Bao Pham
Papers
1
Total Citations
2
H-Index
1
About
Bao Pham is a rising researcher in computer vision whose work focuses on advancing active object tracking (AOT) through multi-agent systems. His most-cited paper, "CSAOT: Cooperative Multi-Agent System for Active Object Tracking" (2025), introduces a novel framework where multiple autonomous agents collaborate to track objects in dynamic environments—a critical capability for autonomous navigation, surveillance, and robotics. Unlike traditional passive object tracking, which depends on static cameras, Pham’s approach enables agents to actively adjust their viewpoints, significantly improving tracking robustness and accuracy. Though early in his career with 2 citations to date, this work represents a meaningful step toward scalable, real-world deployment of intelligent tracking systems. Pham’s contributions bridge the gap between cooperative robotics and computer vision, offering practical solutions for complex scenarios like multi-robot coordination and adaptive surveillance. His research promises to influence future developments in autonomous systems, where active perception and teamwork are essential for reliable performance.
Research Focus
Key Achievements
Top Papers
- 1CSAOT: Cooperative Multi-Agent System for Active Object Tracking2 citations · 2025