Reich Lab

Biostatistics faculty members foster a unique environment in which practical involvement in transdisciplinary research collaborations can flourish. Our faculty creates the theoretical and applied statistical methods necessary to design laboratory, medical, and public health studies; to undertake quantitative evaluation and measurement; and to use statistical inferences to arrive at appropriate conclusions from medical and public health data. 

Working closely with colleagues across the School of Public Health and Health Sciences, the Biostatistics faculty are involved in multiple avenues of research. Areas of expertise include Bayesian methods, Biomarker Discovery, Causal Inference, Machine Learning, Observational Studies, Randomized Trials, and Time-To-Event Outcomes.