Morris J. Greenberg

I am a Ph.D. candidate in the Department of Statistical Sciences at the University of Toronto, advised by Prof. Radu Craiu and Prof. Kieran Campbell. My research centers on Bayesian modeling and computation, with a focus on scalable methods for complex health-care data — particularly ‘omics data — graph inference, hierarchical models, and approximate Bayesian computation.

Before Toronto, I earned an M.S. in Statistical Science from Duke University and a B.S. in Quantitative Economics and Mathematics from Tufts University. Prior to graduate school, I worked as an analyst/senior analyst at Analysis Group working on building models in healthcare, antitrust, and technology litigation as well as building machine learning models in health economics and outcomes research (HEOR).

Outside of my primary research, I stay active in applying statistical and machine learning methods to two long-standing interests of mine: competitive Scrabble and baseball analytics. You can read more about both on my projects page.

Feel free to reach out by email if you’d like to talk research, teaching, or other projects.