Affiliated Department or Office
BS Johns Hopkins University, Physics and Mathematics
PhD University of Michigan, Statistics

My research in applied statistics focuses on methods for causal inference using large, administrative datasets, primarily with applications in learning sciences and social sciences. I have developed and worked on methods combining machine learning with design-based analysis of randomized trials and matched observational studies, principal stratification and mediation analysis using log data from intelligent tutoring systems, and regression discontinuity designs. In my teaching and mentoring, I try to present good statistical practice as central to rigorous science, and I am looking forward to teaching, mentoring, and working alongside WPI students.