I currently work for Google in the Machine Intelligence group. I really enjoy the research opportunities at Google and exploring the amazing amounts of data that we have access to.
I also run a side project called Steam Recommender. Many gamers (including myself) keep their Steam profiles public and this allows me to gather data on what games people have been playing. Powering the website is a recommendation engine that I’ve cobbled together and provides fairly good recommendations.
Prior to joining Google, I was the Lead Data Scientist at Riot Games working within the Insights and Big Data teams for the wildly popular video game League of Legends. We were very focused on building a general purpose recommender system that was capable of online and batch learning and able to serve millions of recommendations with horizontal scaling. We were able to deploy a collaborative-filter recommender that recommends champions to play or purchase based on who a summoner has been playing recently.
I still actively develop games and am currently working on a 2D game that is a spiritual successor to a game developed as part of a 48 hour game competition while I was a professor at the University of Wisconsin-Stout. iTanks is a collaboration with Ryan Appel and Tegan Moersfelder that was made using the Monkey engine.
Profiles
Software
- Wubble World 2D
- Agent simulator developed as part of my PhD thesis.
- UA Time Series
- Framework for processing sensor data generated from Wubble World 2D and other sources.
- Fluid Swarms
- Research on autonomous swarm control algorithms that behave as particles in a fluid simulation.
Education
- PhD in Computer Science, 2010, University of Arizona, Tucson AZ
- MS in Computer Science, 2005, University of Wyoming, Laramie WY
- BS in Computer Science, 2001, Kansas State University, Manhattan KS