Dingye Yang
Papers
2
Total Citations
38
H-Index
2
About
Dingye Yang is a researcher advancing the field of autonomous systems through innovative work in human trajectory prediction and pedestrian behavior modeling. His primary research areas include spatial-temporal reasoning, social interaction modeling, and multi-modal prediction for robotics and autonomous driving. Yang's major contribution is the development of the Group-Aware Spatial-Temporal Transformer (GA-STT), a novel framework that addresses the core challenge of modeling socially aware spatial interactions and complex temporal dependencies among crowds. This work, which has garnered 31 citations, significantly improves the accuracy of human trajectory prediction by incorporating group dynamics into transformer architectures. Additionally, his research on Social Aware Multi-modal Pedestrian Crossing Behavior Prediction (7 citations) extends these capabilities to real-world traffic scenarios, enabling safer autonomous navigation. Yang's work is notable for bridging the gap between theoretical AI models and practical deployment in dynamic environments, making him a rising contributor to the intersection of computer vision, robotics, and intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Social Aware Multi-modal Pedestrian Crossing Behavior Prediction7 citations · 2023