Overview
We offer a Ph.D. curriculum that integrates the foundations of computation, data engineering, data modeling, theory, data policy, and ethics. The program generates graduates that are talented data handlers, expert modelers, competent theorists, and engaged, collaborative scientists. We designed the Ph.D. curriculum around four Domains of Data Science:
- Analytics (statistical and machine learning, stochastic modeling, decision making)
- Design (human-computer interaction, data engineering, visualization, networks)
- Systems (software and hardware, cloud computing, high performance computing)
- Values (privacy, ethics, governance, society)
Pathway to the degree
Students begin with coursework to establish a common language and acquire a broad knowledge of the foundations of data science. Students then transition into research by focusing in an area of data science or research topic. There are four milestones to earning the degree:
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Completion of Core courses
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Successful completion of the qualifying exam
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Successful dissertation proposal
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Successful defense of dissertation research
Coursework
Core Courses
These are required 7000-level courses that all students must successfully pass with a grade of B or better. The courses span all four domains of data science.
Recommended Courses
Before enrolling in Core classes, students may enroll in preparatory, foundation-level courses. Students are encouraged to complete the research methods course in preparation for the qualifying exam. Students may consult with the director of the PhD program or their academic advisor for individualized advice on the timing and preparation for the Core classes.
Elective Courses
In addition to the Core courses, there are electives for deeper specialization within the different domains or for research experiences. For example, those specializing in analytics may enroll in electives such as Bayesian machine learning, reinforcement learning, or deep learning. There are electives in networks and human-computer interaction for those in the design space.
View the current list of course offerings.
Research
After completing the Core courses, students continue with a mixture of research hours and elective course credits.
Qualifying Exam
After completing the Core courses, the next milestone is completing the qualifying exam. The qualifying exam is both a written and oral exam to assess the research readiness of PhD candidates. The exam is administered by a qualifying committee of three faculty members, including the student's faculty advisor. The exam covers topics proposed by the student and vetted by the qualifying committee.
Dissertation Proposal
Successful completion of the qualifying exam marks the start of the research phase. The student will form a dissertation committee of 4 faculty, including a research advisor. After crafting a research proposal, the student will present the plan to the committee.
Dissertation Defense
During the research phase, the student will meet weekly with the research advisor and twice yearly with the dissertation committee. Upon successful execution of the dissertation proposal, the student will present the research to the dissertation committee and the campus community. The PhD in data science is a research focused degree. Students are expected to generate new knowledge and push the boundaries of data science in their particular domain of choice, as well as demonstrate the impact of, and need for, these ideas in comprehensive application.
Community
Data science is a rapidly changing field. Our students are encouraged to actively engage with others in the research community through national and international conference attendance and participation in professional organizations. Students are required to attend school-wide seminars and conferences. See examples of conference session topics here and here.
Funding
Doctoral students receive financial support from the School of Data Science for the duration of their enrollment in the program, pending satisfactory completion of requirements and progression through the program. Tuition and fees are set annually by the University of Virginia Board of Visitors in early spring.