Nayomi Fernando is a dedicated researcher with a strong academic and professional foundation in electrical and electronic engineering, with a focus on energy systems, machine learning, and artificial intelligence. She holds a Master of Science in Renewable Energy Engineering with Distinction from Kingston University, London, and a Bachelor of Science in Engineering (Hons) in Electrical and Electronic Engineering from the Sri Lanka Institute of Information Technology (SLIIT). Her research interests encompass a broad spectrum, including machine learning, image processing, fuzzy logic and systems, FPGA design, embedded systems, electronic circuit design, artificial intelligence, renewable energy technologies, electrical power systems, control systems, and smart grid technologies. Nayomi’s research experience includes key areas such as: FPGA-based computer vision for renewable energy systems, thermal image analysis in energy applications, smart grid control and optimization, and intelligent fault detection systems for electrical infrastructure.