Reza Khalili | Strategic Decision-Making | Best Researcher Award

Published on by Business Strategy

Mr. Reza Khalili | Strategic Decision-Making | Best Researcher Award 

Research Assistant at Stony Brook University | United States 

Mr. Reza Khalili is a graduate student in Electrical and Computer Engineering at Stony Brook University, where he is pursuing a Ph.D. in Electrical Engineering with a strong academic record. His educational background also includes a master’s degree in Electrical Engineering from Amirkabir University of Technology and a bachelor’s degree in Electrical Engineering from the University of Isfahan. His research primarily focuses on power systems optimization, renewable energy integration, electricity markets, and the application of advanced computational and machine learning methods in energy systems. His scholarly impact is reflected in 81 citations across 78 documents, with 6 publications and an h-index of 4. Khalili has contributed to several peer-reviewed journals and conferences, publishing impactful works on topics such as robust multi-objective optimization for electricity markets, socio-economic energy hub design, peer-to-peer energy trading, and uncertainty management in renewable energy integration. His co-authored works have appeared in respected journals including Applied Energy, Journal of Energy Storage, and Energy & Buildings, and he has contributed a book chapter published by Taylor & Francis. His conference papers include research on security-constrained optimal power flow and distribution network resilience, one of which was recognized as a best paper finalist at IEEE SmartGridComm. In his academic career, Khalili has gained valuable research experience as a graduate research assistant, working on advanced optimization techniques, contingency prediction in power systems, and uncertainty quantification methods.

Profiles : Scopus | ORCID | Google Scholar 

Featured Publications: 

Khalili, R., Khaledi, A., Marzband, M., Nematollahi, A. F., Vahidi, B., & Siano, P. (2023). Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs. Applied Energy, 334, 120737.

Darvishi, A., Ranjbar, B., Gharibi, R., Khalili, R., & Dashti, R. (2024). Multi-objective optimization of a socio-economic energy hub with demand response program and considering customer satisfaction. Journal of Energy Storage, 100, 113624.

Gharibi, R., Khalili, R., Vahidi, B., Nematollahi, A. F., Dashti, R., & Marzband, M. (2025). Enhancing energy hub performance: A comprehensive model for efficient integration of hydrogen energy and renewable sources with advanced uncertainty management strategies. Journal of Energy Storage, 107, 114948.

Gharibi, H., Gharibi, R., Khalili, R., Dashti, R., Marzband, M., & Rawa, M. (2025). Optimizing multi-objective peer-to-peer energy trading in green homes: Robust strategies to address non-probabilistic uncertainty using IGDT with integrated demand response. Energy and Buildings, 116435.

Gharibi, R., Vahidi, B., Dashti, R., & Khalili, R. (n.d.). From electrons to solutions: Power-to-X strategies for energy systems integration. In Power-to-X in regional energy systems (pp. 201–227). Taylor & Francis.

Hossein Mirzaeen | Strategic Planning | Best Researcher Award

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Dr. Hossein Mirzaeen | Strategic Planning | Best Researcher Award

Dr. Hossein Mirzaee, University of Saskatchewan, Canada

Dr. Hossein Mirzaee is a passionate researcher in the field of operations management, with expertise spanning green supply chain optimization, uncertainty modeling, and game theory applications. He holds a PhD in Operations Management from the University of Saskatchewan, where his work has been recognized for advancing sustainability in supply chain systems. With a strong academic foundation and professional experience both in academia and industry, Hossein brings a rare combination of analytical rigor, programming expertise, and real-world insight to his work. 🌍📈

👤 Profile

Scopus

🎓 Education

Dr. Mirzaee earned his PhD in Operations Management from the University of Saskatchewan (2019–2023), where he focused on green supply chain management, uncertainty control, and game theory-based models. Prior to that, he completed an MSc in Industrial Engineering at Kharazmi University (2015–2017), with research on optimization and metaheuristics. His academic journey began with a BSc in Industrial Engineering from Razi University (2011–2015), where he delved into project management and operations research.

💼 Experience

Dr. Mirzaee has diverse academic and industry experience. As a Graduate Research Assistant at the University of Saskatchewan, he implemented exact and metaheuristic algorithms in Python and GAMS to optimize green supply chains. He applied game-theoretical models using NashPy to reduce carbon emissions and handle regulatory conflicts. His teaching roles include sessional lecturer and co-instructor in operations and statistics, where he led tutorials and designed assessments. Outside academia, he served as Operations Manager at Europcar Iran and worked at the National Iranian Oil Refining and Distribution Company, contributing to equipment maintenance planning.

🔬 Research Interests

Dr. Mirzaee’s research interests lie at the intersection of green supply chain management, optimization, and game theory. He explores uncertainty modeling through stochastic, fuzzy, and robust optimization techniques. His recent studies address challenges like carbon cap-and-trade, supply chain disruption during pandemics, and sustainable decision-making models. He is also intrigued by approximation algorithms and metaheuristics in large-scale supply chain systems.

🏆 Awards & Recognition

Dr. Mirzaee was entrusted with leadership as President of the Iranian Students’ Council at the University of Saskatchewan (2020–2021), where he organized cultural and academic events. As a respected peer reviewer for journals like Computers & Industrial Engineering and Maritime Policy & Management, he has been acknowledged for his constructive insights and contributions to academic quality enhancement.

📚 Publication Top Notes

 A preemptive fuzzy goal programming model for generalized supplier selection and order allocation with incremental discount. Computers & Industrial Engineering,

A robust optimization model for green supplier selection and order allocation in a closed-loop supply chain considering cap-and-trade mechanism.

 A three-player game theory model for carbon cap-and-trade mechanism with stochastic parameters. 

Resilient green supply chain design to mitigate the ripple effect: A two-stage stochastic optimization model (To be submitted)

Sustainable Entrepreneurship: A Systematic Review and Call for Pivoting toward SDGs

An evolutionary game theory model to solve the conflicts between cap-and-trade — In preparation