I am a Computing Ph.D. student at the University of Utah, where I am advised by Suresh Venkatasubramanian. I am interested in analyzing the social impact of machine learning systems to develop better AI law and policy. My work has been supported by the ARCS Foundation.
Previously, I worked on the Data Science team at MassMutual, where I developed machine learning models for the pricing and valuation of insurance products, while completing my M.S. in Computer Science at the University of Massachusetts. I received my B.A. in Mathematics from Scripps College, where I spent the spring of my junior year abroad with Budapest Semesters in Mathematics, and also spent some time working as a drawing teacher at an art camp.
email: kumari at cs dot utah dot edu
I. Elizabeth Kumar, Suresh Venkatasubramanian, Carlos Scheidegger, Sorelle Friedler. Problems with Shapley-value-based explanations as feature importance measures. Forthcoming in Proceedings of the 37th International Conference on Machine Learning (ICML), 2020.