Mohammed Ramdani

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About

Mohammed Ramdani is an emerging researcher whose work sits at the intersection of artificial intelligence, robotics, and intelligent systems. His research spans two primary domains: AI-driven diagnostic expert systems and autonomous mobile robot navigation, with a particular focus on fuzzy logic and neuro-fuzzy approaches. Ramdani's most notable contribution to date is his development of a fuzzy explainable expert system for COVID-19 diagnosis, which addresses a critical limitation of traditional rule-based systems by improving interpretability and transparency — an increasingly vital concern in medical AI. This work has garnered 4 citations since its 2023 publication, reflecting its relevance during a period of intense global interest in automated diagnostic tools. In the robotics domain, Ramdani has pursued intelligent solutions for autonomous mobile robot navigation, developing both ANFIS-based controllers and expertise-guided neuro-fuzzy strategies. These contributions aim to enhance the reliability and efficiency of robots operating in complex real-world environments across fields such as medicine, military applications, and agriculture. While still building his citation profile, Ramdani's interdisciplinary approach — bridging explainable AI and adaptive control systems — positions him as a promising voice in the growing conversation around trustworthy, intelligent autonomous systems.