Operations Management studies how firms organize their resources and recurring activities in order to be competitive in cost, price, responsiveness and quality. The field stresses quantitative techniques ranging from applied probability to optimization and game theory. Successful applicants will have strong technical and mathematical training, and we particularly encourage applicants with undergraduate degrees in mathematics, economics and/or engineering to apply at the USC Application Portal. A prior background in business is not required.

Research areas: Our faculty are interested in a wide variety of research questions; check their personal webpages for specific examples. Some indicative topics include:

• Revenue management and dynamic pricing
• Data-driven analytics
• Healthcare operations
• Market and auction design
• Sustainability
• Supply-chain and service management

Operations Management and operations research prize interdisciplinary thinking and approaches. Hence, high-quality research often leverages a range of methodologies and tools, including:

• Optimization (linear, nonlinear, combinatorial, data-driven)
• Game Theory
• Queuing Theory
• Stochastic Processes / Applied Probability
• Econometrics
• Machine Learning

High quality research can involve developing new theoretical tools in these areas, application driven case studies, or both.

Our statistics faculty are interested in both pushing the boundaries of theoretical knowledge in the field as well as applied areas. There are many interesting research projects at the intersection of statistics, computer science, econometrics, finance, and marketing. Selected topics include:

• Statistical machine learning
• High­dimensional data analysis
• Computational and statistical limits of "Big data" problems
• Structural learning (such as clustering, sparse recovery and network analysis)
• Multiple hypotheses testing, uncertainty assessment and inference problems
• Finance and econometrics
• Applications in genetics, neuroscience and health care

Cutting­edge research in these areas leverages and builds upon many mathematical tools including:

• Functional data analysis
• Graphical models and iterative algorithms
• Optimization

The DSO Ph.D. program is research-focused, collegial, supportive and highly interactive. Ph.D. students are viewed as “junior colleagues” and are encouraged to become involved in academic research with faculty early in their doctoral studies through the following programs and initiatives:

• Low student-to-faculty ratio coupled with the faculty's "open-door" policy leading to frequent and meaningful collaborations. Unlike many other PhD programs, successful students often collaborate with several different faculty members, both in operations and statistics, throughout their PhD. Successful students typically co-author several papers with faculty members, which are often published in top peer-reviewed journals in the field.
• Presentations by invited faculty from around the world as part of a regular seminar provide an opportunity for students to experience the breadth of the field and meet renowned scholars. Click here for more information.
• Internal brown-bag seminars and colloquia with other research-oriented universities in Southern California

Research Environment

The structure of the Ph.D. program permits great flexibility, allowing custom-tailored courses of study emphasizing all areas of specialization within the department. In addition to our own faculty, students typically draw on the distinguished faculty and outstanding resources available throughout the University, most notably in economics, mathematics, industrial and systems engineering, computer science, and the Information Sciences Institute. The Center for Global Supply Chain Management(GSCM) and the Institute for Communication Technology Management (CTM) are also key resources to this program.

Recognized Research Authorities

The Operations Management faculty have served as senior editors and associate editors of premier management journals, including:

• Management Science
• Manufacturing and Service Operations Management
• Naval Research and Logistics
• Operations Research
• Production and Operations Management

Faculty Honors

• Fellows, Production and Operations Management Society
• National Science Foundation Grants

Learn More: Explore the Data Sciences and Operations department to learn more about current research and faculty activities.

Research Environment

Research by the statistics faculty emphasizes developing new methodology that grows out of business and public policy applications. In methodology, the statistics faculty's research covers a wide segment of the field of statistics including Bayes and empirical Bayes methods, data mining, categorical data, hidden state Markov models, classification rules, clustering methods, econometric and psychometric models, and general linear models. Applications include finance, marketing, real estate, health policy, defense system testing, computer science and discrimination in employment and in sentencing.

Recognized Research Authorities

The Statistics faculty members are among the leading authorities of Business Statistics worldwide. One senior Statistics faculty member plays a leading role in the profession's advice to the federal government on statistical methodology. In addition, Statistics faculty members have served as senior editors and associate editors of premier management journals, including:

• Annals of Statistics
• Journal of the American Statistical Association
• The Econometrics Journal
• Journal of Multivariate Analysis
• Statistica Sinica

Faculty Honors

• Fellow of the American Statistical Association; Noether Young Scholar Award; National Science Foundation Grants; National Science Foundation CAREER Award

Learn More: Explore the Statistics group to learn more about current research and faculty activities.

Sample Course Schedule

Fall:

• DSO 671: Inventory Models and Supply Chain Management
• GSBA 602: Selected Issues in Economic Theory
• ISE 631: Linear Programming
• Elective (1)

Spring:

• ISE 538: Elements of Stochastic Processes (or MATH 505B: Applied Probability)
• DSO 677: Dynamic Programming and Markov Decision Processes
• ISE 630: Foundations of Optimization
• GSBA 604: Regression and Generalized Linear Models for Business

Summer:

• BUCO 634: Communication for Doctoral Students: Conference Papers and Presentations
• Summer Research Paper

Research Development
Beginning in the first semester, students will apprentice with a faculty mentor to learn research fundamentals. Typically students are assigned to a new mentor each semester in the first year. During the summer following the first year in the program, students are expected to research and complete a Summer Research Paper.

