About
My goal is to understand what machine learning predictions have to offer for causal decision making about interventions. This includes using machine learning for causal inference research (for example, nuisance parameter estimation in semiparametric models), understanding how confounding affects the usefulness of machine learning predictions, and identifying cases where prediction or classification models are good surrogates for intervention effectiveness.
Research Areas
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We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work