Ph.D. in Operations Management

The goal of the doctoral program in Operations Management is to train researchers and future faculty to develop scientific solutions to the problems currently being faced by operations managers.

Operations Management covers a broad range of topics as found in:

• Online platforms and sharing economy
• Health care management
• Supply chain management
• Sustainable operations
• Service operations
• Omni-channel retail
• Global operations and strategy
• Inventory control
• Just-in-time manufacturing
• Revenue management
• Commodity and energy merchant operations
• Real options
• Innovative business models

Research

Faculty research interests range from quantitative modeling to empirical studies using tools from operations research, mathematical programming, applied stochastic processes, simulation, artificial intelligence, statistics, econometrics, and economics.

The Tepper School has a long tradition of outstanding doctoral education in all branches of management. The business school is strongly committed to manufacturing and operations management as evidenced by a strong MBA program in production and operations management (we have always been in the top two in major surveys) as well as an excellent Ph.D. program.

More generally, the Tepper School at Carnegie Mellon is committed to quantitative management research and has made innovative contributions leading to several Nobel Prizes in Economics, and the faculty in Operations Research have won the Frederick W. Lanchester Prize and the John Von Neumann Theory Prize (awarded by INFORMS).

Cross-Campus Collaboration

The Tepper School has close ties working with the Carnegie Mellon College of Engineering in topics including energy and green design and the School of Computer Science and Department of Mathematical Sciences in jointly administering the graduate program in Algorithms, Combinatorics and Optimization. The school partners with the CMU Robotics Institute in work involving artificial intelligence and the joint management of manufacturing and automation program. Interdisciplinary collaborations also include other schools and research centers across the CMU campus such as the Department of Statistics and the Heinz School of Public Policy and Management. Students have significant flexibility in conducting research with and taking classes from, faculty in these schools.

Interdisciplinary Approach

The Ph.D. program in Operations Management is small with an interdisciplinary outlook. Students benefit from strong quantitative training as well as close ties with industry. A broad range of core and elective courses provides the students with a business outlook that is uniquely possible. In fact, the breadth of research possibilities under one umbrella at our group is probably unmatched by any other Operations Management department in the country.

Specific Project Partnerships 

• Caterpillar
• IBM
• Amazon
• OrganJet
• EQT
• University of Pittsburgh Medical Center
• University of California, San Francisco Transplant Center
• Massachusetts General Hospital

Methodological Contributions

• Inventory Models
• Machine Learning
• Queueing Theory
• Stochastic Modeling and Optimization
• Mechanism Design
• Approximate Dynamic Programming
• Game Theory
• Queueing Games

Many of our students are very active in the Carnegie Mellon INFORMS Student Chapter.

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates.

Requirements

Ph.D. students in Operations Management must fulfill all of the general Tepper School Ph.D. requirements, in addition to any area specific requirements. 

A normal course load involves taking 108 units during the first two years, including core Operations Management courses.

Students with appropriate preparation prior to their entry to the program may choose to take the qualifying exams prior to the third semester, however, they must take the entire set of qualifiers in the Operations Management area of study.

Tracks

The OM PhD Program is organized into three tracks:

(I) Modeling and Methodology
(II) Modeling and Theoretical Analysis
(III) Modeling and Empirical Analysis 

The courses and qualifiers are organized according to these tracks, as illustrated in the following tables.

Qualifying Exams (Questions)