U-M Industrial and Operations Engineering faculty and students create new tools and methods to extend the frontier of what is possible in our field. This work relates to a range of methodologies including Data Analytics, Human Systems Integration, Optimization, and Stochastic Systems.

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. 


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.