Papers

7

Total Citations

315

H-Index

4

About

Dr. Bingbin Yu is a pioneering researcher at the intersection of surgical robotics, continuum manipulators, and intelligent automation. Her work fundamentally advances how robots interact with delicate, unstructured environments—from the human body to industrial workspaces. Dr. Yu’s landmark survey, “Surgical robotics beyond enhanced dexterity instrumentation” (238 citations), is a seminal contribution that mapped the integration of machine learning into autonomous surgical actions, establishing a roadmap for the field. She has made critical strides in modeling and controlling continuum robots, including a probabilistic kinematic model for robotic catheters (30 citations) and reinforcement learning approaches for autonomous catheter navigation. In parallel, her research on series-elastic actuators (SEAs) for industrial robots (29 citations) addresses the pressing need for safe human-robot collaboration, combining data-driven modeling with novel mechanical design. Dr. Yu’s work on soft-rigid arm collaboration and portable continuum manipulators further showcases her ability to bridge theoretical modeling with practical, dexterous systems. With a career defined by translating complex nonlinear dynamics into controllable, intelligent robotic systems, Dr. Yu is shaping the future of both minimally invasive surgery and collaborative industrial robotics.

Research Focus

Key Achievements

4
H-Index
7
Papers
315
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions
238 citations · 2015
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: University of Bremen, German Research Centre for Artificial Intelligence

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago