I am a research scientist working on machine learning and statistical inference.
I'm currently a Distinguished Postdoctoral Researcher in the department of statistics 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. In a previous life, I worked on quantum computing at the University of Waterloo.
My recent interests revolve around adapting machine learning methods for causal inference. Much of my work focuses on learning from network data. Other recent interests include stochastic optimization, privacy, and probabilistic symmetries.
I like collaborations; reach out if you've got a cool problem you'd like to chat about!