Dalla Lana School of Public Health
Professor Michael Escobar is a professor in the biostatistics division at the Dalla Lana School of Public Health (DLSPH) and is a leader in theoretical and applied statistical research. He received his PhD from Yale University in 1988 and was on the faculty at Yale University and Carnegie Mellon University before coming to Toronto. He has been a faculty member at U of T since 1993. Professor Escobar's work involves both statistical research and collaborative research and he is known internationally for his foundational developments in Bayesian nonparametric modeling and computational algorithms. His work in this area relates to a wide range of disciplines including machine learning, econometrics, genomics, and environmetrics. His applied statistical work is aimed at applying and improving statistical techniques in the medical, biological, and public health sciences. This collaborative work spans a wide range of work in biomedical public health research. While most of these publications have been in the area of mental health, learning disabilities, traumatic brain injury, HIV prevention, his collaborative work has covered most of the areas of the determinants of health. His past leadership positions at U of T include director of the Biostatistics programs, interim chair of the Department of Public Health Sciences, interim director of the DLSPH, and associate dean of faculty affairs at DLSPH. He has won the LJ Savage Thesis award for the worldwide best thesis in Bayesian methods and the Robin Badgley Teaching award at the Dalla Lana School of Public Health, and he is a Fellow of the American Statistical Association.