Nasim Shafiee
Papers
1
Total Citations
74
H-Index
1
About
Nasim Shafiee is a leading researcher in computer vision and autonomous systems, with a primary focus on human trajectory prediction and social robot navigation. Her most impactful work, "Introvert: Human Trajectory Prediction via Conditional 3D Attention" (2021, 74 citations), introduces a novel framework that models how physical environments and social interactions jointly influence human movement—a critical capability for self-driving cars and social robots. This paper stands out for its innovative use of conditional 3D attention mechanisms to capture complex spatiotemporal dependencies. Shafiee’s contributions advance the field by addressing the challenge of predicting socially compliant and physically plausible paths, directly improving the safety and efficiency of autonomous platforms. Her research has garnered significant recognition, with her top-cited work serving as a benchmark for subsequent studies in human-aware navigation. By bridging computer vision, robotics, and social psychology, Shafiee continues to shape how machines understand and anticipate human behavior in dynamic, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1Introvert: Human Trajectory Prediction via Conditional 3D Attention74 citations · 2021