Dr. Amirmohammad Behzadi is a researcher specializing in intelligent thermal energy systems, recognized for advancing AI-driven optimization, predictive control, reinforcement learning, and physics-informed digital-twin modeling for building and district-scale heating and cooling networks. He holds advanced degrees in mechanical engineering and fluid and climate theory with a focus on energy conversion and system optimization. His professional experience spans research roles in leading institutions, where he has developed model-based control frameworks, machine-learning-enabled optimization tools, and integrated thermal–power system models while contributing to major national and international projects on smart, low-carbon, and resilient energy systems. He has led multi-institutional collaborations, coordinated national participation in global research initiatives, supervised students across levels, and contributed extensively to proposal development and funding acquisition. His publication record includes numerous first-author articles in high-impact journals, influential book chapters, and methods that have shaped the design and control of next-generation thermal networks. His research achievements are evidenced by substantial citation metrics, widespread academic influence, and recognition among the world’s top researchers. He has received distinctions for research excellence and contributed to award-winning projects acknowledged by prominent scientific and engineering bodies. His active participation in international collaborations and professional organizations further highlights his leadership and dedication to advancing sustainable, data-driven, and climate-resilient energy solutions.
Profiles: Google Scholar | Scopus | ORCID
Featured Publications
1. Habibollahzade, A., Gholamian, E., Ahmadi, P., & Behzadi, A. (2018). Multi-criteria optimization of an integrated energy system with thermoelectric generator, parabolic trough solar collector and electrolysis for hydrogen production. International Journal of Hydrogen Energy.
2. Habibollahzade, A., Gholamian, E., & Behzadi, A. (2019). Multi-objective optimization and comparative performance analysis of hybrid biomass-based solid oxide fuel cell/solid oxide electrolyzer cell/gas turbine using different configurations. Applied Energy, 233, 985–1002.
3. Behzadi, A., Habibollahzade, A., Zare, V., & Ashjaee, M. (2019). Multi-objective optimization of a hybrid biomass-based SOFC/GT/double effect absorption chiller/RO desalination system with CO₂ recycle. Energy Conversion and Management, 181, 302–318.
4. Behzadi, A., Gholamian, E., Houshfar, E., & Habibollahzade, A. (2018). Multi-objective optimization and exergoeconomic analysis of waste heat recovery from Tehran’s waste-to-energy plant integrated with an ORC unit. Energy.
5. Habibollahzade, A., Gholamian, E., Houshfar, E., & Behzadi, A. (n.d.). Multi-objective optimization of biomass-based solid oxide fuel cell integrated with Stirling engine and electrolyzer. [Journal name not specified].
Dr. The nominee’s work advances intelligent, low-carbon thermal energy systems by integrating AI, data-driven optimization, and physics-informed modeling to create more efficient, resilient, and autonomous urban energy infrastructures. His contributions support global sustainability goals by enabling cleaner, smarter heating and cooling networks that reduce emissions and improve energy reliability. Through innovative research and international collaboration, he drives technological progress that benefits science, industry, and society.