I'm not good with titles. I usually describe myself as a computational scientist and data architect. I have with experience implementing distributed, large data applications and putting cutting edge math to work. In my day job, I play the Chief Science Officer at Continuum Analytics, a Python data science startup. This basically means I get to work with an amazing set of data and computational scientists to address some of industry's data needs.

I'm an advocate for quality open source scientific software tools. I'm currently the President of NumFOCUS, a foundation trying to help sustain scientific software tools. I'm a passionate member of the open source scientific Python community.

I spent a decade in academia creating novel algorithms to speed implementations of mathematical models on the world's largest supercomputers, usually computational fluid dynamic codes. This was done in high level languages and code generation with open source tools. My code has been used in applications as varied as patient specific medical care to predicting hurricane storm surges.

For the more credential-oriented minds, I received my Computer Science PhD at the University of Chicago in 2010. I've held research positions at Argonne National Lab, Sandia National Lab, Institute of Computational Engineering and Sciences at The University of Texas-Austin, and the Texas Advanced Computing Center. In industry, I served as lead developer at Kove, Inc. during its early stages, where I helped bring a record breaking SAN disk array to market. I've also has also worked with big data financial applications at Enthought, Inc and currently at Continuum Analytics, Inc.