معرفی
Barry Fitzgerald is an Assistant Lecturer in the Department of Electrical and Electronic Engineering at the Faculty of Engineering and the Built Environment. His research focuses on applying machine learning to address challenges in data storage systems, particularly NAND flash memory endurance prediction, bit error correction, and process optimization. He has contributed to interdisciplinary work combining machine learning with process mining for industrial applications.
Key research areas include machine learning algorithms for error prediction in flash memory, classification models, and system engineering. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure. Fitzgerald has published extensively in peer-reviewed journals and conferences, with notable contributions in IEEE Access, Procedia Manufacturing, and international machine learning symposia.
Collaboration highlights include partnerships on NAND flash endurance modeling and process optimization techniques. His research bridges electrical engineering and computer science, emphasizing practical solutions for data storage reliability and efficiency.
