I am a research scientist interested in the theory and application of machine learning and statistical inference, particularly in situations where the current tools are lacking or nonexistant.
I'm currently the Distinguished Postdoctoral Research Scientist in the department of statistics at at Columbia University, where I work with the groups of David Blei and Peter Orbanz. I completed my Ph.D. in statistics at the University of Toronto, where I was advised by Daniel Roy.
Much of my work revolves around learning from relational data such as networks. Other recent interests include causal inference, stochastic optimization, privacy, and probabilistic symmetries.
I like collaborations; reach out if you've got a cool problem you'd like to chat about!