Qiyuan Sun

Papers

Total Citations

109

H-Index

About

Qiyuan Sun is a leading researcher at the intersection of surgical robotics and computer vision, whose work is transforming the safety and precision of minimally invasive procedures. His primary contributions lie in developing advanced visual detection and tracking algorithms for surgical instruments, a critical challenge in modern robotic surgery. Sun’s most influential work, a comprehensive 2021 review on visual detection and tracking algorithms for minimally invasive surgical instruments, has garnered 75 citations, establishing it as a foundational resource in the field. Building on this, he pioneered the application of YOLOv4 for real-time object detection of surgical tools, a 2021 study with 24 citations that directly addresses the risk of instrument-tissue collisions in robotic systems. Earlier in his career, Sun demonstrated his versatility by tackling the complex dynamics of flexible manipulators, achieving precise position control for a 2DOF underactuated system—a 2011 paper with 10 citations that showcases his deep expertise in robotics control theory. Through his work, Sun is not only advancing the state-of-the-art in computer-assisted surgery but also paving the way for safer, more autonomous robotic systems in the operating room.