Kamel Boudjit

University of Sciences and Technology Houari Boumediene, University of Algiers 3

Papers

Total Citations

152

H-Index

About

Kamel Boudjit is a researcher at the forefront of autonomous robotics and artificial intelligence, with a primary focus on Unmanned Aerial Vehicles (UAVs) and computer vision. His work centers on enabling quadrotors to perceive, track, and interact with their environment without human intervention. Boudjit’s most significant contribution is his pioneering application of deep learning for real-time human detection from UAVs, as detailed in his highly cited 2021 paper on YOLO-v2, which has garnered 84 citations. This work bridges the gap between advanced AI and practical drone autonomy. Earlier foundational studies, such as his 2015 paper on autonomous target tracking with an AR.Drone (41 citations), established robust frameworks for object pursuit. He has also innovated in control systems, applying fuzzy logic for target tracking (21 citations) and developing stabilization algorithms for micro quadrotors. Boudjit’s research is notable for its direct applicability to surveillance, search-and-rescue, and autonomous navigation, demonstrating a clear progression from basic control theory to sophisticated deep learning integration. His cumulative impact, reflected in over 150 citations, marks him as a key contributor to the evolution of intelligent, autonomous aerial systems.