Giacomo De Rossi
Papers
20
Total Citations
355
H-Index
10
About
Giacomo De Rossi is a prominent robotics researcher whose work sits at the intersection of surgical robotics, autonomous systems, and human-robot interaction. Over more than two decades, he has made significant contributions to the design and intelligence of medical robotic systems, with a particular focus on minimally invasive surgery (MIS). His 2018 study on soft robotic manipulators for MIS (63 citations) demonstrated how compliant, flexible mechanisms could extend surgical dexterity while preserving the patient benefits of minimally invasive approaches. Alongside hardware innovation, De Rossi has pioneered cognitive architectures that enable robots to autonomously execute surgical tasks — a research thread running from his 2015 work on cognitive robotic systems (53 citations) through increasingly sophisticated semi-autonomous frameworks published in 2016, 2019, and 2021. His earlier theoretical contributions on polytope-based kinetostatic analysis (44 citations, 2002) reflect a strong foundation in robot mechanics. More recently, he has explored multi-modal machine learning and model predictive control for real-time motion planning in surgical environments. De Rossi also demonstrates a commitment to education, having developed curriculum innovations for teaching physical human-robot interaction to undergraduate students. His body of work, accumulating over 300 citations, continues to shape the trajectory of intelligent surgical robotics.
Research Focus
Key Achievements
Top Papers
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- 2Development of a Cognitive Robotic System for Simple Surgical Tasks53 citations · 2015
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- 7Dynamic Motion Planning for Autonomous Assistive Surgical Robots25 citations · 2019
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