Dr. Mohammed M. Alenazi is an Assistant Professor of Computer Engineering at the University of Tabuk, Saudi Arabia, whose research focuses on the intersection of energy-efficient communication networks, machine learning, and distributed systems. His work advances intelligent computing architectures that optimize performance, reduce energy consumption, and enable sustainability in next-generation networks. Dr. Alenazi has contributed to several impactful studies, including energy-efficient neural network embedding in IoT over passive optical networks, distributed machine learning in cloud–fog environments, and AI-driven frameworks for 6G-IoT-based remote cardiac monitoring. His research extends to federated learning for low-latency IoT communications, hybrid cloud edge architectures for real-time cryptocurrency forecasting with blockchain integration, and machine learning-optimized energy management for resilient residential microgrids with electric vehicle integration. His scholarly output, cited over 50 times with an h-index of 4 and i10-index of 3, reflects growing recognition in the domains of sustainable networking and intelligent systems. Dr. Alenazi’s work combines AI, IoT, and cloud–fog computing to create adaptive, energy-aware solutions for smart environments, healthcare, and industrial systems. Through his innovative contributions, he continues to enhance the efficiency, reliability, and intelligence of modern communication infrastructures, positioning his research at the forefront of AI-powered green networking and distributed intelligence for the evolving digital ecosystem.