Michael D. Escobar

Michael David Escobar is an American biostatistician and professor in the Biostatistics Division at the University of Toronto's Dalla Lana School of Public Health. He is known for work on Bayesian nonparametrics and mixture models.

Education and career Escobar earned a degree in mathematics at Tufts University in 1981 followed by a doctorate in statistics at Yale University in 1988 under the supervision of John Hartigan. Between 1990 and 1994, he was an assistant professor at Carnegie Mellon University. Escobar subsequently joined the University of Toronto faculty, where he became a tenured professor in the Biostatistics Division at the Dalla Lana School of Public Health and held a cross-appointment in the Department of Statistical Sciences. He has taught the graduate course Applied Bayesian Methods at Toronto. In 2012/13, he received the Robin Badgley Award for Teaching Excellence (Open). In 2015, he was elected a fellow of the American Statistical Association.

Research University of Toronto sources describe Escobar's research as focusing on computation for Dirichlet process models in nonparametric Bayesian statistics, mixture models for heterogeneous populations, psychiatric applications, and broader statistical work in the medical, biological, and public health sciences.

Selected works