My goal is to increase human potential through advancing interactive machine learning. Revolutions in storage and computation have made it easy to capture and react to sequences of decisions made and their outcomes. Simultaneously, due to the rise of chronic health conditions, and demand for educated workers, there is an urgent need for more scalable solutions to assist people to reach their full potential. Interactive machine learning systems could be a key part of the solution. To enable this, my lab’s work spans from advancing our theoretical understanding of reinforcement learning, to developing new self-optimizing tutoring systems that we test with learners and in the classroom. Our applications focus on education since education can radically transform the opportunities available to an individual.