Gary Hettinger, PhD

I am an Assistant Professor in the Division of Biostatistics within the Department of Population Health at NYU Grossman School of Medicine.

My research centers on the development and application of statistical methods for causal inference, with a particular emphasis on comparative effectiveness and health policy evaluation. Currently, I am developing estimators for quasi-experimental designs to assess treatment effects using observational data involving real-world challenges such as continuous exposures, interference, and clustered or longitudinal data structures. My work frequently draws on semiparametric estimation theory to construct robust estimators that integrate flexible modeling approaches like machine learning into causal inference frameworks.

In addition to methodological research, I collaborate on applied projects in health policy, oncology, and predictive modeling, with a focus on evaluating interventions and supporting evidence-based decision-making in population health.