Mahmoud Abdelhamid
Ain Shams University, International University, Clemson University
Papers
4
Total Citations
55
H-Index
2
About
Mahmoud Abdelhamid is a robotics and agricultural automation researcher whose work bridges computer vision, autonomous systems, and precision agriculture. His research focuses on developing intelligent robotic solutions for complex real-world tasks, with a particular emphasis on agricultural robotics and human-robot interaction in unstructured environments. Abdelhamid's foundational contributions began with stereo vision systems, where his early work on correlation and feature-based depth extraction algorithms laid groundwork for autonomous pick-and-place robotic manipulation. This expertise in machine perception evolved into a broader research agenda centered on agricultural automation. His highly cited 2025 comprehensive review of apple harvesting robotics — already accumulating 32 citations — synthesizes advances in deep learning-based fruit detection, multi-source sensor fusion, and multi-arm vacuum systems, establishing itself as an essential reference for researchers in the field. Complementing this, his review of autonomous flower pollination techniques, with 19 citations, reflects his commitment to addressing critical challenges in food security through robotic intervention. Across his career, Abdelhamid has demonstrated a talent for synthesizing complex interdisciplinary research, making his review articles particularly valuable to emerging scholars seeking to navigate the rapidly evolving landscape of agricultural robotics and intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Extracting Depth Information Using a Correlation Matching Algorithm2 citations · 2012
- 4