Md Shohel Sayeed

Multimedia University, Cloud Computing Center

Papers

Total Citations

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About

Md Shohel Sayeed is a researcher whose work bridges the frontiers of intelligent systems, next-generation networking, and computer vision. His key research areas include fuzzy logic control, 5G and beyond (B5G) communications, and efficient object detection. Sayeed made a notable contribution to mobile robotics with his "Modified Hybrid Fuzzy Controller," which tackled the limitations of traditional fuzzy systems when handling multi-sensor inputs—a critical challenge for real-time navigation. In the networking domain, he served as a guest editor for a special issue on P2P computing for 5G, B5G, and the Internet-of-Everything (IoE), a work that has garnered 11 citations and reflects his engagement with the evolving landscape of pervasive connectivity. Most recently, his 2025 study on "Efficient Object Detection with an Optimized YOLOv8x Model" addresses practical hurdles in indoor environments, such as occlusions and variable lighting, by systematically evaluating YOLOv8 variants to enhance detection accuracy. With a growing citation footprint and a trajectory from foundational fuzzy control to cutting-edge deep learning, Sayeed’s work demonstrates a sustained commitment to solving real-world engineering problems across multiple domains.