Madhiarasan Manoharan | Energy-Efficient Architecture | Best Researcher Award

Published on by Architecture Engineers

Dr. Madhiarasan Manoharan | Energy-Efficient Architecture | Best Researcher Award

Postdoctoral Fellow | Aarhus University | Denmark

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.

Lesiba George Mollo | Building Energy Efficiency | Best Researcher Award

Published on by Architecture Engineers

Dr. Lesiba George Mollo | Building Energy Efficiency | Best Researcher Award

Senior Lecturer | Central University of Technology | South Africa

Dr. Lesiba George Mollo is a Senior Lecturer in the Department of Built Environment at the Central University of Technology, Free State, South Africa, specializing in construction management and construction health and safety. He holds a PhD in Construction Management from Nelson Mandela University, where his research focused on reducing human failures in construction through the Training-Within-Industry (TWI) method. He also earned an MTech in Quantity Surveying (Cum Laude), a BTech in Quantity Surveying, and a National Diploma in Building, complemented by professional certifications in project and safety management. Dr. Mollo’s professional journey spans academic leadership as Acting Head of Department, Deputy Research Dean, and Research Chair, as well as practical roles with leading construction firms managing infrastructure, housing, and public works projects. His research expertise encompasses construction safety management, wearable sensing devices, 360° video technology for behavioral monitoring, and energy-efficient building technologies. He has published over forty scholarly outputs, including peer-reviewed journal articles, book chapters, and the authored volume Training-Within-Industry Job Programs for Improved Construction Safety (Routledge). Dr. Mollo actively contributes to academic development through postgraduate supervision, conference organization, and peer reviewing for international journals. He has received recognition for academic excellence, including the MTech Best Performance Award from Nelson Mandela University, and holds memberships in the South African Council for the Project and Construction Management Professions (SACPCMP) and the Association of South African Quantity Surveyors (ASAQS). He has 35 citations, 14 publications, and an h-index of 3.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Mollo, L. G. (2025). Evaluating the use of 360° video technology to monitor workers’ unsafe behaviour in the construction industry. In International Civil Engineering and Architecture Conference (pp. 685–693). Springer Nature Singapore.

2. Mollo, L. G., & Chomey, T. (2025). An analysis of barriers to the implementation of energy-efficient technologies in residential buildings: A quantitative approach. Buildings, 15(19), 3520.

3. Mtetwa, S. I., Mollo, L. G., & Emuze, F. (2024). Wearable sensing devices for better monitoring of health, safety, and wellbeing in construction. In Handbook of Drivers of Continuous Improvement in Construction Health, Safety, and Wellbeing (pp. 59–68). Routledge.

4. Mollo, L. G. (2024). Using wearable technologies to minimise occupational illnesses among construction workers. Proceedings of the Institution of Civil Engineers – Forensic Engineering, 177(2), 64–71.

5. Mollo, L. G., Emuze, F., & Smallwood, J. (2023). Causes of human failure on construction sites. In Training-Within-Industry Job Programs for Improved Construction Safety (pp. 13–27). Routledge.