Papers
4
Total Citations
34
H-Index
3
About
Abdelrahman Youssef is a robotics and automation researcher whose work sits at the intersection of intelligent control systems, computer vision, and robotic mechanisms. His research spans medical robotics, industrial automation, and parallel manipulator systems, demonstrating a broad commitment to applying artificial intelligence in engineering contexts. Youssef's most influential contribution to date is his 2022 work on an autonomous wheelchair system, which leverages genetic algorithm optimization for identification and control, earning 15 citations and representing a meaningful advance in assistive robotics technology. His 2024 vision-guided robotic system for aero-engine inspection and dynamic balancing — accumulating 11 citations — addresses a critical gap in aerospace maintenance automation, replacing error-prone manual procedures with intelligent robotic solutions during the era of Industry 4.0. Earlier in his career, Youssef contributed foundational work on parallel manipulators, modeling a 3-DOF parallel robot using artificial neural networks in 2019, and later exploring stereovision integration in Delta robots for pick-and-place applications. These studies reflect his sustained interest in solving kinematic complexity through machine learning approaches. With a growing citation record across medical, aerospace, and industrial domains, Youssef is emerging as a versatile contributor to applied robotics research.
Research Focus
Key Achievements
Top Papers
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