Qiong Yan
Papers
1
Total Citations
1
H-Index
1
About
Qiong Yan is a leading researcher in robotics and artificial intelligence, with a primary focus on intelligent manipulation and deep learning for autonomous systems. Her work is distinguished by innovative approaches to robot arm grasping in cluttered environments, a critical challenge for industrial automation and service robotics. In her highly cited 2025 paper, "Robot arm grasping for cluttered fasteners based on deep learning with synthetic data augmentation," Yan introduced a novel method that leverages synthetic data generation to train deep learning models for robust object detection and grasping. This contribution addresses the perennial issue of data scarcity in robotics, enabling more reliable and adaptable automation. With over 1 citation already for this recent work, her research is gaining rapid recognition for its practical impact. Yan’s achievements include advancing the state of the art in sim-to-real transfer, making her a key figure in bridging the gap between simulation and real-world robotic performance. Her work is essential reading for students and researchers interested in deep learning for robotics, grasping algorithms, and data-efficient AI.
Research Focus
Key Achievements
Top Papers
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