His current research interests are in the areas of trustworthy machine learning, applied algebraic topology, and networked data models. He is intrigued by the interplay between humans, machines, and data and the societal implications of machine learning. He was involved in the initial development of the open source AI Fairness 360 toolkit, and is still an active contributor/maintainer. His papers have won best paper awards, and his contributions have been recognized by multiple awards at IBM. He is a member of the IEEE.