Master’s program · Rossin College of Engineering
Master of Science in Optimization
The MS in Optimization at Lehigh University teaches you to design, analyze and put into practice the algorithms that solve problems across engineering and data science.
- Credits30
- Typical length1.5–2 years
- DeliveryOn campus, hybrid or fully online
- Degree awardedMaster of Science
- GRENeither accepted nor reviewed
On this page
Overview
What the Master of Science in Optimization is
Optimization is the mathematics and computation behind choosing the best option from many. The program is built for students whose plans include research in a university, government or industry setting, and for anyone who wants real depth in how decisions get computed.
You take several courses in optimization itself, from convex analysis, networks and graphs to dynamic programming, discrete, continuous and conic optimization, and quantum computing, then broaden your knowledge with other industrial and systems engineering courses. Applications reach across data science, machine learning, finance and numerical computing.
A 30-credit degree, typically 1.5–2 years of full-time study, delivered on campus, hybrid or fully online.
Research areas
Research on how to choose well at scale
Across all of its research areas, the department’s faculty and students take on some of the largest and most complex problems in engineering and data science: finding the best answer among astronomically many possibilities, planning under uncertainty, and extracting decisions from massive data. Master’s students can contribute through coursework, projects and optional thesis research.
Optimization Theory and Methods
Many of the hardest planning and design problems have more possible solutions than any computer could ever check one by one. Researchers in this area develop the mathematical theory and the algorithms that find excellent solutions anyway, and they extend those methods to a new kind of computer that works in quantum mechanical ways.
Focus topics: Mathematical Optimization, Quantum Computing Optimization.
Uncertainty and Complexity
The systems that matter most to industry and society are both complicated and unpredictable. This area builds models that describe random behavior, optimization methods that account for it, and ways to measure how much a result can be trusted.
Focus topics: Stochastic Models and Optimization, Uncertainty Quantification and Complex Systems.
Data and Applications
Learning from data is itself an optimization problem, and the methods behind modern machine learning draw heavily on optimization ideas. Work in this area connects those ideas to data science and to practical operations research problems that organizations face every day.
Focus topics: Data Science and Machine Learning, Applied Operations Research.
Curriculum
What you study
The degree requires 30 graduate credits in three parts: 12 credits chosen from a menu of core optimization courses, 9 further credits of 400-level ISE courses, and 9 credits of free electives that you shape around your goals. The Lehigh University Course Catalog is the official source for these requirements, which can change from year to year, so confirm your plan with your academic advisor.
- Core courses, 12 credits. Choose from Convex Analysis (ISE 401), Fundamentals of Optimization (ISE 406), Numerical Methods and Scientific Computing (ISE 407), Networks and Graphs (ISE 411), Optimization Under Uncertainty (ISE 415), Dynamic Programming (ISE 416), Continuous Optimization (ISE 417), Discrete Optimization (ISE 418), Quantum Computing Optimization (ISE 422), Optimization Models and Applications (ISE 426), Optimization Methods in Machine Learning (ISE 444), Financial Optimization (ISE 447), Optimization Algorithms and Software (ISE 455) and Conic Optimization (ISE 456).
- ISE courses, 9 credits. Take nine more credits of 400-level ISE coursework beyond the core courses.
- Free electives, 9 credits. Take nine credits of 300- and 400-level coursework. Nearly all 300- and 400-level ISE courses count, except ISE 300, ISE 304 and ISE 499. So do selected courses in data science, supply chain analytics and strategic supply management, healthcare operations management, and population health. Other courses can count with the permission of the ISE MS program director.
- Thesis option. Up to six elective credits can go to thesis research (ISE 490), culminating in a written thesis. A thesis is not required, and there is no comprehensive exam.
- Course-level rules. At least 24 of your 30 credits must be at the 300 and 400 level, with 18 of those at the 400 level. At least 18 credits must be in the major field, with 15 of them at the 400 level, and research or thesis registration can count toward the 400-level total. You need a B- or better in at least 18 credits of your program and in all 300-level courses in the major field, and courses graded C- or better count toward the degree. Courses with an ESLP or EAPC subject code, ENGR 441, ENGR 499, ENGR 492 and ENGR 496 do not count.
| Code | Course | What it covers |
|---|---|---|
| ISE 401 | Convex Analysis | Convex analysis, optimization and duality. |
| ISE 406 | Fundamentals of Optimization | Linear, discrete and convex optimization. |
| ISE 407 | Numerical Methods and Scientific Computing | Numerical analysis and scientific computing. |
| ISE 411 | Networks and Graphs | Network and graph models and algorithms. |
| ISE 415 | Optimization Under Uncertainty | Stochastic and robust optimization. |
| ISE 416 | Dynamic Programming | Dynamic programming for sequential decisions. |
| ISE 417 | Continuous Optimization | Nonlinear optimization theory and methods. |
| ISE 418 | Discrete Optimization | Discrete optimization theory and algorithms. |
| ISE 422 | Quantum Computing Optimization | Quantum computing for optimization problems. |
| ISE 426 | Optimization Models and Applications | Mathematical programming models and analysis. |
| ISE 444 | Optimization Methods in Machine Learning | Optimization methods for machine learning. |
| ISE 447 | Financial Optimization | Making optimal financial decisions under uncertainty. |
| ISE 455 | Optimization Algorithms and Software | Optimization algorithms and software. |
| ISE 456 | Conic Optimization | Conic optimization models, theory and algorithms. |
The Lehigh University Course Catalog is the official source for degree requirements, and requirements can change from year to year. Confirm your own plan against the catalog and with your academic advisor.
Careers
Where graduates work
Industrial and systems engineering alumni apply analytical skills in technology, finance and research.
