Ying Weng

Bangor University, University of Nottingham Ningbo China

Papers

Total Citations

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About

Ying Weng is a researcher whose work spans robotics, computer vision, and navigation systems. Her key research areas include robotic calibration, surgical skill assessment, and sensor-based navigation. A major contribution is her flexible method for combining camera calibration with hand–eye calibration, which streamlines the process of calibrating vision-guided robotic systems. This work, published in 2013, has garnered 19 citations, reflecting its foundational impact on robotics. More recently, Weng has advanced automated surgical skill assessment with her CWT-ViT framework, which integrates time–frequency analysis and vision transformers to evaluate robotic surgical performance. This 2024 paper has already attracted 12 citations, highlighting its timely relevance in medical robotics. Additionally, her work on UKF-SLAM-based gravity gradient aided navigation (2014, 4 citations) demonstrates her versatility in addressing navigation challenges. Weng’s research is notable for bridging theoretical calibration techniques with practical applications in surgery and autonomous navigation, making her contributions valuable for students and researchers in robotics and AI.