Industrial Engineering (PhD)
The admission standards for the PhD program in industrial engineering are as follows:
- All admission applications for the program shall include:
- A completed graduate application for the Graduate School
- An application fee
- Results from the Graduate Record Examination (GRE)
- At least two letters of recommendation
- Statement of Purpose (include intended area of study and/or research interests)
- Official transcript(s) for all previous post-secondary coursework. All transcripts not in English must be certified as authentic and translated verbatim into English.
- The minimum requirement for admission is the baccalaureate degree or its equivalent from an accredited institution.
- The successful applicant will typically have an undergraduate grade point average of 3.00 or above (on a 4.00 scale).
- International students whose primary language is not English must show English language proficiency by either TOEFL/IELTS/Duolingo score or demonstration of a degree awarded from an acceptable English language institution. The successful applicant will typically have a TOEFL score of 80 or higher or overall IELTS score of 6.5 or higher or a Duolingo score of 105 or higher.
Normally, it is expected that the student would have completed a master's degree before being admitted to the PhD Program. However, qualified applicants may be admitted directly to the doctoral program after receiving a baccalaureate degree. Such post-baccalaureate degree students will be required to complete an additional 30 credit hours of graduate coursework approved by the department's Director of PhD program. Also, remedial work may be specified for those applicants who, in the opinion of the faculty, do not have a sufficient background.
The PhD program has three different focus areas available: Data Analytics & Operations Research (DA-OR), Human Factors (HF), and Advanced Manufacturing (AM). The minimum curricular requirements for each focus area in the doctoral program are:
|Approved Master’s Level Coursework 1||30|
|Core Courses (Select two courses from a focus area below)||6|
|Technical Electives 2||9|
|IE 700||Dissertation Research in Industrial Engineering||9|
|Minimum Total Hours||54|
Master's level coursework must be approved by the Department.
Non-IE Electives must be approved by the department.
Data Analytics & Operations Research
|IE 610||Foundations of Optimization I||3|
|IE 662||Predictive Analytics for Decision Making I||3|
|IE 663: Predictive Analytics for Decision Making II||3|
|IE 694||Advanced Topics in IE (Algorithms for Combinatorial Optimization OR Stochastic Modeling)||3|
|IE 581||Advanced Topics in Human Factors Engineering||3|
|IE 585||Usability Engineering||3|
|IE 694||Advanced Topics in IE (Quality of Care and Patient Safety)||3|
|IE 694||Advanced Topics in IE (Health IT and Clinician Support)||3|
|IE 563||Experimental Design in Engineering||3|
|IE 600||Additive Manufacturing Processes||3|
|IE 601||Additive Manufacturing Structure Design||3|