Xiaolin Zhai
Papers
2
Total Citations
38
H-Index
2
About
Xiaolin Zhai is a leading researcher in human trajectory prediction and pedestrian behavior modeling, with a focus on advancing robotics and autonomous driving systems. Her most influential work, "GA-STT: Human Trajectory Prediction With Group Aware Spatial-Temporal Transformer" (2022, 31 citations), introduces a novel framework that integrates group-aware spatial interactions and complex temporal dependencies to predict crowd movements—a critical challenge for safe autonomous navigation. This paper has become a cornerstone in the field, cited for its innovative use of transformers to capture social dynamics. Zhai further extends this research in "Social Aware Multi-modal Pedestrian Crossing Behavior Prediction" (2023, 7 citations), where she models multi-modal pedestrian intentions to improve crossing behavior forecasts. Her contributions are notable for bridging social awareness with deep learning, enabling more robust and context-aware predictions in dynamic environments. With a growing citation impact, Zhai’s work is shaping the next generation of intelligent transportation systems, offering practical solutions for real-world human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2Social Aware Multi-modal Pedestrian Crossing Behavior Prediction7 citations · 2023