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About

Mohammad Alkhedher is a robotics and artificial intelligence researcher whose work spans autonomous systems, intelligent robotics, and human-centered technology. His research consistently bridges cutting-edge AI methodologies with real-world applications, ranging from industrial monitoring to assistive technologies for vulnerable populations. Alkhedher's most influential contributions include a comprehensive survey on multiple object tracking in robotic applications (33 citations) and a cloud-based AI framework for detecting thermal anomalies in industrial environments using edge-fog-cloud architecture (32 citations), demonstrating his expertise in integrating IoT, cloud computing, and machine learning. His early work on neural network-based SCARA robot control (16 citations) established his foundational interest in intelligent control systems, while his frontier-based cooperative robot exploration strategies (12 citations) highlight his contributions to multi-robot coordination. Particularly notable is his commitment to socially impactful robotics — designing AI-powered service robots for elderly and disabled shoppers, autonomous mask-detection systems during the COVID-19 pandemic, and affordable 3D-printed prosthetic hands with sensory feedback. His more recent innovations, including wave-shaped soft robotic actuators and drone-based pavement crack detection systems, reflect a researcher continually pushing boundaries across both hardware design and intelligent systems — accumulating over 140 citations across a diverse and growing body of work.