Screening Examination
In addition to the papers and examinations assigned in their first-year courses, a screening process will occur in May at the end of the first year. This process will include a review of each student's grades, an analysis of competence in written communications and a written exam based on the material covered during the first year. The results of the examination help the faculty determine students’ developmental needs and fitness to continue in the program.

Sample Course Schedule

Fall:

• DSO 670: Current Research in Operations management
• 3 electives

Spring:

• DSO 674: Queuing and Stochastic Networks
• ISE 632: Metwork Flows and Combinatorial Optimization
• 2 electives

Summer:

• BUCO 633: Communication for Doctoral Students: Foundations of Academic Writing
• BUCO 637: Communication for Doctoral Students: Succeeding as a Teacher

Sample Course Schedule

• Independent Dissertation Preparation (2)

Research Development
At this stage in the program, the relationships Ph.D. candidates have developed through the research apprentices often lead to collaborative research projects. Ph.D. candidates continue to apprentice faculty with increasing responsibility. They also begin work on their dissertations and are expected to have an approved dissertation proposal before the start of the fourth year.

Teaching Development
Ph.D. candidates begin developing teaching skills by serving as a teaching assistant for one or two classes and engaging in teaching skills workshops.

Qualifying Exam
The examination qualifying a student for candidacy for the Ph.D. degree is partly written and partly oral, designed, at least in part, to test the student’s fitness to undertake independent research. After successful completion of the qualifying exams, the student is admitted to candidacy.

Sample Course Schedule

• Independent Dissertation Preparation (2)

Research Development
Research is the primary activity in the fourth year and beyond. Faculty view Ph.D. candidates as “junior colleagues” and partner to write and present papers.

Teaching Development
Ph.D. candidates co-teach one course with a faculty member.

Dissertation Defense & Submission
The dissertation is the culminating work of a student’s independent research. In the fifth year of the program, students complete, defend and submit the dissertation. This is the last step to earn the Ph.D. degree.

Sample Course Schedule

Fall:

• MATH 541B Introduction to Mathematical Statistics
• ISE 630 Foundations of Optimization
• MATH 507A Theory of Probability or MATH 505a Applied Probability
• 1 elective

Spring:

• MATH 505b Applied Probability or Math 506 Stochastic Processes
• DSO 607 High-Dimensional Statistics and Big Data Problems
• GSBA 604 Regression and Generalized Linear Models for Business
• MATH 541A Introduction to Mathematical Statistics 1 elective

Summer:

• BUCO 634
• Summer Research Paper

Research Development
Beginning in the first semester, students will apprentice with a faculty mentor to learn research fundamentals. Typically students are assigned to a new mentor each semester in the first year. In the summer following the first year in the program, students research and complete a Summer Research Paper.

Screening Examination
In addition to the papers and examinations assigned in their first-year courses, a screening process will occur in May at the end of the first year. This process will include a review of each student's grades, an analysis of competence in written communications and a written exam based on the material covered during the first year. The results of the examination help the faculty determine students’ developmental needs and fitness to continue in the program.

Sample Course Schedule

Fall:

• MATH 541B Introduction to Mathematical Statistics or MATH 547 Methods of Statistical Inference (if already taken 541B)
• 3 electives (including a graduate level class in a selected business area)

Spring:

• DSO 599 Special Topics Class
• 3 electives

Summer:

• BUCO 633: Communication for Doctoral Students: Foundations of Academic Writing
• BUCO 637: Communication for Doctoral Students: Succeeding as a Teacher

Sample Course Schedule

• Independent Dissertation Preparation (2)

Research Development
At this stage in the program, the relationships Ph.D. candidates have developed through the research apprentices often lead to collaborative research projects. Ph.D. candidates continue to apprentice faculty with increasing responsibility. They also begin work on their dissertations.

Teaching Development
Ph.D. candidates begin developing teaching skills by serving as a teaching assistant for one or two classes and engaging in teaching skills workshops.

Qualifying Exam
Students are required to complete the qualifying exam by November 1 of their third year. The examination qualifying a student for candidacy for the Ph.D. degree is partly written and partly oral, designed, at least in part, to test the student’s fitness to undertake independent research. After successful completion of the qualifying exams, the student is admitted to candidacy.

Sample Course Schedule

• Independent Dissertation Preparation (2)

Research Development
Research is the primary activity in the fourth year and beyond. Faculty view Ph.D. candidates as “junior colleagues” and partner to write and present papers.

Teaching Development
Ph.D. candidates co-teach one course with a faculty member.

Dissertation Defense & Submission
The dissertation is the culminating work of a student’s independent research. In the fourth or fifth year of the program, students complete, defend and submit the dissertation. This is the last step to earn the Ph.D. degree.

Dissertation Defense & Submission
The dissertation is the culminating work of a student’s independent research. In the fifth year of the program, students complete, defend and submit the dissertation. This is the last step to earn the Ph.D. degree.