Mahyar Fazli | Green Building and LEED Design | Best Innovation Award

Published on by Architecture Engineers

Dr. Mahyar Fazli | Green Building and LEED Design | Best Innovation Award

Research Assistant | Sharif University of Technology | Iran

Mahyar Fazli is a Research Assistant in the Department of Aerospace Engineering at Sharif University of Technology, specializing in thermoacoustics, renewable energy systems, waste heat recovery, pulsating heat pipes, and advanced thermal management technologies. His professional experience includes leading simulation, analysis, and design efforts on thermoacoustic refrigeration and power-generation systems, contributing to the development of high-efficiency thermal devices, and advancing research on pulsating heat pipes, nanofluid-based solar receivers, and Organic Rankine Cycle applications. He has authored multiple high-impact publications in reputable journals, including comprehensive reviews, experimental investigations, and optimization studies that address thermoacoustic performance, exergy analysis, and innovative cooling strategies. His contributions include conceptual design of thermoacoustic integration in sustainable architecture, advancements in pulsating heat pipe geometries, and methodologies for enhancing heat-driven refrigeration systems. In addition to his research output, he has an extensive record of peer-review service for major international journals across renewable energy, thermal engineering, artificial intelligence, and fluid dynamics, reflecting his recognition as an emerging expert in the field. He actively engages in scholarly communities through editorial and review activities, professional memberships, and interdisciplinary collaborations, demonstrating a strong commitment to advancing sustainable energy technologies and improving thermal system efficiency. His research impact includes 517 citations, 8 publications, an h-index of 7.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Ansari M., Basiri M., Fazli M., Mazaheri K., Hosseinzadeh S., Matini M.R., Innovative integration of thermoacoustic technology in architectural design for sustainable cooling: A conceptual design. Energy, 2025, 139102.

2. Mahmoudi A., Fazli M., Morad M.R., A recent review of waste heat recovery by Organic Rankine Cycle. Appl. Therm. Eng., 2018, 143, 660–675.

3. Mehrjardi S.A.A., Khademi A., Fazli M., Optimization of a thermal energy storage system enhanced with fins using generative adversarial networks method. Therm. Sci. Eng. Prog., 2024, 49, 102471.

4. Mahmoudi A., Fazli M., Morad M.R., Gholamalizadeh E., Thermo-hydraulic performance enhancement of nanofluid-based linear solar receiver tubes with forward perforated ring steps and triangular cross section: A numerical investigation. Appl. Therm. Eng., 2020, 169, 114909.

5. Fazli M., Mehrjardi S.A.A., Mahmoudi A., Khademi A., Amini M., Advancements in pulsating heat pipes: Exploring channel geometry and characteristics for enhanced thermal performance. Int. J. Thermofluids, 2024, 22, 100644.

Mahyar Fazli’s work advances next-generation thermal and energy systems by developing high-efficiency thermoacoustic, heat-transfer, and waste-heat-recovery technologies that address global sustainability challenges. His research contributes to cleaner energy futures by improving cooling systems. Through innovative modeling, design, and interdisciplinary collaboration, he drives scientific progress toward more efficient and environmentally responsible energy systems worldwide.

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.