Entering the #2-ranked Industrial Engineering program in the nation means you’ll study next to the very best faculty and PhD students academia has to offer. Our PhD students have extensive interdisciplinary opportunities available with different engineering departments, Michigan Medicine and other U-M schools and colleges. These collaborations raise the impact of your research and ensure you’ll rise to the top of your chosen field. Applications: Business operations and analytics: All sectors of the modern economy rely on fundamental quantitative tools for analysis, prediction and optimization to leverage data for the purposes of improving decision-making. Energy and sustainability: Energy utilization and sustainability are linked through their influence on communities, climate change and economics. Health and human safety: Health and human safety involve many important decisions that affect people’s lives, including the management of expensive resources in health systems, complex clinical treatment decisions and the design of safe environments for people to live and work. Mobility and transportation networks: Mobility and transportation systems research use data-driven analytics, human-centered design principles, computer simulation models and experimental studies to design and utilize advanced automation technologies. Methodologies: Data analytics: Data science research uses principles from computation, machine learning, statistics, and mathematics, to develop methods to analyze data and gain insight and knowledge about underlying systems to improve decision making. Human systems integration: The domain of human systems integration is a multidisciplinary field of research that endeavors to extend knowledge about how people interact with technology. Optimization: Methodological research in optimization uses techniques of algebra, geometry, analysis and combinatorics to develop and analyze algorithms for fundamental optimization models having broad applicability. Stochastic systems: This area of research is concerned with systems that involve uncertainty. Unlike deterministic systems, a stochastic system does not always generate the same output for a given input.

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Doctor of Philosophy (Ph.D) in Industrial and Operations Engineering

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