My research interests include convex analysis, matrix analysis, conic programming, and their applications to nonlinear optimization. My current focus is on the relaxation of combinatorial optimization problems arising from applications in machine learning and high-dimensional statistics, specifically, convex relaxations for learning tasks such as clustering and classification.
I spent the 2011-12 and 2012-13 academic years as a Postdoctoral Fellow at the Institute for Mathematics and its Applications at the University of Minnesota, participating in the 2011-12 thematic program on the Mathematics of Information.
I completed my Ph.D. in July of 2011 under the direction of Dr. Stephen Vavasis in the Department of Combinatorics and Optimization at the University of Waterloo. I previously studied in the Department of Mathematics and Statistics at the University of Guelph where I obtained a M.Sc. in Applied Mathematics (completed under the direction of Dr. Hristo Sendov) and B.Sc. in Mathematics.