Dr. Tim Randolph is a statistician and mathematician who works with clinical research and public health scientists to analyze complex molecular data. For example, patterns of gene expression may be predictive of disease; groups of metabolites may be indicative of a drug’s success; or communities of gut bacteria may be associated with health. Dr. Randolph specializes both in applying appropriate statistical and machine-learning tools — and in developing his own methods — to help researchers understand how these varied types of data, when analyzed together, may reveal additional insights so that inferences can be made about relationships between molecular measurements and health or disease.