Dr. Long’s research purposefully includes novel statistical and machine learning research and impactful biomedical research, each of which reinforces the other. Its thrust is to develop robust statistical and machine learning methods for advancing intelligent and equitable health and medicine. Specifically, he has developed methods for analysis of big health data (-omics, EHRs, and mHealth data), predictive modeling, missing data, causal inference, data privacy, data and algorithmic fairness, Bayesian methods and clinical trials. Dr. Long’s methodological research has been supported by the National Institutes of Health, the Patient-Centered Outcomes Research Institute, and the National Science Foundation.