Dr. Manoharan Madhiarasan is a Postdoctoral Fellow at the Department of Business Development and Technology, Aarhus School of Business and Social Sciences, Aarhus University, recognized for his expertise in renewable energy systems, artificial intelligence, machine learning, deep learning, forecasting, and optimization. He has previously served in research and academic roles across leading institutions, including IIT Roorkee, Transilvania University of Brașov, and the French Institute of Pondicherry, along with experience as Assistant Professor, Research and Development Coordinator, and project mentor in engineering and technology programs. His research spans solar and wind energy forecasting, photovoltaic system modelling, metaheuristic optimization, neural network design, IoT-based energy systems, and intelligent hybrid models, resulting in extensive international journal publications, book chapters, patents, and conference contributions. He has led national workshops, served as convener and coordinator for faculty development programs, and delivered keynote addresses at global summits on renewable energy and intelligent systems. Dr. Madhiarasan holds several prestigious recognitions, including competitive research fellowships and a Best Researcher Award, and he is an IEEE Senior Member with memberships across numerous professional bodies. He contributes widely to the scholarly community as Associate Editor, Guest Editor, and Editorial Board Member for multiple international journals, and as a reviewer for high-impact publishers such as Springer, Elsevier, IEEE, Wiley, MDPI, and Frontiers. His record reflects sustained leadership, interdisciplinary scholarship, and significant contributions to advanced energy technologies and computational intelligence. His research impact includes 466 citations, 31 publications, and an h-index of 9.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. M. Madhiarasan, G. Fotis, M. Presser, M.J. Beliatis, Mountain Gazelle Optimiser-based single, double, and triple diode models associated solar cells and panels parameters extraction. Discover Sustainability, 2025, 6, 903.

2. M. Madhiarasan, S.N. Deepa, N.Y. Jayalakshmi, Hyperparameter optimization of a deep radial basis neural learning approach for wind speed forecasting. Int. J. Syst. Assur. Eng. Manag., 2025, Accepted.

3. M. Madhiarasan, Bayesian optimisation algorithm based optimised deep bidirectional long short term memory for global horizontal irradiance prediction in long-term horizon. Front. Energy Res., 2025, 13, 1499751.

4. M. Madhiarasan, S.N. Deepa, Comparative analysis on hidden neurons estimation in multilayer perceptron neural networks for wind speed forecasting. Artif. Intell. Rev., 2016, 1–23.

5. M. Madhiarasan, M. Louzazni, Analysis of artificial neural network: architecture, types, and forecasting applications. J. Electr. Comput. Eng., 2022, 5416722.

Dr. Madhiarasan’s work advances intelligent renewable energy systems by integrating AI-driven forecasting, optimization, and smart energy technologies that enhance the reliability and efficiency of global power infrastructures. His research supports sustainable energy transitions, strengthens industry innovation, and provides data-driven solutions for emerging challenges in solar and wind energy applications. He envisions a future where intelligent computational models power cleaner, smarter, and more resilient energy ecosystems worldwide.