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Solve wordsearch using a camera
An interactive tree respesentation of all english words
Measures distances very accurately with mobile gps
The website you're visiting now
This react app allows multiple users to see and interact with the same stopwatch. Intended for cross country races, it can allow coaches or spectators see live lap updates from people at other sections of the course. The web app was written with React and the backend utilizes AWS and a NodeJS server connected to a MongoDB database.

This project was the culmination of years of frustration at losing to my brothers at our annual beach wordsearch battle. After being very surprised that this didn't already exist, I set out to create a website where you can simply upload a (well cropped) image of a wordsearch and instantly have the solution drawn for you. Since many OCR libraries such as Google Tesseract weren't reliable on the single letters in a wordsearch, I was forced to train an image classifier using tensorflow to identify letters myself after the image is processed and each letter is separated from the original image.

In the fall of my sophomore year at Princeton, I took an introduction to linguistics class where we talked in great detail about the sounds of the english language and how they interact with each other. This, combined with my computer science class where we were implementing tree structures, inspired me to make this visualization of the english lexicon by organizing words by their sequence of letters in order to shed light on their relationships in an intuitive way.
"GPS Ruler" is an android app that I made after being dissatisfied with the apps that were currently available. Although there are many apps targeted towards golf and disc golf that do this, they only took one GPS sample at each point and were therefore very innacurate. I solved this by averaging many points on each end of the measurent and using statistical analysis to alert users of error and outliers in their measurement and showing the measurements on a Google map.

This website was written using NextJS and TypeScript. As I continue my studying and career, I expect to keep this website up to date with everything I'm doing. Feel free to check out the code on github!
