I'm a professor in the School of Computing at the University of Utah. My research interests are a random walk through the theoretical and applied aspects of data science, including computational geometry, sublinear algorithms, clustering, and kernel methods.
I'm currently very interested in the social ramifications of automated decision making. I'm a founding member of the FAccT conference. I'm also a member of the board at the ACLU of Utah and a member of the Computing Community Consortium Council.
As of July 1, 2021, I'm at Brown University. You can contact me at firstname at brown dot edu.
News
- Jun 9: I will be part of the Utah State Auditor's Commission on Protecting Privacy and Preventing Discrimination
- Jun 1: New Paper: Problems with Shapley-value-based explanations as feature importance measuresaccepted to ICML 2020.
- May 19: Talk at NSF CISE-SBE Roundtable on Harnessing the Computational and Social Sciences to Solve Critical Societal Problems
- May 12: Talk to University of Utah Alumni Association on social and ethical ramifications of machine learning in society.
- May 12: Talk at the University of Chicago's CAPP program on algorithmic fairness
For more, see my news page
Research
I'm interested in the problem of algorithmic fairness: ensuring that in a world of automated decision-making, decisions that get made about us and for us are fair, accountable and transparent.
This is the culmination of a series of research explorations that started with algorithms and computational geometry, lifted to high dimensional geometry and sublinear algorithms, with a random sampling of work in clustering and kernel methods.
For more, see my publications
Teaching
Spring 2020
- Clustering
Fall 2019
- Ethics of Data Science
Spring 2019
For more, see my teaching page.