His primary interests are in the field of statistical machine learning, including problems at the intersection of systems and learning, and applications in computational genomics. His current work is motivated by the goal of democratizing machine learning, with a focus on topics related to the scalability, automation, and interpretability of learning algorithms and systems. He led the initial development of the MLlib project in Apache Spark, is a co-author of the graduate-level textbook 'Foundations of Machine Learning' (2012, MIT Press), and created an award-winning edX MOOC about distributed machine learning.