Research
Ph.D. students in Statistics & Data Science are mentored by world-renowned faculty and conduct research that advances statistical methods, solves complex problems, and drives innovation.
Research in our department offers an exciting, dynamic environment where Ph.D. students engage in cutting-edge research that tackles complex challenges. What sets us apart is our strong interdisciplinary focus—you’ll collaborate with leading experts both in our department and across the university in areas such as causal inference, statistical machine learning, computational finance, optimization and algorithms, and optimal transport.
Ph.D. students dive into research right from the start, spending their first semester exploring faculty research areas and identifying potential projects for the Advanced Data Analysis (ADA) Project—a year-long collaborative research experience. After completing the ADA and core coursework, students typically begin focused work on their thesis.
Three pillars of research in Stat & DS
Early Exposure
Ph.D. students begin engaging in research from the start of the program, working closely with faculty and exploring diverse research areas. This early immersion helps students build critical skills and identify potential research directions early in their academic journey.
Interdisciplinary Collaborations
Students have the opportunity to collaborate with experts across a range of disciplines, such as genetics, neuroscience, and finance. These collaborations allow students to apply statistical methods to complex problems in other fields, driving innovation and expanding the impact of their research.
Faculty Mentorship
Ph.D. students receive close mentorship from world-renowned faculty, who provide guidance in developing research ideas, navigating challenges, and advancing their careers. This one-on-one support ensures students are well-prepared to make significant contributions to the field.