Most of my work focuses on the applied mathematics of data, in particular on the theory and practice of what is now called big data, although I was doing it back when it was just massive, and prior to that when it was just large. On the theory side, we develop algorithmic and statistical methods for matrix, graph, regression, optimization, and related problems. On the implementation side, we provide implementations (e.g., on single machine, distributed data system, and supercomputer environments) of a range of matrix, graph, and optimization algorithms. On the applied side, we apply these methods to a range of problems in internet and social media analysis, social networks analysis, as well as genetics, mass spec imaging, astronomy, climate, and a range of other scientific applications.