Yueling Liu

Shanghai University of Engineering Science

Papers

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About

Yueling Liu is a rising researcher in the field of robotic-assisted vascular intervention, with a focused interest in improving the precision and safety of minimally invasive surgery. Her work centers on the intersection of medical robotics, computer vision, and machine learning, particularly for vascular interventional surgery robots (VISR). Her most notable contribution, detailed in her 2024 paper "An unsupervised learning-based guidewire shape registration for vascular intervention surgery robot," addresses a critical challenge in these systems: maintaining accurate shape registration of the flexible guidewire as it deforms during navigation. By proposing an unsupervised learning method, Liu’s work enhances the transparency of the master-slave control system, enabling physicians to manipulate guidewires more intuitively and precisely within complex vascular pathways. This innovation directly tackles the deformation-induced inaccuracies that can compromise surgical outcomes. Though early in her career, with her key paper already garnering attention, Liu’s research promises to advance the autonomy and reliability of robotic surgery, paving the way for safer, more effective endovascular procedures. Her dedication to solving real-world clinical problems marks her as a promising contributor to the future of interventional robotics.