About

Elena De Momi is a leading researcher at the intersection of surgical robotics, human-robot collaboration, and artificial intelligence, whose work has fundamentally advanced the field of robot-assisted minimally invasive surgery. Her research addresses some of the most pressing challenges in surgical automation, including haptic feedback integration, autonomous robotic behavior, and intelligent control frameworks — areas where her 2016 paper on haptics in robot-assisted surgery (246 citations) and her influential 2020 review on surgical autonomy (235 citations) have become essential references for the community. De Momi's contributions span both theoretical and applied dimensions. She has pioneered teleoperation control schemes for redundant surgical robots, developed deep neural network approaches for tool dynamics identification, and advanced teaching-by-demonstration methodologies that enable robots to acquire surgical skills from human experts. Her work on recurrent neural networks for manipulator control and incremental learning for anthropomorphic manipulators reflects a sustained commitment to making surgical robots more intelligent and adaptable. Beyond soft robotics and control, De Momi has made notable contributions to image-guided neurosurgery and capsule endoscope navigation. With multiple papers exceeding 100 citations and a body of work spanning computer vision, machine learning, and clinical validation, she represents a formative voice shaping the future of safe, autonomous, and collaborative surgical systems.

Research Focus

Key Achievements

40
H-Index
201
Papers
5,579
Total Citations
28
Avg Citations/Paper
🏆 Most Cited Paper
Haptics in Robot-Assisted Surgery: Challenges and Benefits
246 citations · 2016
📈 Most Prolific Year: 2022 (28 Papers)
🤝 Key Collaborators: 439
🏛 Institutions: Politecnico di Milano, University of Leeds, University of Science and Technology of China, University of Verona, Bioengineering Technology and Systems (Italy), European Institute of Oncology

Top Papers

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    Autonomy in Surgical Robotics
    235 citations · 2020
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Key Collaborators

Contact & Links

Available for collaboration
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