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 organization FAT* and have helped run the last three FATML workshops. I'm also a member of the board at the ACLU of Utah and a member of the Computing Community Consortium Council.


  • May 22-23: I was at the CCC workshop on Fairness in Economics in Boston.
  • May 20-21: I attended an Amnesty International event in the Netherlands on predictive policing in Europe.
  • May 15: Ashkan Bashardoust presented our paper on Gaps in Information Access in Networks at the 2019 Web Conference
  • . See also the blog post by Ben Fish.

For more, see my news page


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


Fall 2019

  • Ethics of Data Science (new course page coming soon!)

Spring 2019

For more, see my teaching page.