Industrial Engineering & Operations Research

The Department of Industrial Engineering and Operations Research (IEOR) offers four graduate programs: a Master of Engineering (MEng), a Master of Science (MS), a Master of Analytics (MAnalytics), and a PhD. These programs have been developed to meet the needs of individuals with backgrounds in engineering or the mathematical sciences who wish to enhance their knowledge of the theory, development, and use of quantitative models for design, analysis, risk management, and decision-making. This knowledge applies to complex systems in the industrial, service, or public sectors, including energy systems, supply chains, healthcare systems, and financial systems. Students may concentrate on theoretical studies in preparation for doctoral-level research, or on applications of state-of-the-art techniques to real world problems.

Master of Engineering (MEng)

The MEng is a professional, full-time, accelerated professional master's degree program. Students learn advanced techniques in IEOR and skills that prepare them to lead teams in developing new engineering solutions: skills in managing complex projects, motivating people, and directing financial and operational matters.

Master of Science (MS)

The MS is a full-time technical master's degree program. Students focus on both the theory of IEOR techniques and the application of those techniques. The MS is a terminal degree, meaning that students enrolled in the MS program do not typically continue further into the IEOR PhD program. Participants in the program are self-funded; the Department of IEOR does not offer funding and students will not be eligible for ASE (academic student employment) appointments funded by the department.

Master of Analytics (MAnalytics)

The 11-month in-person Master of Analytics program trains students in data-driven analytical methods and tools for optimization, statistics, simulation, and risk management with relevant industry context so that the graduates are not only highly skilled in the latest tools and fluent with working with large data sets, but also are able to raise the right questions to develop innovative models and find creative solutions to rapidly changing business and industry challenges, and communicate and implement their solutions.

Doctor of Philosophy (PhD)

The paramount requirement of a doctoral degree is the successful completion of a thesis on a subject within Industrial Engineering and Operations Research. Research areas may include the investigation of the mathematical foundations of and computational methods for optimization or stochastic models, including risk analysis. Research also may be undertaken to develop methodologies for the design, planning, and/or control of systems in a variety of application domains, including supply chains, energy systems, healthcare systems, and financial systems.

1. A bachelor’s degree or recognized equivalent from an accredited institution;
2. A satisfactory scholastic average, usually a minimum grade-point average (GPA) of 3.0 (B) on a 4.0 scale; and
3. Enough undergraduate training to do graduate work in your chosen field.