Tyler’s work develops statistical models for inference and prediction in scientific settings where data are sparsely observed or measured with error. His recent projects include estimating features of social networks (e.g. the degree of clustering or how central an individual is) using data from standard surveys, inferring a likely cause of death (when deaths happen outside of hospitals) using reports from surviving caretakers, and quantifying & communicating uncertainty in predictive models for global health policymakers. He holds a PhD in Statistics (with distinction) from Columbia University and is the recipient of a NIH Director’s New Innovator Award, NIH Career Development (K01) Award, Army Research Office Young Investigator Program Award, and a Google Faculty Research Award. Currently, he is an Associate Professor of Statistics and Sociology at the University of Washington, where he is also a core faculty member in the Center for Statistics and the Social Sciences and a Senior Data Science Fellow in the eScience Institute. He also co-leads the Science Core at UW’s Center for Studies in Demography and Ecology. Tyler served as the Editor for the Journal of Computational and Graphical Statistics (JCGS) from 2019-2021.

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