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Industrial and Systems Engineering

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Ph.D. in ISyE

The Industrial & Systems Engineering graduate program offers a PhD in ISyE (there are no "tracks" for the PhD). Exceptional students may apply directly to the PhD program without a prior MS.

How to Apply

Core Course Requirements

All PhD students take 4 out of the 5 core courses listed below. Two out of these must be IE 8521 and IE 8532, or qualifying replacements. Students may replace core courses with more advanced courses if they have already taken the equivalent of the core course elsewhere. A list of acceptable replacements is shown below (possible replacement courses are indented).

IE 8521 Optimization

IE 8531 Discrete Optimization
IE 8534 Advanced Topics in Operations Research

IE 8532 Stochastic Processes and Queueing Systems

IE 8533 Advanced Stochastic Processes and Queueing Systems
IE 8534 Advanced Topics in Operations Research

IE 5551 Production and Inventory Control

IE 8552 Advanced Topics in Production, Inventory, and Distribution Systems

IE 5545 Decision Analysis

IE 5511 Human Factors and Work Analysis

IE 8538 Advanced Topics in Information Systems
IE 8541 Decision Support Systems

Sample Program of Study for Ph.D. in ISyE

This program assumes full-time enrollment status and no prior background in ISyE. Students who are combining work and study may reduce the number of courses taken each semester. Students with a MS in ISyE from a recognized institution can transfer credits and shorten their program of study. There is no limit on the number of credits that may be transferred. Transfers require recommendation by the Advisor and approval by the DGS.

Year 1, Fall Semester
IE8521 Optimization
IE8532 Stochastic Processes and Queueing Systems
Elective from Math, CS, Statistics, or Economics (see list below)
IE8773 Graduate Seminar

Year 1, Spring Semester
IE5551 Production Planning and Inventory Control
IE5545 Decision Analysis
IE8xxx Elective or an Elective from Math, CS, Statistics, or Economics (see list below)
IE8774 Graduate Seminar

Students are advised to complete about 26 credits in the first year. Students should prepare to take the qualifying exam in the fall semester of the second year.

Year 2, Fall Semester
IE8xxx Elective
Elective from Math, CS, Statistics, or Economics (see list below)
Elective from Math, CS, Statistics, or Economics (see list below)

Year 2, Spring Semester
IE8xxx Elective
Elective from Math, CS, Statistics, or Economics (see list below)
Elective from Math, CS, Statistics, or Economics (see list below)

Students should plan to complete all course credits (minimum 44, including 12 non-major) by the end of second year. They should simultaneously work to develop a thesis proposal and take the preliminary exam in the fall semester of their third year. Years 3 and 4 should be devoted entirely to thesis research, with graduation planned sometime in year 4 or 5 depending on progress.

ISyE PhD students should select electives in consultation with their advisor and/or the Director of Graduate Studies. The courses listed below are suitable as electives. Many other choices are possible (subject to advisor/DGS approval), depending upon individual goals and interests.

Computer Science Electives for ISyE Ph.D. Students:
CSci 5304 Matrix Theory
CSci 5421 Advanced Algorithms and Data Structures
CSci 5521 Introduction to Machine Learning
CSci 5523 Introduction to Data Mining
CSci 5525 Machine Learning

Economics Electives for ISyE Ph.D. Students:
Econ 8001-2-3-4 Microeconomic Analysis
Econ 8117-8 Non-cooperative Game Theory
Econ 8119 Cooperative Game Theory

Math Electives for ISyE Ph.D. Students:
Math 5615-6H Introduction to Analysis I, II
Math 5485-6 Introduction to Numerical Methods I, II
Math 5654 Prediction and Filtering
Math 8601-2 Real Analysis I, II (for advanced students)
Math 8651-2 Theory of Probability Including Measure Theory (for advanced students)

Statistics Electives for ISyE Ph.D. Students:
Stat 5302 Applied Regression Analysis
Stat 5303 Designing Experiments
Stat 5401 Applied Multivariate Methods
Stat 8101-2 Theory of Statistics 1, 2
Stat 8501 Introduction to Stochastic Processes with Applications


For More Information

Please contact Dr. William Cooper.

 

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