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About

Xiaoyan Yu is a robotics and biomedical engineering researcher whose work sits at the intersection of surgical robotics, force sensing, and intelligent control systems. Yu's most recognized contribution is the development of forceps with three-dimensional force sensing capability for robot-assisted surgical systems, a landmark 2018 paper that has garnered 35 citations. This work directly addresses one of the core challenges in minimally invasive surgery — enabling surgeons to accurately differentiate tissue stiffness and apply precise manipulation forces within the severe space constraints imposed by surgical instruments. Building on this foundation, Yu has also explored machine learning approaches to surgical instrumentation, notably applying BLSTM–MLP neural network architectures to estimate microinstrument contact forces through cable tension measurements, demonstrating a sophisticated blend of deep learning and mechanical engineering. Further expanding into autonomous surgical assistance, Yu has investigated reinforcement learning algorithms for automatic laparoscope arm positioning, contributing to smarter preoperative planning in robot-assisted laparoscopic procedures. Collectively, Yu's research portfolio reflects a coherent vision: making robotic surgery safer, more precise, and increasingly intelligent — work that holds significant promise for the future of minimally invasive clinical practice.