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About

Yu Dai is a prominent researcher specializing in robotic surgical systems, intelligent sensing, and autonomous control for medical robotics, with a particular focus on robot-assisted bone milling and minimally invasive surgery. His work addresses one of the most critical challenges in spinal and orthopedic surgery: enhancing safety and precision during high-risk hard tissue removal procedures. Dai's most influential contributions center on developing vibration-based monitoring and control systems for robotic milling operations. His foundational work on milling state identification and condition monitoring (accumulating over 60 and 49 citations respectively) established robust signal processing frameworks using bone vibration analysis to detect tissue states in real time during spine surgery. He has progressively advanced these methods to incorporate wavelet analysis, dynamic milling models, sound pressure signals, and multi-sensor fusion techniques for estimating vertebral lamina thickness — directly mitigating the risk of spinal cord injury. Beyond vibration sensing, Dai has pioneered human-inspired haptic perception approaches that emulate experienced surgeons' tactile judgment, as well as FBG-based force measurement instruments for minimally invasive robotics. His research portfolio, spanning over a decade with more than 260 cumulative citations, reflects sustained, impactful contributions to the intersection of robotics, biomechanical sensing, and surgical automation — making his work essential reading for researchers in medical robotics and intelligent surgical systems.