Computer Science & Engineering
University of Minnesota
I am an Assistant Professor
Science & Engineering at
the University of
Minnesota. I received my PhD in Computer Science from
the University of
Pennsylvania, where I was extremely fortunate to have
Kearns and Aaron
Roth. My doctoral dissertation received Penn's Morris
and Dorothy Rubinoff Award for best thesis. Before joining
the UMN, I spent a year as a post-doctoral
at Microsoft Research-New York
the Machine Learning
and Algorithmic Economics groups.
I work on algorithms and machine learning. My recent work focuses on (1) how to make machine learning better aligned with societal values, especially privacy and fairness, and (2) how social and economic dynamics, such as strategic interactions, influence machine learning. I study these questions using methods and models from machine learning, statistics, optimization, differential privacy, game theory, and mechanism design.
My research has been generously supported by the National Science Foundation (NSF), an Amazon Research Award, a Google Faculty Research Award, a J.P. Morgan Faculty Award, a Facebook Research Award, and a Mozilla Research Grant.
Please see my CV and publications for more details.
Come learn about privacy at differentialprivacy.org!
Six papers accepted at ICML'20. Congratulations to Giuseppe Vietri on his three papers!
Three papers accepted at EC'20, COLT'20, and DIS'20.
One NSF proposal awarded (as PI) in the NSF Program on Fairness in Artificial Intelligence (FAI) in Collaboration with Amazon.
Program Committee Member
NeurIPS 2020 (area chair)
ICML 2020 (area chair)
ICLR 2021, 2020 (area chair)
AISTATS 2021 (area chair)
FAT* 2019 (track co-chair)
TheWebConf 2020, 2018
EC 2020, 2019, 2018
Recent Developments in Research on Fairness. The Simons Institute for the Theory of Computing, Berkeley, CA. July 8-10, 2019.