I'm an academic (bio)statistician whose work sits at the interface of causal inference, de-biased and/or targeted machine learning, semi-parametric estimation, statistical machine learning, and computational statistics.
- I currently direct the NSH Lab (pronounced like "niche"), a (bio)statistical science research group that focuses on developing theory, methods, algorithms, and open-source software tools for novel causal-analytic and statistical learning techniques, often inspired directly by open questions in the biomedical and public health sciences.
- A while ago, I co-created and served as a core developer for the TLverse project, an open-source software ecosystem of R packages for Targeted Learning; the project includes an open-source handbook to guide implementation of the techniques. The TLverse project is part of the ICTML Project, a scalable platform for machine learning and causal inference.