I am a standard-issue carbon-based meat popsicle produced in the late 1980s in the general vicinity of Washington, D.C. and then introduced to the general patterns of human activity in an artificially designed suburb called Columbia. After developing basic motor skills and an adeptness at video games, I relocated to Portland, Oregon and attempted to learn social skills with a very low level of success. As a result, I enrolled for undergraduate studies at Georgia Tech in the fall of 2005 and did not manage to escape until the fall of 2015, having collected three degrees.

My time at Tech was varied and unplanned, but it did (mostly) follow the laws of causality. As an undergraduate I was an electrical engineering student with an interest in digital signal processing. This slowly morphed into an interest in the algorithmic details of machine learning, which I studied in detail as part of the FASTLab, led by Dr. Alex Gray. Aside from a minor foray into chicken research, my Ph.D. work and thesis (finally finished in 2015) focused on efficient abstractions for efficient algorithms for core machine learning problems, mostly implemented as part of the mlpack C++ machine learning library.

In the time since then, my interest in fast algorithms hasn't waned; I continue to maintain mlpack, as well as ensmallen (a C++ mathematical optimization library), Armadillo (C++ linear algebra), and bandicoot (C++ GPU linear algebra). I was a part of the Center for Advanced Machine Learning at Symantec, applying these efficient techniques to malware and cybersecurity problems, and also implemented the core machine learning support for RelationalAI's database product.

After quite some years of this, there's one common thread I've found pretty much everywhere in and around data science and machine learning software: there's a huge amount of inefficiency from the top of the stack all the way down to the bottom of the stack. My goal is to produce open software that improves on those inefficiencies---and help apply that software for real-world impact.


But, anyway, that only paints a picture of what I do to pay my bills. Although I enjoy that very much, it is only a sampling of the activities I pursue. At other times I may be found driving (or fixing) a 1930 Model A around the country and documenting historically relevant bridges, operating a blast furnace, winning kart races, interacting with my cats, turning cardboard into fashionable clothing, over-engineering seating solutions, or spending time with my wife, for whom I learned metallurgy. Also, I have yet to meet someone who can beat me at Double Dash or Mario Kart 8 Deluxe.