Razin Ahmed

Razin Ahmed is an Adjunct Lecturer at the School of Engineering, specifically within the Department of Electrical, Electronic and Computer Engineering at The University of Western Australia. His research focuses on renewable energy systems, particularly photovoltaic power forecasting and machine learning applications. He has published extensively on topics such as LSTM-based ensemble methods for solar power prediction and advanced antenna design for wireless communication standards like IEEE 802.11p.

Key research interests include photovoltaics, solar energy optimization, artificial neural networks, and multiband antenna technologies. His work contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and climate action (SDG 13). Ahmed's methodologies often integrate machine learning with traditional engineering approaches to enhance energy system efficiency and predictive accuracy.

His most recent publications (2022) highlight advancements in adaptive weighting techniques and data segmentation for photovoltaic forecasting, while earlier works (2014–2016) explore innovative antenna designs using metamaterials and slot structures. Collaborations have focused on optimizing renewable energy systems and improving wireless communication infrastructure.

Notably, his 2020 review article evaluates state-of-the-art PV forecasting techniques, influencing both academic and industry practices. While no specific awards or grants are listed, his high citation count (954 citations) and h-index (9) reflect significant scholarly impact in energy and electronics fields.