Contact
Room 245, Mervis Hall
412-499-0652
Profile
Dr. Rokou develops computational approaches to complex decision problems in healthcare, manufacturing, and business operations. Her work integrates operations research, optimization, and machine learning, with an emphasis on building decision systems that are analytically rigorous and practically implementable. She is particularly interested in the use of emerging AI technologies, including digital twins and large language models with specialized agent personas, to support operational planning and innovation.
Her research spans scheduling and network optimization, genetic algorithms for combinatorial problems, and multi-criteria decision frameworks such as the Analytic Hierarchy Process and Analytic Network Process.
In the classroom, Dr. Rokou takes a model-driven approach. Students build working models, conduct computational experiments, and learn to translate quantitative results into operational insights. She emphasizes strong technical foundations, including algorithmic thinking, mathematical rigor, and computational efficiency, while grounding instruction in real-world implementation challenges and ethical considerations.
Awards and Honors
2024 Alexander Family Award for Teaching Excellence
2024 Outstanding Faculty of the Year – Class of 2024, Executive MBA
2024 Full-time Master’s Student Choice Award
Degrees
• Ph.D., Operations Research, National Technical University of Athens
• M.Sc., Financial and Engineering Management, University of the Aegean
• B.Sc., Computer Science, University of Ioannina
Selected Publications
Wei, L., & Rokou, E. (2024). A literature review on the integration of AI with AHP/ANP. Proceedings of the International Symposium on the Analytic Hierarchy Process.
Apostolopoulos, N., Chalvantzis, K., Liargovas, P., Newbery, R., & Rokou, E. (2020). The role of the expert knowledge broker in rural development: Renewable energy funding decisions in Greece. Journal of Rural Studies, 78, 96–106.
Saaty, T. L., & Rokou, E. (2017). How to prioritize inventions. World Patent Information, 48, 78–95.
Spanos, A. C., Ponis, S. T., Tatsiopoulos, I. P., Christou, I. T., & Rokou, E. (2014). A new hybrid parallel genetic algorithm for the job-shop scheduling problem. International Transactions in Operational Research, 21, 479–499.
Rokou, E., & Kirytopoulos, K. (2013). A calibrated group decision process. Group Decision and Negotiation, 1–16.