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About

Boqiang Jia is a rising researcher in surgical robotics and intelligent medical systems, with a focus on enhancing precision and autonomy in robot-assisted surgery. His work spans tremor compensation, surgical gesture recognition, and tool detection—critical components for improving surgical outcomes. Jia’s most cited paper, "Tremor Estimation and Removal in Robot‐Assisted Surgery Using Improved Enhanced Band‐Limited Multiple Fourier Linear Combiner" (2024, 5 citations), tackles the challenge of hand tremor-induced vibrations during minimally invasive procedures, proposing a novel algorithm to stabilize surgical instruments. This contribution directly addresses a key barrier to fine motor control in robotic surgery. In "STANet: A Surgical Gesture Recognition Method Based on Spatiotemporal Fusion" (2025, 2 citations), he advances deep learning models for real-time action recognition, enabling better surgical quality evaluation. His work "Tool-YOLO" (2025, 1 citation) further demonstrates his versatility in computer vision for surgical environments. Though early in his career, Jia’s integrated approach to sensing, estimation, and recognition positions him as a promising innovator in the next generation of intelligent surgical systems.