Aaron Roth

Photo of me

About Me

I am a Raj and Neera Singh Assistant Professor of Computer and Information Science at the University of Pennsylvania computer science department, associated with the theory group, our new program in Networked and Social Systems Engineering, and the Warren Center for Network and Data Sciences. I spent a year as a postdoc at Microsoft Research New England. Before that, I received my PhD from Carnegie Mellon University, where I was fortunate to have been advised by Avrim Blum. My main interests are in algorithms and theoretical computer science, and specifically in the area of database privacy, game theory and mechanism design, and learning theory. I am the recipient of an NSF CAREER award, and a Yahoo Academic Career Enhancement award.

New! Our Differential Privacy book is now available!

My lovely wife Cathy just got her PhD in math at MIT. At her insistence, I link to her website

Contact Information

Office: Levine 603
Phone: 215-746-6171
Email: aar...@cis.upenn.edu (Click to reveal my email address)

Teaching
This semester I am teaching: Automata, Computability, and Complexity.

Previous courses:
I'm fortunate to be able to work with several excellent graduate students and postdocs.
Current: Alumni:
Professional Activities

Workshops and Tutorials: Program Committee Member For:
Books and Surveys
  1. The Algorithmic Foundations of Differential Privacy. Joint with Cynthia Dwork. Foundations and Trends in Theoretical Computer Science, NOW Publishers. 2014.
  2. Privacy and Mechanism Design. Joint with Mallesh Pai. SIGecom Exchanges, 2013.

Selected Publications
 (See here for all publications)
Click for abstract/informal discussion of results
  1. Jointly Private Convex Programming. Joint work with Justin Hsu, Zhiyi Huang, and Steven Wu. Manuscript.
  2. Preserving Statistical Validity in Adaptive Data Analysis. Joint work with Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, and Omer Reingold. Manuscript.
  3. Privacy and Truthful Equilibrium Selection for Aggregative Games. Joint with Rachel Cummings, Michael Kearns, and Steven Wu. Manuscript.
  4. Private Pareto Optimal Exchange. Joint with Sampath Kannan, Jamie Morgenstern, and Ryan Rogers. Manuscript.
  5. Online Learning and Profit Maximization from Revealed Preferences. Joint with Kareem Amin, Rachel Cummings, Lili Dworkin, and Michael Kearns. To appear in AAAI 2015.
  6. Accuracy for Sale: Aggregating Data with a Variance Constraint. Joint with Rachel Cummings, Katrina Ligett, Steven Wu, and Juba Ziani. To appear in ITCS 2015.
  7. Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy). Joint with Sampath Kannan, Jamie Morgenstern, and Steven Wu. To appear in SODA 2015.
  8. Dual Query: Practical Private Query Release for High Dimensional Data. Joint work with Marco Gaboradi, Emilio Jesús Gallego Arias, Justin Hsu, and Steven Wu. In the proceedings of ICML 2014.
  9. Privately Solving Linear Programs. Joint with Justin Hsu, Tim Roughgarden, and Jon Ullman. In the proceedings of ICALP 2014.
  10. Buying Private Data without Verification. Joint work with Arpita Ghosh, Katrina Ligett, and Grant Schoenebeck. In the proceedings of EC 2014.
  11. Asymptotically Truthful Equilibrium Selection in Large Congestion Games. Joint work with Ryan Rogers. In the proceedings of EC 2014.
  12. Bounds for the Query Complexity of Approximate Equilibria. Joint work with Paul Goldberg In the proceedings of EC 2014.
  13. Private Matchings and Allocations. Joint work with Justin Hsu, Zhiyi Huang, Tim Roughgarden, and Steven Wu. In the proceedings of STOC 2014.
  14. Mechanism Design in Large Games: Incentives and Privacy. Joint with Michael Kearns, Mallesh Pai, and Jon Ullman. In the proceedings of ITCS 2014.
  15. Constrained Signaling in Auction Design. Joint work with Shaddin Dughmi and Nicole Immorlica. In the proceedings of SODA 2014.
  16. Exploiting Metric Structure for Efficient Private Query Release. Joint work with Zhiyi Huang. In the proceedings of SODA 2014.
  17. Beyond Worst-Case Analysis in Private Singular Vector Computation. Joint with Moritz Hardt. In the proceedings of STOC 2013.
  18. Differential Privacy for the Analyst via Private Equilibrium Computation. Joint with Justin Hsu and Jon Ullman. In the proceedings of STOC 2013.
  19. Efficiently Learning from Revealed Preference. Joint with Morteza Zadimoghaddam. In the proceedings of WINE 2012.
  20. Conducting Truthful Surveys, Cheaply. Joint with Grant Schoenebeck. In the proceedings of EC 2012.
  21. Beating Randomized Response on Incoherent Matrices. Joint with Moritz Hardt. In the proceedings of STOC 2012.
  22. Iterative Constructions and Private Data Release. Joint with Anupam Gupta and Jonathan Ullman. In the proceedings of TCC 2012.
  23. Privately Releasing Conjunctions and the Statistical Query Barrier. Joint with Anupam Gupta, Moritz Hardt, and Jonathan Ullman. In the proceedings of STOC 2011.
    Full version appears in SIAM Journal on Computing (SICOMP) 2013.
  24. Selling Privacy at Auction. Joint work with Arpita Ghosh. In the proceedings of EC 2011.
    Invited to a special issue of Games and Economic Behavior (GEB) 2013.
  25. New Algorithms for Preserving Differential Privacy. PhD Thesis.
  26. Interactive Privacy via the Median Mechanism. Joint with Tim Roughgarden. In the proceedings of STOC 2010.
  27. Constrained Non-Monotone Submodular Maximization: Offline and Secretary Algorithms. Joint with Anupam Gupta, Grant Schoenebeck, and Kunal Talwar. In the Proceedings of WINE 2010.
  28. Differentially Private Combinatorial Optimization. Joint with Anupam Gupta, Katrina Ligett, Frank McSherry, and Kunal Talwar. In the Proceedings of  SODA 2010.
  29. Auctions with Online Supply. Joint with Moshe Babaioff and Liad Blumrosen. In the Proceedings Of EC 2010.
  30. A Learning Theory Approach to Non-Interactive Database Privacy. Joint with Avrim Blum and Katrina Ligett. In the proceedings of STOC 2008: The 40th ACM Symposium on the Theory of Computing.
    Full version appears in Journal of the ACM (JACM) 2013.
  31.  The Price of Stochastic Anarchy. Joint with Christine Chung, Katrina Ligett, and Kirk Pruhs. In the proceedings of SAGT 2008: The first Annual Symposium on Algorithmic Game Theory.
  32. Regret Minimization and the Price of Total Anarchy. Joint with Avrim Blum, MohammadTaghi Hajiaghayi, and Katrina Ligett. In the proceedings of STOC 2008: The 40th ACM Symposium on the Theory of Computing.
Presentations
(Slides Available Upon Request)