Ph.D. Program Requirements
Page Updated August 2012
The general requirements for completing a doctor of philosophy (Ph.D.) degree in the Department of Industrial and Systems Engineering (ISE). A basic outline of the steps is provided below, followed by more details in the remaining sections.
- Complete a set of common core courses.
- Declare a primary and a secondary field of study within ISE and complete the Ph.D qualifying exam in these areas.
- Pass a formal review conducted by the faculty following completion of the first two requirements.
- Complete the additional course requirements associated with major and minor fields of study.
- Form a dissertation committee, propose a dissertation topic, and successfully defend this proposal to the committee.
- Successfully complete a general exam conducted by the dissertation committee consisting of written and oral parts.
- Successfully pass all annual progress reviews.
- Complete and successfully defend a doctoral dissertation.
- Satisfy any additional Ph.D. degree requirements specified by the P.C. Rossin College of Engineering and Applied Science (refer to Lehigh University Catalog).
I. Core Course Requirements
The core course requirements for all first-year students are as follows:
| Fall Semester | Course Title |
|---|---|
| IE 406 | Introduction to Mathematical Optimization (3) |
| One mathematics course approved by the Ph.D program coordinator. Either | Math 301 Principles of Analysis I (3) OR Math 3XX (3) OR Math 4XX (3) |
| One additional course | |
| Spring Semester | Course Title |
|---|---|
| IE 429 | Stochastic Models and Applications (3) |
| One mathematics course approved by the Ph.D program coordinator. Either | Math 338 Linear Models in Statistics (3) OR Math 3XX (3) OR Math 4XX (3) |
| One additional course | |
For core courses in ISE, any student who has already completed an equivalent course at another institution may fulfill the course requirement by successfully passing an examination by the instructor of the course in question. Note, however, that this does not reduce the required number of credit hours and the student will not receive formal credit for the course. For courses in Mathematics, a student may, with the permission of the Ph.D program coordinator, replace any core course with another course at the same level if sufficient evidence of having completed an equivalent course is presented.
II. Declaration of Fields and Course Requirements
At the end of the first year of study, each student must declare a methodological field of study, which will be one of either
- Optimization, or
- Applied Probability and Statistics
and an applied field of study, which may be one of either
- Financial Engineering
- Computational Engineering,
- Manufacturing, Production and Logistics, or
- A custom-designed program in another applied field (with approval of the Ph.D program coordinator).
Other custom-designed programs in applied fields are also permissible with approval. Core course requirements associated with each of these fields of study are discussed in Section V below.
III. Qualifying Exam
Immediately following final exams at the end of the first year, all Ph.D students must take the qualifying exam. The purpose of the exam is to
- Test the student’s knowledge of material from the core courses taken during the first year.
- Test the student’s knowledge in his/her chosen field of study.
- Assess the student’s ability to conduct original research.
- Assess the student’s ability to communicate, both orally and in writing.
Each student’s exam will be conducted by a panel consisting of three faculty members. Each member of the student’s panel will pose a research question to be studied during the two-week examination period. After the two-week period, the student will present a written report and oral presentation to the panelists, who will each assess the student’s performance using an evaluation form that will be made available to the student ahead of time on request. The results of the exam are either pass or fail. These results are only used as input to the annual review, described below.
NOTE: A student entering the Ph.D. program with only a B.S. degree may petition to delay their first qualifier exam until their third semester of study. This does not exempt them from a first year review. A student entering the Ph.D. program without a Master’s degree may petition to delay their first qualifying exam until the end of their third semester of study. This does not exempt them from a first-year review (see below). The timing of the qualifying exam for part-time students will be determined based on a customized program of study developed in consultation with the Ph.D program coordinator.
IV. Annual Reviews
First Year
At the end of the first year, every Ph.D. student will undergo a review consisting of:
- Evaluation of grades.
- Evaluation of qualifier exam results (if applicable).
- Other input as deemed relevant by the faculty.
The results of this first-year review are determined by vote of the faculty and may be either pass, conditional pass, or fail. A pass indicates that the student may continue into the second year of the program and should start to form a dissertation committee. A conditional pass indicates that the student may continue, subject to certain stated conditions being fulfilled. These conditions may include, but are not limited to, re-taking the qualifying exam, taking additional coursework, or achieving a minimum GPA during subsequent semesters. Failure of the first-year review will result in a student’s dismissal from the Ph.D program, after which the student may petition to transfer to an M.S. degree program in order to receive a degree before leaving the department.
In cases in which a student has arranged to delay the scheduling of the qualifying exam, is required to retake it, or has conditionally passed a prior review, a supplemental review will take place directly following any off-cycle offering of the qualifying exam or completion of a required conditional action. When the student feels that the conditional actions have been completed, he or she should notify the Ph.D program coordinator and request a supplemental review. The Ph.D program coordinator may also call for the supplemental review to take place as deemed appropriate. For part-time students whose exam date extends beyond the second year, annual reviews will be conducted by the faculty each year until the qualifying exam is passed successfully.
