Yaofeng Sun
Papers
1
Total Citations
34
H-Index
1
About
Yaofeng Sun is a leading researcher in autonomous driving and robotics, specializing in multi-agent interaction behavior prediction. His work addresses a critical challenge: enabling AI systems to learn continuously from sequential datasets without forgetting prior knowledge. Sun’s most cited paper, “Continual Multi-Agent Interaction Behavior Prediction With Conditional Generative Memory” (2021, 34 citations), introduces a novel framework that uses conditional generative memory to preserve and adapt knowledge across evolving traffic scenarios. This breakthrough allows autonomous vehicles to predict the trajectories of multiple agents—pedestrians, cyclists, and other cars—more robustly over time, even as data distributions shift. By tackling catastrophic forgetting in multi-agent systems, Sun’s contributions bridge continual learning and trajectory forecasting, directly impacting the safety and reliability of self-driving technologies. His work has garnered attention for its practical relevance, with applications in real-world autonomous navigation and robot coordination. Sun’s research continues to push the boundaries of adaptive AI, making him a key figure in advancing intelligent transportation systems.
Research Focus
Key Achievements
Top Papers
- 1