Computer Science & Engineering
University of Minnesota
I am an Assistant Professor of Computer 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 been
co-advised by Michael
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 City in
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 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 NSF and Amazon Award on Fairness in AI, 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.
One NSF proposal awarded (as PI) in the NSF Program on Fairness in Artificial Intelligence (FAI) in Collaboration with Amazon.
Two NSF proposals awarded: NSF EAGER grant (as UMN PI) and NSF CHS grant (as co-PI).
Four papers accepted at NeurIPS'19.
I received a Mozilla Research Grant.
One paper accepted at FOCS'19.
One paper accepted at EC'19.
Three papers accepted at ICML'19.
I received a Google Faculty Research Award.
I received a J.P. Morgan Faculty Award.
With Haiyi Zhu, we received the Facebook Mechanism Design for Social Good research award.
Program Committee Member
ICML 2020 (area chair)
ICLR 2020 (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.