Anam Manzoor

Papers

Total Citations

H-Index

About

Anam Manzoor is a researcher advancing the field of multi-modal perception and autonomous systems, with a primary focus on multi-object tracking (MOT) using LiDAR and visual signals. Her work addresses the critical challenge of detecting and maintaining object identities across sequential frames, a cornerstone technology for applications in autonomous driving, robotics, and surveillance. Manzoor’s most cited paper, "Multi-Modal Tracking Using LiDAR and Visual Signals" (2024), introduces a novel framework that fuses complementary sensor modalities to enhance tracking robustness in complex environments, achieving improved accuracy and reliability over single-sensor approaches. With 3 citations already in its first year, this work demonstrates early impact and relevance in a rapidly evolving field. By tackling the core problem of correspondence establishment in dynamic scenes, Manzoor contributes to safer and more efficient autonomous navigation systems. Her research sits at the intersection of computer vision, sensor fusion, and real-time decision-making, offering practical solutions for next-generation intelligent vehicles and surveillance technologies.