Rafiq Asghar received the M.Sc. degree in Electrical Power Engineering from the University of Engineering and Technology, Peshawar, in 2018. His master's thesis focuses on the design of an SMC-based MSTFCL to improve LVRT and provide reactive power for the DFIG wind turbine system. He received the Ph.D. degree in Electrical Engineering (Photovoltaics) from the University of Salerno, Italy, in 2026. His doctoral research focused on developing hybrid deep learning models and adaptive metaheuristic optimisation algorithms for multi-step-ahead and real-time solar power forecasting. His current research interests include deep learning, power systems, power electronics, renewable energy systems, control systems, optimisation algorithms, and AI-driven energy applications.