Puhua Jiang

Tsinghua–Berkeley Shenzhen Institute

Papers

1

Total Citations

10

H-Index

1

About

Puhua Jiang is a researcher whose work lies at the intersection of computer vision, robotics, and human behavior modeling, with a particular focus on enabling autonomous systems to safely navigate crowded, dynamic environments. In their highly regarded 2023 paper, "The Group Interaction Field for Learning and Explaining Pedestrian Anticipation," Jiang tackles a fundamental challenge: how machines can anticipate the future movements of pedestrians—a skill that comes naturally to humans but remains elusive for robots and self-driving cars. By introducing the concept of a "Group Interaction Field," Jiang provides a novel framework that not only predicts pedestrian trajectories but also offers interpretable explanations for those predictions, moving beyond black-box solutions. This work, which has already garnered 10 citations, addresses a critical gap in existing predictive models, which often struggle with the complex, non-linear interactions of dense crowds. Jiang’s contributions are paving the way for safer, more socially-aware unmanned systems, making them a rising voice in the fields of autonomous navigation and human-robot interaction.

Research Focus

Key Achievements

1
H-Index
1
Papers
10
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
The Group Interaction Field for Learning and Explaining Pedestrian Anticipation
10 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Tsinghua–Berkeley Shenzhen Institute

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago