School of Computer Science
Carnegie Mellon University
I am an Assistant Professor in
the School of Computer
Science at Carnegie
Mellon University, with an appointment in the
Institute for Software
Computing program), and affiliated appointments with
the Machine Learning
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 to make machine learning more reliable and robust when algorithms interact social and economic dynamics. I study these questions using methods and models from machine learning, statistics, optimization, differential privacy, game theory, and mechanism design. For more details, please see my publications.
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.
Previously, I received a Ph.D. in Computer Science in 2017 from the University of Pennsylvania, where I was extremely fortunate to have been co-advised by Michael Kearns and Aaron Roth. My doctoral dissertation titled "Data Privacy Beyond Differential Privacy" received Penn's Morris and Dorothy Rubinoff Award for best thesis. Before joining CMU, I was an Assistant Professor of Computer Science & Engineering at the University of Minnesota for two years. Before that, I spent a year as a post-doctoral researcher at Microsoft Research-New York City in the Machine Learning and Algorithmic Economics groups. Please see my CV for more details.
Three papers accepted at NeurIPS'20: one as Oral and one as Spotlight.
Our NSF proposal in the Smart and Connected Communities (S&CC) program has been funded.
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.
Our NSF proposal in the NSF Program on Fairness in Artificial Intelligence (FAI) in Collaboration with Amazon was selected for funding.
Conference Program Committee
NeurIPS 2020 (area chair)
ICML 2020 (area chair)
ICLR 2021, 2020 (area chair)
AISTATS 2021 (area chair)
FAccT 2019, 2021 (area chair)
TheWebConf 2020, 2018
EC 2020, 2019, 2018
Workshop Program Committee
Recent Developments in Research on Fairness. The Simons Institute for the Theory of Computing, Berkeley, CA. July 8-10, 2019.