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About

Zaid Abdi Alkareem Alyasseri is a rising figure in computational intelligence and biomedical engineering, whose work bridges the gap between nature-inspired algorithms and real-world healthcare solutions. His primary research areas include EEG signal processing, feature fusion techniques, and the application of metaheuristic optimization—particularly bat-inspired algorithms—to complex engineering problems. Alyasseri’s most impactful contribution is a robust EEG feature fusion framework for motor imagery, designed to aid stroke patients’ rehabilitation; this work has garnered 70 citations, reflecting its significance in brain-computer interface research. He has also authored a comprehensive review on bat-inspired algorithms, tracing their evolution and diverse applications, which has attracted 37 citations. More recently, he has explored the role of image processing in securing IoT applications, addressing critical privacy challenges in connected systems. Through these contributions, Alyasseri demonstrates a commitment to developing intelligent, secure, and human-centered technologies. His work not only advances theoretical understanding but also offers practical tools for rehabilitation and cybersecurity, making him a researcher to watch in the intersection of AI, signal processing, and healthcare.