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Master of Science in Operations Research and System Analytics

Program Overview

This program uniquely combines mathematical modeling, computer programming, data science, and business analytics to solve significant problems in a variety of domains. It provides hands-on experience through a required capstone project and is open to students with an undergraduate degree in any STEM field. The program is built for people with diverse backgrounds and offers a variety of electives to tailor to individual interests and skills. It is an applied operations research program with a computer science and artificial intelligence flavor.

Relevant Learning Outcomes

• Apply operations research models and methods to identify, formulate, and solve problems in engineering systems.
• Use principles of mathematical programming to make informed holistic decisions while being cognizant of their societal, economic, and environmental impact.
• Proficiency in scientific tools to efficiently operate systems with significant uncertainty and predict their performance.
• Perform descriptive, predictive, and prescriptive analytics using data-driven approaches and communicate the outcomes effectively.
• Integrate concepts from mathematics, programming, and engineering to design and optimize systems, analyze trade-offs, and interpret results for engineering practice.

Program Curriculum

Mathematical Background (2 courses)

• Linear Algebra and Applications (ELE 603)
• Introduction to Probabilistic Models (ELE 606)

Operations Research Topics (2 courses)

• Optimization Techniques (MAE 630)
• Stochastic Modeling and Applications (ECS 629)

Machine Learning Topics (1 course)

• Machine Learning Algorithms (CIS 662)

Electives (4 courses)

• Select courses from areas such as artificial intelligence, machine learning, engineering management, and industrial engineering.

Industrial Project Experience (1 course)

• Capstone project in operations research and system analytics (ECS 697)