Who I Am

What I've Done


June 2012–present
Technologies Used: C, C++, Python
  • Obtained reference code for parts of the game's COM framework to reverse engineer
  • Created a partial framework from the reference to create a working hardcoded module
  • Documented various structures and classes in the game for potential developers


December 2015; January 2018
Technologies Used: C, C++, x86 Assembly
  • Used Ollydbg to debug a reproducible null dereference crash in the game SimCity 4
  • Resolved a serialization bug that could cause savegame corruption


April 2016
Technologies Used: Python, Raspberry Pi, Dropbox API
  • Best Hardware Hack at HackNY's Spring 2016 hackathon
  • Created a threaded Python program for capturing picture streams and video
  • Configured a Pi A+ to roam open Wi-Fi networks to be able to upload most of the time
  • Experimental Twitch streaming implemented for kicks
Collaborative project with Ben Roytenberg, Claire Wang and Patrick Wu.


February 2016
Technologies Used: Python, Flask, SQLite (via Peewee ORM), VirtualBox CLI
  • Created reference images of OEM copies of Windows 2000 and XP
  • Used Python 2.x and avast! antivirus on images to track when a machine is infected
  • Used shared folders to automatically execute malware samples and model infections
  • Flask frontend created on host to display state of machines and infections


February 2015–September 2015
Technologies Used: Android, Java, TCP networking, Spotify API
  • Users could vote on songs to play (or not) in a "party" using this platform
  • Network Service Discovery was used for discovering servers on a common network
  • Used the Kryonet library to (de)serialize packets between server and client
  • Spotify API was used for streaming media, but requires a premium account as a result


December 2014
Technologies Used: Python, Pygal graphing
  • Used requests library to make and time HTTP requests
  • Allows a user to see the response time of a site over time without admin access to server
  • Outputs each result to a CSV and constructs a line graph at the end


May 2014
Technologies Used: Android, Java, MongoDB, Node.js, Sails.js, Spotify API
  • Listens to broadcasted Android intents for songs being played
  • When a song is played, broadcasts GPS coordinates and song to a central server
  • Server uses Spotify search API to verify proper song title if possible
  • Users can also see other geotagged listens near them on a map
Note: I was mostly involved with the Android client. The server, which was written in Node.js, was almost entirely written by Ilya Rubnich.