I'm a Senior Software Engineer at the University of Utah in the Visualization Design Lab. Most of my work is building performant web applications to support the visualization of complex data. I received my Ph.D. in Applied Mathematics from the University of Arizona where I focused on the intersection of data analysis and pure mathematics -- specifically in Topological Data Analysis.
At Utah, I've had the pleasure to work on two major open-source projects - reVISit and Loon. You can learn more about the projects that I've worked on recently on my Projects page.
On reVISit, most of my work is developing the authentication system so that when users fork this repository, there is minimal setup required in order for the user to fully secure their data. I have also contributed to many UI components in reVISit, created our Docusaurus documentation website, and still manage said documentation website. In Loon, my goal was to move the single page-web application built in Vue.js to a dockerized set of services which supports large data upload. Similar to reVISit, while we do host our own version of our application, the application is meant to be shipped as docker images. That way, the user can easily start a local version (or deploy a version on their own server) and no users have to be concerned with storing sensitive data on Utah servers. The back-end of our application primarily a Django server combined with Celery and Redis for background task execution (specifically for processing and transforming data), a MinIO storage engine for data storage, a MySQL database for storing file references, and a DuckDB instance for use with the visualization library Mosaic.
Before my current role, I worked at Gravy Analytics (now Unacast), a leader in geo-location services, where I focused heavily on software development and data engineering. I designed and built two critical systems that streamlined internal processes and improved operational efficiency. The first was an internal API, written entirely in Python using Flask, which automated the quality assurance process for daily data deliveries. By integrating AWS and GCP, the API dynamically generated queries, executed them, and logged results into a shared Google Sheet, reducing a two-hour manual QA process to, in most cases, under one minute. I also developed a full-stack application with a React.js front-end and a Flask back-end to optimize data extraction workflows, now widely adopted across multiple teams.
While in graduate school, I co-founded a tutoring company with a former colleague. Our goal was to hire mainly current master's and Ph.D. students as tutors for students ranging from 5th grade all the way to upper-level undergraduates. We believe this solved two critical issues at once:
At it's peak, we employed 20+ tutors and had a contract with a local Tucson charter school where we tutored 120+ hours per week across three different campuses. These services were provided as extra support to struggling students with a student to tutor ration of approximately 5:1. My position in all of this was not only to help manage our company, but mostly focused on our company website where tutor profiles were hosted with personalized videos, allowed users to schedule tutors, and securely capture payment information. Additionally, I fully built a tutor portal so that each tutor could log sessions that they have completed, check worked hours, and many other administrative features.
Aside from work, I'm an avid music fan and love to cook. My love for music and desire for a better way to sift through the multitude of music reviews is why I created MuView
.