University of Oklahoma, Norman, OK
School of Industrial and Systems Engineering
Center for Cyber-Physical-Social Systems, Risk-Based Systems Analytics Laboratory
Post-Doctoral Scholar, in collaboration with: Dr. Kash Barker, Dr. Andrés González , and Dr. Shima Mohebbi, 2018-present

  • Developing dynamic work crew routing problem for infrastructure network restoration under incomplete and stochastic information.
  • Developing optimization models for critical infrastructure network damage assessment using UAVs.

University of Oklahoma, Norman, OK
School of Industrial and Systems Engineering
Risk-Based Systems Analytics Laboratory
Graduate Research Assistant, Advisor: Kash Barker, 2014 – 2018

  • Developed optimization models to enhance the resilience capacity of infrastructure networks. Particular innovations include: integrated vehicle routing formulation for restoration work crew services, multi-objective formulations to balance adaptive and restorative capacities, formulations for complete and proportional recovery.
  • Applied formulations to French and US electric power networks, as well as to general scale-free and small-world networks.
  • Collaborated on projects with researchers from ETH-Zurich and Vanderbilt University (funded by the U.S. National Science Foundation).
  • Developed a novel local search heuristic algorithm for work crew routing for critical infrastructure restoration

University of Cincinnati, Cincinnati, OH
Carl H. Lindner College of Business
Visiting Student Scholar, Mentor: Craig Froehle, 2015

  • Studied hourly emergency room patient arrival data, including cleansing noisy and inhomogeneous data.
  • Proposed a new extension of the Kalman Filter to a multivariate autoregressive time series model to predict patient arrivals.

University of Tehran, Tehran, Iran
Department of Industrial and Systems Engineering
Graduate Research Assistant, Advisor: Reza Tavakoli-Moghadam, 2011 – 2013

  • Extended the basic time window vehicle routing problem to account for traffic flow on the route, the sequence of demand nodes assigned to each vehicle, and queuing-driven estimates of waiting time and traffic flow.
  • Conducted data gathering and cleansing for the simulated data sets.
  • Developed a multi-objective imperialist competitive algorithm to compute the upper bound on the optimal solution.
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