M.S. and Ph.D. students have the opportunity to graduate with concentrations in the following areas:

Data Analytics

Data analytics is the science of analyzing data to discover some relevant information that provides descriptive insights into the past and facilitates accurate forecasting of future trends. The information can further be leveraged to support decision-making processes, which aim to identify the best action under uncertain future outcomes.

View the requirements for the Data Analytics concentration (PDF)

Decision Analysis

Decision analysis is a theory and body of professional practice to illuminate the analysis of complex decision problems. Often these decisions are complex because of uncertainty, but decision analysis also includes the representation and modeling of complex preferences/tradeoffs and complex alternatives.

View the requirements for the Decision Analysis concentration (PDF)


Optimization is broadly focused on the identification of the best solution to complex decision problems that can be represented mathematically. It deals with problems that are complex because there are a large number of alternatives (e.g., scheduling). In some cases, uncertainty is also included and optimization may seek to identify alternatives that perform well across a range of uncertain scenarios.

View the requirements for the Optimization concentration (PDF)

Stochastic Systems

Stochastic systems is focused on the modeling and analysis of systems whose behavior or performance is governed by an underlying probabilistic process. Often, we seek to model this system so that we can determine how to influence the system to perform in a more efficient or beneficial way.

View the requirements for the Stochastic Systems concentration (PDF)