Most of our alumni work in information technology, finance and life sciences, with others in education, manufacturing and consulting. Typical roles include machine learning engineer, applied scientist, lead data scientist, data science manager and software engineer. Others teach and research as assistant and associate professors, and many alumni move into senior leadership as directors and vice presidents.
Employers where our alumni most often work include:
- Amazon
- Meta
- Axtria
- EY
- JPMorgan Chase
Alumni also work at Johnson & Johnson, Deloitte, Air Products, KMK Consulting, Citi, Greenwich Biosciences, Intel, SAS and TikTok.
Based on current employers of Lehigh industrial and systems engineering alumni who graduated between 1996 and 2025. Class of 2025 master’s graduates across the Rossin College averaged $100,000 in starting salary.
Tuition and funding
What it costs, and what help is available
Base tuition for this 30-credit degree is $52,050.
- Qualified applicants are automatically considered for merit scholarships as high as 20% of tuition, with no separate application required.
- International students are considered on the same basis as domestic applicants.
How to apply
What a complete application needs
- Academic record
A GPA of 2.75 or equivalent. Through prior study or work experience, you should have a background in industrial engineering, computer science, mathematics, mechanical engineering, electrical engineering or a similar discipline.
- GRE
GRE scores are neither accepted nor reviewed.
- English proficiency
International applicants submit a TOEFL iBT, IELTS, Duolingo, Cambridge English or Pearson Test of English score that meets the College and University minimums shown in the table below.
- Application fee
$50, non-refundable.
- Deadlines
Decisions are made on a rolling basis, with deadlines of December 15 for a spring start and July 15 for a fall start.
| Test | Overall | Speaking | Writing | Reading | Listening |
|---|---|---|---|---|---|
| TOEFL iBT | 81 | 22 | 20 | 20 | 16 |
| IELTS | 6.5 | 6.5 | 6.0 | 6.5 | 6.0 |
| Duolingo | 125 | 125 | 120 | 125 | 110 |
| Cambridge English | 176 | 176 | 169 | 176 | 169 |
| Pearson Test of English | 68 | 53 or above on each band | |||
FAQ
Frequently asked questions
What is the MS in Optimization at Lehigh?
It is a 30-credit master’s degree for students who want a solid understanding of how to design, analyze and use optimization algorithms for problems that arise throughout engineering and data science. It is designed especially for students whose plans include research in an educational, governmental or industrial environment.
How many credits is the MS in Optimization?
30 credits: 12 credits of core optimization courses, 9 credits of 400-level ISE courses and 9 credits of free electives.
How long does the MS in Optimization take to complete?
The program typically takes 1.5 to 2 years.
Do I have to write a thesis or take a comprehensive exam?
No. Neither is required. If you want research experience, up to six of your elective credits can go to thesis research (ISE 490) that culminates in a written thesis.
What courses can I choose for the core?
You choose 12 credits from fourteen optimization courses, including Convex Analysis, Fundamentals of Optimization, Networks and Graphs, Optimization Under Uncertainty, Dynamic Programming, Continuous Optimization, Discrete Optimization, Quantum Computing Optimization, Optimization Methods in Machine Learning, Financial Optimization and Conic Optimization.
What other courses count toward the degree?
After the core, you take 9 more credits of 400-level ISE courses and 9 credits of free electives at the 300 and 400 level. Most ISE courses at those levels count, as do selected courses in data science, supply chain and business, healthcare operations, and population health. The ISE MS program director can permit other courses.
What are the admission requirements?
You need a GPA of 2.75 or equivalent and a background in industrial engineering, computer science, mathematics, mechanical engineering, electrical engineering or a similar discipline, gained through prior study or work experience.
Is the GRE required for the Master of Science in Optimization?
GRE scores are neither accepted nor reviewed for any Rossin College graduate program.
What English proficiency scores do international applicants need?
The program follows the College and University standards. Minimum overall scores are 81 on the TOEFL iBT, 6.5 on the IELTS, 125 on Duolingo, 176 on Cambridge English, and 68 on the Pearson Test of English. Each test also has minimum speaking, writing, reading and listening scores, listed in the application requirements section above.
When are applications due?
Decisions are made on a rolling basis, with deadlines of December 15 for a spring start and July 15 for a fall start.
How is the program delivered?
On campus, hybrid or fully online. Consult the program contact for the current term-by-term format.
What does it cost, and is funding available?
Base tuition is $52,050 for the 30-credit degree. Qualified applicants are automatically considered for merit scholarships as high as 20% of tuition, with no separate application required. International students are considered on the same basis as domestic applicants.
Which department offers this program?
The Department of Industrial and Systems Engineering.
What do graduates earn?
Class of 2025 master’s graduates across the Rossin College averaged $100,000 in starting salary.
How do I apply?
Apply through Lehigh’s graduate application. A complete application includes transcripts, a personal statement, a resume, letters of recommendation, English-proficiency scores where applicable, and a $50 application fee. Decisions are made on a rolling basis, with deadlines of December 15 for a spring start and July 15 for a fall start.
What elective courses can I choose from?
Electives are chosen with your advisor. Courses students can choose from include Accelerated Computing for Machine Learning, Introduction to Statistical Modeling, Statistical and Machine Learning, Ethics in Data Science, Strategic Supply Management, Supply Chain Analytics, Healthcare Operations Management, and Population Health Concepts and Methods, among others. The Lehigh course catalog carries the full list.
Contact
Talk to the program
Department of Industrial and Systems Engineering
Harold S. Mohler Laboratory, 200 West Packer Avenue, Bethlehem, PA 18015-1582
Department of Industrial and Systems Engineering »
General inquiries go to engineering@lehigh.edu.