I'm an academic (bio)statistician. My 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 organize the NSH Lab (pronounced like "niche"), a statistical science research group focused on developing novel theory, methods, algorithms, and open-source software for causal-analytic and statistical learning techniques. Work in my group is inspired directly by and tied to data-driven, real-world 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.