My research lies at the intersection of mathematical statistics, machine learning, combinatorics, multilinear algebra, and applied algebraic geometry. I particularly enjoy discovering mathematical structure which is inherently responsible for the successful solution to a statistical problem. Most recently I have been working on the theory of linear causal models, structured tensor decompositions, shape-constrained density estimation, and super-resolution imaging.
Here is a link to my CV.
Prior to joining UBC I was priviliged to spend three years as a Statistics Instructor and an NSF Postdoctoral Fellow in the Department of Mathematics and the Institute for Data, Systems, and Society at MIT.
In the spring of 2016 I received my PhD in mathematics from UC Berkeley under the supervision of Bernd Sturmfels. Here is a link to my thesis, which won the Bernard Friedman Memorial prize in applied mathematics.
In 2011 I received my BS with Honors in mathematics and a minor in computer science from Stanford University.