Ahmed H. Elsheikh

Cairo University, Hamad bin Khalifa University

Papers

Total Citations

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About

Dr. Ahmed H. Elsheikh is a pioneering researcher at the intersection of computer vision, robotics, and human-robot interaction. His primary research areas include event-based object detection and the adoption of assistive robotics, with a particular focus on developing intelligent systems that bridge the gap between advanced machine learning and real-world applications. Dr. Elsheikh's most notable contribution is his work on a recurrent YOLOv8-based framework for event-based object detection (2025, 15 citations), which addresses critical limitations of conventional frame-based RGB sensors—such as motion blur and poor performance under extreme lighting—by leveraging neuromorphic vision for autonomous vehicles and robotics. Additionally, his systematic review on the acceptance and adoption of humanoid robots among older adults (2024, 4 citations) provides valuable insights into the social and psychological factors influencing technology adoption in aging populations. Through his innovative approach to both algorithmic development and human-centered design, Dr. Elsheikh is shaping the future of intelligent, adaptive systems that are not only technically robust but also socially inclusive.