About me

I work on data-focused projects that span machine-learning, data visualization, web development, and the Internet of Things (IoT). I write mostly in Python and JavaScript with smaller amounts of R, PHP, sed/awk, C++, and Java.

Professionally, I work on the agency data analytics team within NASA’s Office of the Chief Information Officer’s Technology and Innovation division. I consult and build prototypes for internal NASA customers in finance, human resources, facilities, space technology, and other domains that solve client problems and enable new insights. Lately, my professional work has leveraged speech-to-text machine-learning, graph database, and web-based data visualization libraries.

In my personal time, I co-organize the Houston Data Visualization Meetup and manage the social media of the Gulf Coast Section of SEPM (sedimentology geology society). I also attend hackathons, like the Houston NASA Space-Apps hackathon and geoscience hackathons run by AgileScientific.

Side projects are a major way I add to my skills, so I always have several in development or on the to-do list.

Previous Side-Projects

  • Assembled a Raspberry Shake, a personal seismometer.
  • Built an internet connected pumpkin for Halloween that talked to small children.
  • Presented a talk on the changing data visualization landscape in large organizations (1974-2016).
  • Competed in a machine-learning contest to predict well log facies put on by a geophysics journal.
  • Created an augmented reality webpage / business card using AR.js, which leverages three.js, aframe.js, and ARtoolkit.
  • Used SVM machine-learning approach to identify direct returns, reflections, multiples, and coherent noise in seismic gathers as part of a Geoscience Hackathon organized by Agile Scientific and Total. I participated virtually and the rest of my team was physically present in Paris.
  • Helped build map applications to assist in the spreading and collection of accurate information about shelters and flooding post-Hurricane Harvey in collaboration with a large number of other volunteers via SketchCity, a civic tech organization.
  • Built version zero of an application that can take in any google forms results csv files, pick the right charts, and create a data visualization such that clicking on an answer to a question filters the answers to every other question.
  • Participating in a geoscience hackathon run by AgileScientific before the annual Society of Exploration Geophysicists Conference in Houston. Built a python-based machine-learning model to mimic geologists’ stratigraphic picks of the top of the McMurry Formation in Canada. Still working on this project as I get spare cycles.
  • Building a “where science happens in Houston” map that leverages web-scraping and machine-learning.
  • Played around with using three.js to make three-dimensional data visualizations from car-based lidar data.

Side-Projects over the last couple months

  • Built a well log file uploader & parser called “wellio.js” that converts LAS files into JSON files, so the data can be manipulated by JavaScript. This enables other applications to be built that load local LAS files and manipulate/visualize them in the browser without needing python, server, or a proprietary application.
  • Did a quick bit of machine-learning in a jupyter notebook to answer the question, “software engineer or data scientist”?
  • Wrote a bunch of small JavaScript data visualization experiments on ObservableHQ, which is a new way to write public, live, forkable JavaScript in a way that feels a lot like a more easily sharable Jupyter notebook. Specifically, messing around with machine-learning, data parsing, and sonification of data in JavaScript.


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GitHub-Mark-32px or check out some of my code on Github