In his role as a machine learning engineer, Gabe designs, develops, and evaluates the mathematical models that convert terabytes of raw data into key insights. In addition to a strong familiarity with the academic side of machine learning research, he has significant experience solving practical AI problems through deployment and analysis of models in industry. Gabe graduated from Princeton magna cum laude with a degree in Computer Science and a certificate in Applied and Computational Math. He finished up his education at the University of Washington, obtaining a PhD in Computer Science with a focus on how Big Data can be used for predictive purposes in developing countries. His published research has included using anonymized call data to predict wealth, inferring road quality from satellite imagery and debugging complex machine learning systems. Gabe has also had experience with machine learning in industry. He worked two years for Microsoft in the Bing Core Relevance team as a program manager and had internships with both Microsoft Research (in Redmond) and IBM Research Africa (in Nairobi) as a researcher.