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About

Fathi E. Abd El‑Samie is a leading researcher at the intersection of biometric security, human‑computer interaction, and machine learning for robotic applications. His work has garnered significant attention, with his most‑cited paper—on deploying machine learning techniques for human emotion detection—accumulating 117 citations. In this influential study, he advanced emotion recognition from both speech and visual modalities, directly impacting fields like robotic vision and interactive robotic communication. Abd El‑Samie has also made pioneering contributions to cancelable biometrics for the Internet‑of‑Things, introducing optical double random phase encoding to secure IoT devices and robots. His research extends to robust speaker identification using Radon transform and convolutional neural networks under interference, as well as the development of electrooculogram (EOG) acquisition systems for controlling robot arms via eye movements. By integrating biometrics, signal processing, and deep learning, Abd El‑Samie’s work enables more secure, intuitive, and adaptive human‑robot interaction. His achievements reflect a sustained commitment to solving real‑world challenges in security and assistive technology, making him a notable figure in modern applied signal processing and biometric systems.