Ph.D. Program Requirements

Page Updated August 2014

(DRAFT: To be approved at the first faculty meeting in Fall 2014)

This page outlines the general requirements for completing a doctor of philosophy (Ph.D.) degree in the Department of Industrial and Systems Engineering (ISE). A summary of the steps is provided below, followed by more details in the remaining sections.

  1. Complete a set of common core courses.
  2. Declare a field of concentration within ISE and complete the Ph.D. qualifying exam.
  3. Pass a formal review conducted by the faculty following completion of the first two requirements.
  4. Complete the additional course requirements associated with field of concentration.
  5. Form a dissertation committee, propose a dissertation topic, and successfully defend this proposal to the committee.
  6. Successfully complete a general exam conducted by the dissertation committee consisting of written and oral parts.
  7. Successfully pass all annual progress reviews.
  8. Complete and successfully defend a doctoral dissertation.
  9. 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
ISE 406Introduction to Mathematical Optimization (3)
ISE 496Convex Analysis and Optimization (3)
One of the following courses approved by the Ph.D. program coordinator. EitherMath 310 Random Processes and Applications (3) OR
ISE 418 Integer Programming (3)


Spring Semester Course Title
ISE 417Nonlinear Optimization (3)
ISE 429Stochastic Models and Applications (3)
One additional course in the field of concentration.


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 the Department of 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 an area of concentration, which will be one of either

  • Optimization
    • Convex and Conic Optimization
    • Discrete Optimization and Integer Programming
    • Nonlinear Optimization
    • Numerical Methods of Optimization and Software
    • Optimization Methods for Learning
    • Stochastic and Robust Optimization
  • Applied Probability and Statistics
    • Queueing Networks
    • Simulation
    • Stochastic Processes
  • Applied Operations Research
    • Financial Optimization
    • Healthcare Systems
    • Scheduling
    • Smart Grids and Applications in Energy
    • Supply Chains

Core course requirements associated with each of these fields of study are discussed in Section V below. Additional custom-designed programs in applied or theoretical fields are also permissible with approval.

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

  1. Test the student's knowledge and strength in basic topics of Industrial and System Engineering.
  2. Assess the student's ability to conduct original research.
  3. Assess the student's ability to communicate, both orally and in writing.
  4. Test the student's ability to use the material from the core courses taken during the first year.

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 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:

  1. Evaluation of grades.
  2. Evaluation of qualifier exam results (if applicable).
  3. 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:

  • Six core courses described in Section I.
  • Six additional 400-level courses with 4 from the list of their chosen area of concentration and at least 2 in another area list.

Students are also encourage to take relevant 400-level courses outside of the ISE department and these courses can stand in place of some of the six additional courses, with approval of PhD program coordinator or PhD advisor. The above minimal Ph.D. course requirements total 12 courses (36 credits). For students who enter Lehigh with a Master's degree, completion of the degree requires an additional 12 credits (via courses or dissertation), totaling 48 credit hours. Those entering without a Master's degree need to complete an additional 36 credits, totaling 72 credit hours. 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 Areas of Concentration


CORE (Minimum of 3 courses from the following list)

  • CSE 441 Advanced Algorithms
  • ISE 407 Computational Methods in Optimization
  • ISE 411 Graphs and Network Flows
  • ISE 414 Heuristic Methods in Combinatorial Optimization
  • ISE 416 Dynamic Programming
  • ISE 417 Nonlinear Optimization
  • ISE 418 Integer Programming
  • ISE 447 Financial Optimization
  • ISE 495 Optimization Methods in Machine Learning
  • ISE 495 Conic Optimization
  • Math 405 Partial Differential Equations I
Applied Probability and Statistics

CORE (Minimum of 3 courses from the following list)

  • ECO 415 Econometrics I
  • ECO 416 Econometrics II
  • ECO 461 Forecasting
  • ISE 404 Simulation
  • ISE 409 Time Series Analysis
  • ISE 410 Design of Experiments
  • ISE 439 Queueing Systems
  • Math 312 Statistical Computing and Applications
  • Math 334 Mathematical Statistics
  • Math 435 Functional Analysis I
  • Math 461 Topics in Mathematical Statistics
  • Math 462 Modern Nonparametric Methods in Statistics
  • Math 464 Advanced Stochastic Processes
  • Math 467 Financial Calculus I
  • Math 468 Financial Calculus II
Applied Operations Research

CORE (Minimum of 3 courses from the following list)

  • CSE 411 Advanced Programming Techniques
  • CSE 432 Object-Oriented Software Engineering
  • CSE 441 Advanced Algorithms
  • Math 405 Partial Differential Equations I
  • Math 467 Financial Calculus I
  • Math 468 Financial Calculus II
  • ISE 358 Game Theory
  • ISE 404 Simulation
  • ISE 407 Computational Methods in Optimization
  • ISE 409 Time Series Analysis
  • ISE 411 Graphs and Network Flows
  • ISE 412 Quantitative Models of Supply Chain Management
  • ISE 414 Heuristic Methods in Combinatorial Optimization
  • ISE 416 Dynamic Programming
  • ISE 419 Sequencing and Scheduling
  • ISE 424 Robotic Systems and Applications
  • ISE 425 Advanted Inventory Theory
  • ISE 439 Queueing Systems
  • ISE 447 Financial Optimization
  • ISE 458 Topics in Game Theory
  • ISE 495 Optimization Methods in Machine Learning
  • ISE 495 Data Mining

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