Papers
5
Total Citations
38
H-Index
4
About
Yawen Deng is a leading researcher in surgical robotics, with a focus on autonomous path planning, medical image segmentation, and procedure recognition for orthopedic and ophthalmic interventions. Her most significant contributions lie in advancing robot-assisted pelvic fracture closed reduction (RPFCR), where she developed intelligent path-planning algorithms that integrate collision avoidance and muscle force optimization to enhance surgical safety and efficiency. Her 2022 paper on autonomous path planning with collision avoidance has garnered 16 citations, while her 2023 work on muscle force optimization has received 8 citations, underscoring their impact on the field. Deng also pioneered dynamic multi-action recognition and expert movement mapping for closed pelvic reduction (7 citations), and introduced a semi-supervised medical image segmentation method guided by bi-directional constrained dual-task consistency (6 citations), addressing critical challenges in low-contrast tissue segmentation. Her recent work extends to vitreoretinal surgery, where she developed knowledge-driven procedure recognition for ILM peeling, a procedure requiring micrometer-level precision. Deng’s research bridges the gap between autonomous robotics and clinical safety, making her a key figure in the evolution of intelligent surgical systems.
Research Focus
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