Specialist in Data

Part data science, part data analysis, part data engineer; occasional sysadmin.

Professional Experience

  • Mapping and converting a financial SQL dataset to an RDF Knowledge Graph
  • Managing the ETL data pipeline for the Fine Arts Museums of San Francisco (the de Young and Legion of Honor)
  • Ontology development at Semantic Arts
  • Systems administration & implementing CIS standards for the School of Information at the University of Texas at Austin
  • Academic Assistant for courses on Data Semantics and Datafication


  • Courses on implementing AI/ML, including
    • Natural Language Processing
    • Deep Learning & Multimodal AI
    • Computer Vision
    • Intro to Machine Learning
  • Independent Study on rapid prototyping for existing AI/ML and data augmentation tools (currently ongoing)
  • Independent Study on systems administration for robotics
  • Courses on critical analysis of information and Human-AI Interaction

Other Learning

  • Running my own web servers to practice systems administration
  • Completed classes and soon will be taking the exam for the AWS Cloud Foundations certification


I have more projects that I’m still converting to a web format; here’s some more of what I’ve been up to:

  • Training an AI model to analyze what questions SQL queries were answering
  • Building an experience around the WebGazer eye-tracking library
  • Ansible configuration for Turtlebot robots
  • Ansible configuration for servers following CIS security benchmarks
  • Ansible configuration for desktops/workstations, including Nvidia drivers and CUDA
  • Smithsonian Collections

    Smithsonian Collections

    This project is an interactive dashboard visualization of the Smithsonian Institute’s Smithsonian Open Access dataset, which contained 11.9 Million Records at time of. The dashboard allows insight into the composition of the Smithsonian’s collections, including what, when, and where items come from. Specifically, the visualization looks at the unit (such as the National Museum of… Read more…

  • Cleveland Museum of Art Collections

    Cleveland Museum of Art Collections

    This project is a narrative visualization seeking to interpret some of the information that can be obtained by looking at a museum’s collections. The dataset contains about 62,000 records including data like department, type (such as “print” or “jewelry”), and whether the item is on display. Read more…


  • Trying Home Assistant’s “Year of Voice” AI

    Home Assistant is arguably a staple of home labs for IoT devices and this year they’ve been running a “Year of Voice” campaign about their efforts to enable voice assistant functionality. So, I decided to take a peek and see how well it works. Read more…

  • Trying out a Coral TPU

    A few years ago, Google released a neat little product called Coral, a “tensor processing unit” (TPU), aka, an AI accelerator. Targeted at IoT/embedded devices, such as a Raspberry Pi, Coral can run models using TensorFlow Lite and has enough performance to allow these devices to do some AI in a reasonable amount of time. Read more…

  • Searching Manuals with ElasticSearch

    Continuing from the last post on searching the Linux manual (“man”) pages, this week I’m going to be using ElasticSearch and see how well it works. Read more…