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

• Advanced Algorithms

For more, see my teaching page.