Meysam Rabiee is an Assistant Professor of Business Analytics at University of Colorado Denver. He earned his Ph.D. in Operations & Business Analytics from the Lundquist College of Business at the University of Oregon.

Meysam's research focuses mostly on developing decision support systems or applying analytics tools for social good. To be more specific, his primary areas of interest are healthcare analytics, sustainable supply chain, machine learning, evolutionary algorithms and group decision-making.

Education

Ph.D. Operations and Business Analytics, University of Oregon

MS, Operations and Business Analytics, University of Oregon

MS, Industrial Engineering, K.N. Toosi University of Technology

BS, Industrial Engineering, Bu-Ali Sina University

Areas of expertise

Methodology: Mathematical Modeling, Machine Learning, Evolutionary Algorithms, Multi-Criteria Decision Making

Application: Healthcare, Sustainable Supply Chain, Group Decision Making, Analytics for Social Good

Selected Publications

Hajiali, M., Teimoury, E., Rabiee, M., & Delen, D. (2022). An interactive decision support system for real-time ambulance relocation with priority guidelines. Decision Support Systems, 155, 113712.

Jabbari, M., Sheikh, S., Rabiee, M., & Oztekin, A. (2022). A collaborative decision support system for multi-criteria automatic clustering. Decision Support Systems, 153, 113671.

Sheikh, S., Rabiee, M., Nasir, M., & Oztekin, A. (2022). An integrated decision support system for multi-target forecasting: A case study of energy load prediction for a solar-powered residential house. Computers & Industrial Engineering, 166, 107966.

Rabiee, M., Aslani, B., & Rezaei, J. (2021). A decision support system for detecting and handling biased decision-makers in multi criteria group decision-making problems. Expert Systems with Applications, 171, 114597.

Jafarian, A., Rabiee, M., & Tavana, M. (2020). A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties. International Journal of Production Economics, 228, 107852.

Rabiee, M., Zandieh, M., & Ramezani, P. (2012). Bi-objective partial flexible job shop scheduling problem: NSGA-II, NRGA, MOGA and PAES approaches. International Journal of Production Research, 50(24), 7327-7342.

Jolai, F., Rabiee, M., & Asefi, H. (2012). A novel hybrid meta-heuristic algorithm for a no-wait flexible flow shop scheduling problem with sequence dependent setup times. International Journal of Production Research, 50(24), 7447-7466.

Rabiee, M., Zandieh, M., & Jafarian, A. (2012). Scheduling of a no-wait two-machine flow shop with sequence-dependent setup times and probable rework using robust meta-heuristics. International Journal of Production Research, 50(24), 7428-7446.

Please visit the following link for a complete list of other publications:

https://scholar.google.com/citations?user=sy1Se5cAAAAJ&hl=en&oi=ao

Awards

Robin & Roger Best Teaching Award, University of Oregon (2021)

Robin & Roger Best Teaching Award, University of Oregon (2022)

Robin & Roger Best Research Award, University of Oregon (2022)