Renhe Jiang

The University of Tokyo

Papers

2

Total Citations

36

H-Index

2

About

Renhe Jiang is a leading researcher in intelligent transportation and autonomous systems, with a core focus on human trajectory prediction and social interaction modeling. His work addresses the critical challenge of enabling autonomous vehicles and social robots to navigate safely in crowded, dynamic environments. Jiang’s major contributions lie in developing interpretable, multimodal models that capture the complex, heterogeneous nature of human motion and social interactions. His highly cited 2020 paper, "Multimodal Interaction-Aware Trajectory Prediction in Crowded Space" (28 citations), pioneered accurate path forecasting by integrating dynamic human interaction patterns with the intrinsic multimodality of pedestrian movement. More recently, his 2024 work, "Modeling interpretable social interactions for pedestrian trajectory" (8 citations), advances the field by making these interaction models transparent and understandable, a crucial step for real-world deployment in road safety and traffic management. Through these contributions, Jiang is shaping the future of collision avoidance and socially-aware navigation, providing foundational methods that bridge the gap between complex human behavior and autonomous decision-making.

Research Focus

Key Achievements

2
H-Index
2
Papers
36
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Multimodal Interaction-Aware Trajectory Prediction in Crowded Space
28 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: The University of Tokyo

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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