Computer Science & Engineering Department
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. Please see my CV and publications for more details.
My research has been generously supported by the National Science Foundation, a Google Faculty Research Award, a J.P. Morgan Faculty Award, a Facebook Research Award, and a Mozilla Research Grant.
Two NSF proposals awarded: NSF EAGER grant #1927166 (as UMN PI) and NSF CHS grant #1908688 (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
ICML 2018, 2017
During my undergraduate, I was involved in the Bard Prison Initiative and serving as a math tutor in New York Eastern Correctional Facility.
Recent Developments in Research on Fairness. The Simons Institute for the Theory of Computing, Berkeley, CA. July 8-10, 2019.