The Ph.D. in Data Science at SMU is distinctive because of its highly interdisciplinary nature.
Most existing Data Science Ph.D. programs are either housed in a single department, such as Statistics, Computer Science, Operations Management or Business Analytics; or they focus on a single disciplinary area of research, such as Business or Medicine.
The Data Science Ph.D. at SMU is housed in the Department of Statistics and Data Science, which belongs to three different academic units: The Dedman College of Humanities and Sciences; the Cox School of Business; and the Lyle School of Engineering. Faculty from all three of these schools and colleges participate in the program, and faculty outside of those academic units—such as the Meadows School of the Arts, the Dedman School of Law, and the Simmons School of Education and Human Development—can also offer courses and advise Ph.D. students.
The program’s core curriculum consists of courses in Computer Science, Operations Management, Statistics, and Data Science, and elective courses go beyond those disciplines to include Mathematics, Finance, Marketing, Education, Psychology, Chemistry, Game Design, Economics, and more. Student and faculty interest will continue to set directions for how the program evolves in the future.
Another distinctive feature are the research rotations that students engage in after having completed 4 semesters of coursework.
The goal of this program is to recognize that data science research can inform nearly every discipline at the university and beyond; and that the future of research and work in data science will not be limited to specific and restricted areas.