Subsequent Years
Following successful completion of the qualifying exam and successful fulfillment of conditions imposed as a result of the subsequent review, each student is required to identify a dissertation advisor, identify a dissertation topic, and form a dissertation committee to guide their further study. In each subsequent year, the student will be required to submit an annual report of progress to be reviewed by the committee who will pass on to the Ph.D program coordinator a brief summary of the committee’s assessment of the student’s progress.
It is expected that most students will present their dissertation proposal to their dissertation committee at its first meeting, which will also serve as the second annual review.
V. Additional Course Requirements
The overall Ph.D. course requirements include:
- Four core courses described in Section I.
- Three additional 400-level courses in the methodological field of study.
- Three 400-level courses in the applied field of study.
At least two 400-level courses must be taken outside of the ISE department. The above minimal Ph.D. course requirements total 10 courses (30 credits). For students who enter Lehigh with a Master’s degree, completion of the degree requires an additional 18 credits (via courses or dissertation), totaling 48 credit hours. Those entering without a Master’s degree need to complete an additional 42 credits, totaling 72 credit hours. Suggested acceptable courses for each methodological and application area are listed in the addenda. All course selections are subject to approval by the student’s academic advisor in consultation with the student’s dissertation committee.
Addendum A: Acceptable Courses in Methodological Areas
Optimization
CORE (Minimum of 3 courses from the following list)
- CSE 440 Graph Theory and Applications
- CSE 441 Advanced Algorithms
- IE 411 Networks and Graphs
- IE 414 Heuristic Methods in Combinatorial Optimization
- IE 416 Dynamic Programming
- IE 417 Nonlinear Optimization
- IE 418 Discrete Optimization
- IE 426 Optimization Models and Applications
- IE 447 Stochastic Programming and Financial Analysis
- IE 455 Optimization Algorithms and Software
- IE 495 Optimization Methods in Machine Learning
- IE 496 Numerical Methods for Optimal Control
Applied Probability and Statistics
CORE (Minimum of 3 courses from the following list)
- ECO 415 Econometrics
- ECO 416 Econometric Theory
- ECO 460 Time Series Analysis
- ECO 461 Forecasting
- IE 404 Simulation
- IE 409 Time Series Analysis
- IE 410 Design of Experiments
- IE 422 Measurement and Inspection Systems
- IE 439 Queueing Systems
- Math 312 Statistical Computing and Applications
- Math 334 Mathematical Statistics
- Math 461 Topics in Mathematical Statistics
- Math 462 Nonparametric Statistics
- Math 464 Advanced Stochastic Processes
Addendum B: Acceptable Courses in Application Areas
Financial Engineering
CORE (Minimum of 3 courses from the following list)
- ECO 416 Econometric Theory
- ECO 423 Real Options
- ECO 424 Advanced Numerical Methods
- ECO 447 Economics Analysis of Market Competition
- GBUS 413 Advanced Management Accounting
- GBUS 414 Financial Statement Analysis and Interpretation
- GBUS 419 Financial Management
- GBUS 420 Investments
- GBUS 422 Derivatives and Risk Management
- GBUS 424 Advanced Topics in Financial Management
- GBUS 473 International Finance
- IE 358 Game Theory
- IE 413 Advanced Engineering Economy and Replacement Analysis
- IE 447 Financial Optimization
- IE 458 Topics in Game Theory
- MATH 405 Partial Differential Equations
- MATH 435 Functional Analysis
- Math 467 Financial Calculus I
- Math 468 Financial Calculus II
Computational Engineering
CORE (Minimum of 3 courses from the following list)
- CSE 366 Object-Oriented Programming
- CSE 411 Advanced Programming Techniques
- CSE 412 Object-Oriented Programming
- CSE 432 Object-Oriented Software Engineering
- CSE 440 Graph Theory and Applications
- CSE 441 Advanced Algorithms
- IE 341 Data Communication Systems Analysis and Design
- IE 408 Management of Information Systems
- IE 438 Advanced Data Communication Systems Analysis and Design
- IE 439 Queueing Systems
- IE 455 Optimization Algorithms and Software
- IE 495 Data Mining
- IE 495 Optimization Methods in Machine Learning
- IE 496 Computational Methods in Optimization
- IE 496 Numerical Methods for Optimal Control
Manufacturing, Production and Logistics
CORE (Minimum of 3 courses from the following list)
- ECO 460 Time Series Analysis
- ECO 461 Forecasting
- IE 340 Production Engineering
- IE 404 Simulation
- IE 409 Time Series Analysis
- IE 412 Quantitative Models of Supply Chain Management
- IE 419 Sequencing and Scheduling
- IE 424 Robotic Systems and Applications
- IE 425 Inventory Management and Production Planning
- IE 443 Automation and Production Systems
- IE 445 Assembly Processes and Systems
- IE 446 Discrete Event Dynamic Systems
- IE 448 Industrial Control Systems for Manufacturing
- IE 451 Intelligent Manufacturing Systems
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