Elnaz Kabir

Ph.D. Candidate

Department of Industrial & Operations Engineering,
University of Michigan

1205 Beal Avenue
Ann Arbor, MI 48109-2117, U.S.A
e-mail: ekabir@umich.edu 

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I am a Ph.D. candidate in Industrial & Operations Engineering at the University of Michigan and working under the advise of Prof. Seth Guikema. In addition to the PhD, I am partaking in the dual master’s program offered by the Department of Statistics at the University of Michigan

My research lies in the intersection of data and risk analytics, machine learning, optimization and natural hazards. My goal is to use statistical and machine learning theories, and optimization techniques to better understand and solve important problems related to weather-induced power outages. To be more specific, my recent focus is to develop (i) predictive models able to estimate power outages in advance of a severe weather event, and (ii) optimization models for requesting and assigning repair crews and devices to the hazardous districts. The results of these studies are currently used by utility personnel in order to make better decisions to reduce the risk of weather-events on the power system, and also to improve the resilience of this lifeline infrastructure system. Some of the techniques or methods I have been using in my researches are machine learning, unbalanced learning, Bayesian model averaging, robust and stochastic optimization. 

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