Junling Fu
Papers
13
Total Citations
245
H-Index
9
About
Junling Fu is an accomplished robotics researcher whose work sits at the intersection of medical robotics, human-robot interaction, and intelligent control systems. With a focus on advancing automation in clinical and surgical environments, Fu has made significant contributions across several interconnected domains, including model predictive control, augmented reality-assisted robotics, variable impedance control, and bionic hand teleoperation. Fu's most cited work, "Nonlinear Model Predictive Control for Mobile Medical Robot Using Neural Optimization" (2020, 66 citations), demonstrated how neural optimization techniques could be leveraged to enable more adaptive and intelligent mobile medical robots. This was complemented by a highly regarded survey on augmented reality in robotics (2023, 50 citations), which has become a key reference for researchers integrating AR into medical and industrial systems. His work on optimization-based variable impedance control (2024, 32 citations) further highlights his expertise in designing nuanced, safety-conscious controllers for contact-rich medical tasks. Spanning prosthetics, minimally invasive surgery, neurosurgery automation, and shared control frameworks, Fu's research consistently bridges theoretical rigor with real-world clinical relevance. With over 230 cumulative citations across his publications, his body of work reflects a meaningful and growing influence on the future of intelligent medical robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Recent Advancements in Augmented Reality for Robotic Applications: A Survey50 citations · 2023
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