Qing Xiao

Concordia University, Sichuan University

Papers

Total Citations

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About

Qing Xiao is a researcher whose work bridges control theory and biomedical engineering, with key contributions in fuzzy control systems and neural signal processing. Xiao’s early influential paper, “Theory and Implementation of a Fuzzy Control Scheme for Pendubot” (2002, 6 citations), laid foundational work in nonlinear control, demonstrating how fuzzy logic can stabilize complex underactuated systems—a contribution that has informed robotics and automation research. More recently, Xiao has advanced medical technology through the proof-of-concept study “Neural signals-based respiratory motion tracking” (2023, 5 citations). This work addresses a critical challenge in thoracoabdominal radiotherapy and robotic surgery: the time lag inherent in conventional imaging-based tracking due to system latency. By leveraging neural signals, Xiao’s approach offers a more direct, potentially real-time method for respiratory motion compensation, promising to improve treatment accuracy and patient outcomes. Though citation counts are modest, the novelty and translational potential of this neural-signal framework mark a significant step forward. Xiao’s career reflects a thoughtful evolution from theoretical control to impactful biomedical applications, making their work of interest to students and researchers in robotics, control systems, and medical physics.