Syed Sahal Nazli Alhady
Summary
Assoc. Prof. Dr. Syed Sahal Nazli Alhady is an Associate Professor at the School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM). A leading expert in Artificial Intelligence (AI) and Embedded Systems, his career is defined by the integration of Neural Network architectures into hardware platforms (FPGA) to enhance autonomous robotic applications and medical diagnostics. Since his early pioneering work on noiseless ECG monitoring systems, he has remained at the forefront of intelligent system design, focusing on making AI more efficient through hardware acceleration.
Dr. Alhady has spearheaded numerous high-value research initiatives, serving as the Principal Investigator for projects such as the Embedded Neural Network FPGA for Cart Followers and Distance Identification using Neural Networks (in collaboration with Efinix Technology). His diverse research portfolio includes the development of tree-climbing robots for inoculation processes and intelligent navigation systems for wheelchair users. His contributions to the field have earned him prestigious recognitions, including the ITEX Gold Medal, the Agilent Technologies Innovator Award, and the Gold Medal for Intelligent ECG Diagnostic Systems.
Beyond his technical research, Dr. Alhady is a dedicated educator and mentor at USM, having successfully supervised several PhD and Master’s candidates to completion in areas ranging from Grid Environment Job Scheduling to Fault Detection in Induction Motors. He currently leads research teams investigating advanced Convolutional Neural Networks (CNN) for wearable technology and AI-based pediatric heart murmur diagnosis.
His extensive publication record spans high-impact international journals and book series with Springer Nature, IEEE, and IOP Publishing, covering topics such as meta-heuristic optimization, remote sensing for agriculture, and robust UAV flight control. As a senior member of the academic community, Dr. Alhady continues to bridge the gap between theoretical AI research and practical, embedded industry solutions.
Editorial Board Member
Work Details
Embedded System, Artificial Intelligent
Universiti Sains Malaysia
Malaysia
