Data Sciences and Operations

Operations Management

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

Collegial, Supportive and Expansive

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

Faculty webpages can be found here.

Faculty Coordinator

Vishal Gupta, Associate Professor of DSO

Learn More

Learn more about Data Science and Operations program requirements, research, placements, and students.