Serena Roin
Papers
2
Total Citations
33
H-Index
2
About
Serena Roin is a leading researcher at the intersection of robotics, machine learning, and minimally invasive surgery. Her work focuses on endowing surgical assistant robots with a crucial capability: the ability to understand and anticipate a surgeon’s actions in real time. Roin’s primary contribution lies in developing multi-modal learning systems that fuse video data with kinematic information to perform on-line surgical action segmentation. This foundational technology is the key building block for introducing safe, cooperative autonomy into the operating room, allowing robots to assist with precision tasks and reduce physical strain on surgeons. Her most cited work, “A First Evaluation of a Multi-Modal Learning System to Control Surgical Assistant Robots via Action Segmentation” (2021), has garnered 29 citations for its pioneering approach to deterministic, high-safety human-robot collaboration. By enabling robots to “see” and “understand” the current phase of a procedure, Roin’s research is paving the way for a new generation of intelligent surgical assistants that can work seamlessly alongside human experts.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Multi-Modal Learning System for On-Line Surgical Action Segmentation4 citations · 2020