I’m currently at Google Research working on large-scale machine learning problems in the domains of personalization and user targeting. My focus is on reducing the dimensionality of problems through embeddings and semantic annotations, and optimizing the machine learning pipeline.
I am a Ph.D. Graduate from the Evolutionary Complexity lab at the University of Central Florida. My research interests involve biologically inspired solutions to strategic and tactical problems. I co-invented the HyperNEAT indirect encoding with Kenneth O. Stanley and David D’Ambrosio. My dissertation involved applying HyperNEAT to strategic and tactical domains such as checkers and Go. If you are interested in more information, you can view my dissertation or visit the HyperNEAT User’s Page.
I am also active in numerous hobby programming projects, you can see videos and descriptions on my portfolio.