I'm an Assistant Professor of Computer Science at Northeastern University.


  • 09-25-2020 Three papers accepted to NeurIPS 2020! one, two, three!
  • 09-25-2020 Congrats to Audra and Lydia on their spotlight paper in NeurIPS 2020!
  • 09-18-2020 Congrats to Albert on his successful thesis proposal!
  • 09-18-2020 New paper with Albert proving strong lower bounds for shuffle-privacy and pan-privacy!
  • 07-13-2020 Why did I just join Twitter?
  • 07-12-2020 Come learn about privacy at differentialprivacy.org!
  • 06-11-2020 Just how private is private SGD? Our new paper tries to find out.
  • 06-11-2020 Introducing CoinPress: a practical algorithm for private mean and covariance estimation: code, paper!
  • 06-08-2020 Congratulations to Albert on his paper in IEEE S&P 2021!
  • 06-01-2020 Congratulations to Audra on her new position at Apple. We'll miss you!
  • 06-01-2020 Congratulations to Albert on his ICML 2020 paper!
  • 05-25-2020 Congratulations to Vikrant and Lydia on their COLT 2020 papers!
  • 04-15-2020 New primer on private statistics with Gautam Kamath: blog, pdf.



623 ISEC
805 Columbus Avenue
Khoury College of Computer Sciences
Northeastern University
Boston, MA 02118
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Google Scholar


My research is about how to use data robustly, reliably, and responsibly. I'm aiming to build firm foundations, but with a focus on the questions that will be critical for real-world systems, which I study using a mix of tools from algorithms, cryptography, security, machine learning, and statsitics. I am particularly interested in data privacy and preventing false discovery in the empirical sciences.

I am a member of the Theory Group and the Cybersecurity & Privacy Institute.

My research has been generously funded by the National Science Foundation and Google.


I am fortunate to work with a number of talented students and postdocs. My current group consists of:


I've taught a number of courses, including:

I am also the proud recipient of the Ruth and Joel Spira Outstanding Teacher Award.


I have served on the program committees of many conferences, including: IEEE S&P '21, CCS '20, ITC '20, FOCS '18, SODA '18, TCC '16, EC '16, TCC '15, STOC '15, and ITCS '15.

I also co-organize the Workshop on Theory and Practice of Differential Privacy, and differentialprivacy.org.

Students and Advising

I have been fortunate to work with a number of talented students and postdocs.

  • Current
  • Former
    • Audra McMillan, Postdoc, 2018–2020
      Now a research scientist at Apple
    • Jeff Champion, Undergraduate, 2018–2019, CRA Outstanding Undergraduate Researcher Award Finalist
      Now a Ph.D. Student at UT Austin
    • Mitali Bafna, Undergraduate, 2016
      Now a Ph.D. Student at Harvard University


  • Organizer
  • Program Committee Member
    • IEEE Symposium on Security & Privacy (S&P) 2020
    • ACM Conference on Computer and Information Secutity (CCS) 2020
    • Information Theoretic Cryptography (ITC) 2020
    • IEEE Symposium on Foundations of Computer Science (FOCS) 2018
    • SIAM Symposium on Discrete Algorithms (SODA) 2018
    • ACM Conference on Economics and Computation (EC) 2016
    • Theory of Cryptography Conference (TCC) 2015, 2016
    • ACM Symposium on Theory of Computing (STOC) 2015
    • Innovations in Theoretical Computer Science (ITCS) 2015
  • Reviewer
    • Conference on Learning Theory (COLT) 2020
    • International Conference on Machine Learning (ICML) 2018, 2020
    • International Conference on Artificial Intelligence and Statistics (AISTATS) 2017
    • Conference on Neural and Information Processing Systems (NeurIPS) 2016, 2017

Research Papers

Each list is in reverse chronological order.
Authors are ordered alphabetically unless otherwise noted.

  • Manuscripts
    • The Limits of Pan Privacy and Shuffle Privacy for Learning and Estimation arXiv
      Albert Cheu and Jonathan Ullman
  • Conference Publications
  • Journal Publications
    • Multidimensional Dynamic Pricing for Welfare Maximization
      Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman, and Zhiwei Steven Wu
      ACM Transactions on Economics and Computation, 2020
    • The Fienberg Problem: How to Allow Human Interactive Data Analysis in the Age of Differential Privacy
      Cynthia Dwork and Jonathan Ullman
      Journal of Privacy and Confidentiality, 2018. Special issue commemorating Steve Feinberg.
    • Fingerprinting Codes and the Price of Approximate Differential Privacy arXiv
      Mark Bun, Jonathan Ullman, and Salil Vadhan
      SIAM Journal on Computing, 2018
      Special issue for STOC'14
    • Computing Marginals Using MapReduce arXiv
      Foto Afrati, Shantanu Sharma Jeffrey Ullman, and Jonathan Ullman
      Journal of Computer and Systems Science, 2018
    • An Antifolk Theorem for Large Repeated Games arXiv
      Mallesh Pai, Aaron Roth, and Jonathan Ullman
      ACM Transactions on Economics and Computation, 2017
    • Between Pure and Approximate Differential Privacy arXiv
      Thomas Steinke and Jonathan Ullman
      Journal of Privacy and Confidentiality, 2017
    • When Can Limited Randomness Be Used in Repeated Games? arXiv
      Pavel Hubác̆ek, Moni Naor, and Jonathan Ullman
      Theory of Computing Systems, 2016
      Special issue for SAGT'15
    • Answering n2+o(1) Counting Queries with Differential Privacy is Hard arXiv
      Jonathan Ullman
      SIAM Journal on Computing, 2016
      Special issue for STOC'13
    • Privately Releasing Conjunctions and the Statistical Query Barrier arXiv
      Anupam Gupta, Moritz Hardt, Aaron Roth, and Jonathan Ullman
      SIAM Journal on Computing, 2013
  • Surveys and Other Writings