Backend and Machine Learning fo the Content Strategy tool. For more context around the tool, check out Christopher O'Donnell present it at the Inbound 2016 Product Spotlight

Built the Machine Learning and backend of the Predictive Lead Scoring tool. Watch Dharmesh Shah announce it at the Inbound 2015 keynote

An implementation paper in which I implemented and compared 7 different auction algorithms for multiple items. Implementation in Java.

An implementation paper in which I implemented divide and conquer algorithms for finding strongly connected components in parallel. Implementation in Scala.

A machine learning paper based on a Kaggle competition, written together with the excellent Bryan Ball. Used a variety of algorithms to predict weather and sentiment from weather-related tweets.

I hacked this website together using Jekyll and GitHubPages. Source viewable at https://github.com/Krimit/Krimit.github.io

I co-founded NabbTix, a startup aimed at making getting tickets to hot events easier

A 3D model of mars created in WebGL using Three.js showing the locations of spacecraft landings. Go here to see a live demo. You can check out the extremely messy source code at github.com/Krimit/mars

A blogging platform coded in Python and hosted on Google AppEngine. I had a great time building it. Code at github.com/Krimit/blog

An implementation of Connect Four in Java. This project was an exercise in using The Observer design pattern (MVC). Created as an assignment for the incredibly awesome Production Quality Software course at NYU with Professor Michael Schidlowsky. Code available upon request

An implementation of a paint program in Java. This project was an exercise in using The Observer design pattern (MVC). Created as an assignment for the incredibly awesome Production Quality Software course at NYU with Professor Michael Schidlowsky. Code available upon request