My research is focused on using methods in causal inference and machine learning and the vast amount of data available in health care to personalize and improve cancer control. Many important decisions about cancer control must be made in the absence of evidence from randomized trials, which may be impractical or too lengthy to provide a timely answer. In these cases, I apply rigorous methods to large observational databases (e.g., electronic health records) to provide the best available evidence to inform clinical decision-making and future trial design. I teach clinical data science at the Harvard Medical School and causal inference methodology at the Harvard T.H. Chan School of Public Health.