Josh Byster

CS and Mathematics Major
University of Illinois at Urbana—Champaign
Passionate Developer

Please scroll down for my latest projects or connect with me on a channel below!


Projects

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UIUC Bus Tracker

Thousands of students at U of I rely on the Champaign-Urbana buses each day as a means of getting to class. Unfortunately, many apps to check bus times take too long to load. As college students, we need this information as soon as possible. This is a simple, minimalist web app designed for frequent bus riders in Urbana—Champaign. No clutter, no ads, no hassle, just info. Used by hundreds of students and faculty on a daily basis. Uses a CDN and API response caching with Redis to ensure the fastest load times for users. Please feel free to check out the site, frontend, and backend code.
Tech Stack:

ReactJS NodeJS TravisCI GitHub Pages Redis Heroku

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Philadelphia READS© Web App

Philadelpha READS© makes an impact on thousands of students each year through their programs to help increase literacy in Philadelphia. As a volunteer software engineer for Hack4Impact, I had the opportunity to work with an incredible team of developers to create a web app for students from fourth through eighth grade. The app allows students to prepare for Philadelphia READS Reading Olympics, an annual competition where over 1,500 participants form reading teams and put their comprehension to the test. Please feel free to have a look at the source code.
Tech Stack:

Python Postgresql ReactJS NodeJS CircleCI DigitalOcean

Twitter Support Vector Machine

Recognized by the American Statistical Association for outstanding use in machine learning at science fair, this Python script allows users to carry out authorship attribution algorithms on thousands of tweets. After acquiring an Twitter API key, users can input as many public channels as they would like, and the script loads and parses every tweet, generates confusion matrices, finds the most distinct words, and returns a trained and cross-validated classifier. A properly trained model can correctly pick between two possible authors of a of a given tweet 95% of the time! Please feel free to have a look at the source code.
Tech Stack:

Python Cloud9