XU Yue-yun
Papers
1
Total Citations
2
H-Index
1
About
Dr. Xu Yue-yun is a rising researcher in the field of intelligent transportation and autonomous systems, with a primary focus on pedestrian trajectory prediction and human-robot interaction. Their most notable contribution, the 2025 paper "Pedestrian trajectory prediction via physical-guided position association learning," introduces a novel framework that integrates physical constraints with deep learning to address the inherent uncertainty and environmental complexity in forecasting pedestrian movements. By moving beyond simplistic LSTM-based models, Dr. Xu’s work enhances the reliability of trajectory prediction for critical applications in autonomous driving, robotics, and video surveillance. Though early in their career, this work has already garnered 2 citations, signaling growing recognition in the computer vision and robotics communities. Dr. Xu’s research bridges the gap between physical modeling and data-driven approaches, offering a more robust solution for safe navigation in dynamic environments. Their contributions are particularly valuable for students and researchers seeking to understand how domain knowledge can be effectively embedded into neural architectures for real-world prediction tasks.
Research Focus
Key Achievements
Top Papers
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