M.Sc. and Ph.D., Industrial and Systems Engineering, University of Tennessee
M.Sc., Statistics, University of Tennessee
Post Doc., Civil Engineering, University of South Florida
Shima Mohebbi is an assistant professor in the School of Industrial and Systems Engineering (ISE) at the University of Oklahoma. She received her PhD in ISE, and her second Master’s degree in Statistics from the University of Tennessee, and achieved several academic recognitions and fellowships during her graduate studies. She joined the Department of Civil and Environmental Engineering at the University of South Florida for her postdoctoral studies in 2015. She was also a visiting scholar at the University of Exeter’s center for water systems, UK, in summer 2017.
Dr. Mohebbi’s research interests include algorithmic game theory, simulation-optimization models, and high dimensional data mining. She serves as an associate editor for International Journal of Applied Logistics (IGI-Global) and has collaborated across disciplines including civil engineering, computer science, environmental anthropology, and nursing. Her collaborative research has been supported by NSF.
2015 IISE’s Nominee, New Faces of Engineering Award, DiscoverE
2015 Chad/Ann Blair Holliday Fellowship, Department of Industrial and Systems Engineering, University of Tennessee, Knoxville
2014 Gilbreth Memorial Fellowship Finalist, Institute of Industrial and Systems Engineers (IISE)
2014 Outstanding Graduate Student, College of Engineering, University of Tennessee, Knoxville
2013 Chancellor’s Extraordinary Professional Promise Award, University of Tennessee, Knoxville
Methodology: Algorithmic game theory, Simulation modeling, Stochastic Programming, High dimensional data mining
Application: Resilient infrastructure systems, Sustainable urban water systems, Smart cities, Healthcare systems
Integrative Decision Making Framework to Enhance the Resiliency of Interdependent Critical Infrastructures
This research project aims to understand the effects of physical-based (primarily co-location), virtual-based (primarily information), and socioeconomic-based (primarily resource management) interdependencies on the resiliency of critical infrastructures, focusing on water, transportation, and cyber infrastructures. The proposed framework uses hybrid simulation models to integrate outcomes from different methods including: multi-layer network optimization, infrastructure prognostic and health management, and consensus analysis and Monte Carlo simulation of decision making outcomes (focus: organizational aspects of infrastructures).
Link: NSF Website
List of all publications: Google Scholar