Rospocher’s research is laying the essential groundwork for next-generation surgical AI, enabling machines to not only read but truly understand the step-by-step logic of complex medical interventions.