Edric Tam, PhD

I am a statistician and machine learning scientist developing novel methodology and theory motivated by biomedical and neuroscience applications. I am broadly interested in (Bayesian) statistics, (probabilistic) machine learning, and all things graph/network related. On the more mathematical front, I am interested in spectral graph theory, convex geometry and concentration of measure.

Currently, I am the Warren Alpert Fellow in AI and Computational Biology at Stanford, working with Barbara Engelhardt. Prior to that, I received my PhD in Statistical Science from Duke, advised by David Dunson. I also hold degrees in biomedical engineering and computer science from Johns Hopkins, Yale and Chicago.