Teresa Do is a fourth-year journalism and computer science student in Austin who bridges data-driven reporting and software skills to make local news more accessible and accountable. As Data Editor for UT’s Media Innovation Group and a former Daily Texan reporter and illustrator, she leads student teams, files FOIA requests, and turns messy public datasets into clear data graphics and stories. She also tutors discrete mathematics and reviews student code, bringing pedagogical rigor and practical debugging experience to collaborative projects. An active open-source contributor, Teresa improved documentation and user-facing tutorials for KA Lite, showing comfort across full-stack workflows and offline educational tools. Her work focuses on uncovering disparities in marginalized communities, combining investigative curiosity with technical precision.
11 years of coding experience
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at The University of Texas at Austin
KA Lite: lightweight web server for serving core Khan Academy content (videos and exercises) without needing internet connectivity
Role in this project:
Full-stack Developer
Contributions:59 commits, 7 PRs, 4 comments in 5 months
Contributions summary:Teresa primarily contributed to the documentation of the KA Lite project, focusing on user manuals for administrators and learners. They added sections on user management, accessing the KA Lite server, and downloading content. The user also made changes to the Raspberry Pi installation guide and implemented the inline tutorial feature, showcasing a broad understanding of the project's technical aspects.
Contributions:2 pushes, 1 branch in 7 years 4 months
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