I am an assistant professor in the School of Computer Science at the University of Waterloo. Prior to this I was a postdoctoral fellow at the University of California Berkeley in the Department of Statistics and a Principal Investigator at the International Computer Science Institute, where I worked with Michael Mahoney. I completed a PhD in optimization in the School of Mathematics at the University of Edinburgh under the supervision of Prof. Jacek Gondzio.
PhD in Numerical Optimization, 2015
University of Edinburgh
MSc in Operational Research and Computational Optimization, 2010
University of Edinburgh
BSc in Management Science and Technology, 2008
p-Norm Flow Diffusion This repository contains the code to solve primal and dual p-Norm Flow Diffusion problems from the paper p-Norm Flow Diffusion for Local Graph clustering.
Local Graph Clustering provides methods to find local clusters in a given graph without touching the whole graph. C++ implementation with Python interface.
Trillion. Instance generators for l1-regularized over- and underdetermined least squares. The generators are implemented in MATLAB, they are memoryless and computationally inexpensive. Hence, large-scale instances can be created.
pdNCG: primal-dual Newton Conjugate Gradients. A MATLAB implementation for the solution of unconstrained l1-regularized problems. For example, Machine Learning problems, such as l1-regularized least-squares and logistic regression, Compressed Sensing problems, such as l1-synthesis, l1-analysis and isotropic total-variation. The solver is memoryless, it requires only matrix-vector product operations, hence it is appropriate for large-scale instances.
MFIPMCS: Matrix-free Interior Point Method for Compressed Sensing. An interior point method implemented in MATLAB for the solution of real valued compressed sensing problems. The “matrix-free” implies that only matrix-vector products operations are allowed and the process is memoryless. The solver implements efficient preconditioning techniques for the fast solution of linear systems at every iteration.
FCD: Flexible Coordinate Descent. This software only reproduces the experiments in paper Flexible Coordinate Descent.
I am always looking for highly motivated and hard-working Master’s and PhD students to work with. Send me an email if you would like to work with me.
NSERC-Discovery Grant. Project duration 2019-2025.
Data-Driven Discovery of Models (D3M) DARPA Grant. Project duration 2016-2020. In collaboration with M. Mahoney, Farbod Roosta-Khorasani and Alex Gittens.