Program Statistics
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Last Updated: August 28, 2026
Industrial Engineering and Management Sciences
Overview
Degree Types: PhD
The Industrial Engineering and Management Sciences PhD Program produces researchers who combine strength in core methodologies of operations research (e.g., optimization, stochastic modeling and simulation, statistics, and data analytics) with the ability to apply them to yield practical benefits in solving problems that are important in the real world. The program offers students the opportunity to use skills in computing, mathematical analysis and modeling, and economics to produce research that helps to improve the efficiency, quality, and the potential of organizations to fulfill their missions. The program prepares students for research-based careers in industry, academia, non-profit, and government.
Areas of specialization include Analytics, Stochastic Analysis & Simulation, Optimization, Financial Engineering, Logistics & Operations, Healthcare Engineering, Applied Statistics &Statistical Learning, and Computational Social Science.
Applicants must have a bachelor's or master's degree in a relevant discipline, but need not have a degree in industrial engineering. The program has attracted students of applied mathematics, computer science, economics, finance, mathematics, physics, statistics, and most other engineering disciplines.
Additional resources:
Program Contact
Contact
Brittany Jasin
Graduate Program Assistant
847-491-4394
Degree Requirements
Degree Requirements
The following requirements are in addition to, or further elaborate upon, those requirements outlined in The Graduate School Policy Guide.
Master's
Those students enrolled in the IEMS PhD program receive the MS as they progress toward the PhD. For students who are progressing to the PhD, the master's degree is generally awarded upon completion of the following:
Minimum GPA 3.0
Total Units Required: 12
| Course | Title |
|---|---|
| First Year Core Courses | |
| IEMS 401-0 | Applied Mathematical Statistics |
| IEMS 450-1 | Mathematical Optimization I |
| IEMS 460-1 | Stochastic Processes I |
| Two of the Following: | |
| IEMS 402-0 | Statistical Learning |
| IEMS 450-2 | Mathematical Optimization II |
| IEMS 460-2 | Stochastic Processes II |
| IEMS 435-0 | Stochastic Simulation |
| 7 other courses for credit | |
Other MS Degree Requirements
- Successful performance on examination of a research paper at end of first year.
PhD
Total Units Required: 15
| Course | Title |
|---|---|
| First Year Core Courses | |
| IEMS 401-0 | Applied Mathematical Statistics |
| IEMS 450-1 | Mathematical Optimization I |
| IEMS 460-1 | Stochastic Processes I |
| Two Research-Based Courses, IEMS 499 Independent Study | |
| Two of the Following: | |
| IEMS 402-0 | Statistical Learning |
| IEMS 450-2 | Mathematical Optimization II |
| IEMS 460-2 | Stochastic Processes II |
| IEMS 435-0 | Stochastic Simulation |
| Five Other Courses, taken from the list of advanced courses, application courses, and approved elective courses | |
Other PhD Degree Requirements
- Examinations: candidacy examination on a research paper at end of first year.
- Prospectus: Initial part of dissertation research, to be completed by the end of the third year in the program.
- PhD Dissertation: based on independent research.
- Final Evaluations: oral defense of dissertation.
- Other: at least one experience as an instructor or teaching assistant; satisfy TGS English proficiency requirement.