Steven Wu

Assistant Professor
School of Computer Science
Carnegie Mellon University


Email: zstevenwu [at] cmu.edu

I am an Assistant Professor in the School of Computer Science at Carnegie Mellon University, with an appointment in the Institute for Software Research (in the Societal Computing program), and affiliated appointments with the Machine Learning Department and the Human-Computer Interaction Institute.

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.


NEWS

Sept 2020

Three papers accepted at NeurIPS'20: one as Oral and one as Spotlight.

Aug 2020

Our NSF proposal in the Smart and Connected Communities (S&CC) program has been funded.

July 2020

Come learn about privacy at differentialprivacy.org!

June 2020

Six papers accepted at ICML'20. Congratulations to Giuseppe Vietri on his three papers!

May 2020

Three papers accepted at EC'20, COLT'20, and DIS'20.

Jan 2020

Our NSF proposal in the NSF Program on Fairness in Artificial Intelligence (FAI) in Collaboration with Amazon was selected for funding.


GROUP

I am extremely fortunate to be able to work with several excellent students.

PhD students

Hao-Fei Cheng (co-advised by Haiyi Zhu)
Giuseppe Vietri (co-advised by Maria Gini)
Daniel Ngo (co-advised by Maria Gini)
Logan Stapleton (co-advised by Maria Gini)
Keegan Harris (co-advised by Hoda Heidari)
Gokul Swamy (co-advised by Drew Bagnell)

MS students


TEACHING

Fall 2020

Spring 2020

Fall 2019

Fall 2018


SERVICE

Conference Program Committee

NeurIPS 2020 (area chair)
ICML 2020 (area chair)
ICLR 2021, 2020 (area chair)
AISTATS 2021 (area chair)
ALT 2021
FORC 2020
FAccT 2019, 2021 (area chair)
TheWebConf 2020, 2018
EC 2020, 2019, 2018

Workshop Program Committee

TPDP 2019
NIPSML4H18
HAI-GEN 2020

Workshop Organizer

Recent Developments in Research on Fairness. The Simons Institute for the Theory of Computing, Berkeley, CA. July 8-10, 2019.

Other

I co-organize differentialprivacy.org.
During my undergraduate, I was involved in the Bard Prison Initiative as a math tutor at the Eastern New York Correctional Facility. Check out this amazing four-part documentary film series, College Behind Bars, about this initiative.


TALKS

Nov 2019

Between Individual and Group Fairness
Three Decades of DIMACS: The Journey Continues
Video

Oct 2019

Differential Privacy Techniques Beyond Differential Privacy
FOCS 2019 workshop A TCS Quiver
Slides

Jan 2018

Competing Bandits: Learning under Competition
ITCS 2018
Video

Aug 2017

Meritocratic Fairness for Cross-Population Selection
ICML 2017
Video

June 2017

Fairness Incentives for Myopic Agents
EC 2017
Video

June 2017

Multidimensional Dynamic Pricing for Welfare Maximization
EC 2017
Video