Guocheng Yan
Papers
2
Total Citations
72
H-Index
2
About
Guocheng Yan is a researcher advancing the field of autonomous systems through innovative work in pedestrian trajectory prediction. His primary research areas encompass graph-based deep learning, adversarial learning, and uncertainty modeling for dynamic scene understanding. Yan’s most notable contribution is his novel graph-based trajectory predictor with a pseudo-oracle mechanism, which addresses the critical challenge of capturing complex motion patterns and social interactions among pedestrians in real-world environments—a problem central to self-driving cars and socially aware robots. This work, published in 2021, has garnered 69 citations, reflecting its significance in improving prediction accuracy and handling future uncertainty. Additionally, Yan has explored adversarial learning frameworks with knowledge-rich latent variables to further enhance trajectory forecasting robustness. His research directly impacts the safety and efficiency of autonomous navigation systems, offering practical solutions for predicting human behavior in crowded, dynamic scenes. Yan’s achievements position him as a promising contributor to the intersection of computer vision, robotics, and artificial intelligence, with his work serving as a foundation for future advances in socially compliant motion planning.
Research Focus
Key Achievements
Top Papers
- 1A Novel Graph-Based Trajectory Predictor With Pseudo-Oracle69 citations · 2021
- 2