What I've done
These are a collection of side-projects I've worked on.
The News Network
"Big Data", NLP, Data Science
In November of 2019 I built a scraper to collect all headlines from the top 30 US news organizations (as of Jan. 2020 I have collected ~30,000 headlines). Using this data I have been working on a platform that provides media insights like tracing the history & evolution of a story, automatic topic-modeling, and sentiment analysis. More info coming soon :)
Nginx, Swift (iOS), Node.js, RTMP
Dive is a live streaming social network for iOS built using RTMP, Node.js, and Swift. Dive uses a social graph (follower-following model) and hashtags (livestreams have assosciated hashtags that users can follow). This project grew out of a desire to know more about how live streaming technologies work. Screenshots
YouTube tree
JavaScript, Verlet Physics
This project visualizes the YouTube recommendation algorithm to provide insights into its unique characteristics. My hope was the make the blackbox YouTube recommendation algorithm more tangible by creating novel ways of interacting with the algorithm. The visualizations help provide information about the YouTube recommendation algorithm's personalitiy including how it creates rabbit-holes, information silos, and endless recommendations. Demo
Swift (iOS), Node.js
Peer2Peer is an iOS app that connects volunteer tutors to students in need of academic help based on subjects, physical proximity, and our intelligent ratings system. Won 1st place in CA-18 for the 2016 Congressional App Challenge. A demo of the app can be seen here.