Ahmed M. Eltawil

University of California, Irvine, King Abdullah University of Science and Technology

Papers

Total Citations

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About

Ahmed M. Eltawil is a leading researcher at the intersection of neuromorphic engineering and computer vision, with a focus on developing bio-inspired sensing and processing systems. His work is pioneering the creation of hardware and algorithms that mimic the human retina, enabling energy-efficient, high-speed perception for robotics and autonomous systems. A key contribution is his development of a flexible capacitive photoreceptor for biomimetic retinas, a foundational device that encodes light into spike sequences, directly addressing the need for low-power, privacy-preserving vision sensors. This work, published in 2022, has already garnered 60 citations, highlighting its impact on the field. More recently, Eltawil has advanced event-based object detection with a recurrent YOLOv8-based framework, overcoming the limitations of traditional frame-based sensors like motion blur and poor low-light performance. This 2025 publication, with 15 citations, demonstrates his ongoing commitment to solving real-world challenges in autonomous vehicles and advanced robotics. His research is notable for seamlessly integrating novel hardware design with cutting-edge deep learning, positioning him as a key figure in the next generation of intelligent, efficient vision systems.