Hoda Baraka

Papers

Total Citations

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About

Hoda Baraka is a computer vision researcher whose work focuses on efficient multi-object tracking for real-time applications, particularly in crowded environments. Her most-cited paper, "LMOT: Efficient Light-Weight Detection and Tracking in Crowds" (2022, 25 citations), addresses a critical bottleneck in robotics and vision systems: the trade-off between tracking accuracy and computational speed. By introducing a lightweight detection and tracking pipeline, Baraka enables robust multi-object tracking in dense crowds without sacrificing real-time performance—a breakthrough for autonomous navigation and surveillance systems. Her contributions are especially valuable for deploying computer vision on resource-constrained platforms, such as drones or mobile robots. With a growing citation record, Baraka is establishing herself as a rising expert in efficient vision architectures, bridging the gap between academic research and practical deployment. Her work on LMOT has been recognized for its potential to transform how machines perceive and interact in dynamic, crowded spaces.