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

Updates

  • 11-30-2020 I am Privacy and Anonymity Track Chair for CCS 2021! Submit your awesome privacy research!
  • 10-28-2020 Congrats to Vikrant on his successful thesis proposal!
  • 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!

Contact

jullman@ccs.neu.edu

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

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.

Advising

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


Teaching

I am currently teaching CS 3000: Algorithms & Data

Courses I've taught in the past include:

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

Service

I am currently the Privacy and Anonymity Track chair for CCS 2021. 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
    • Albert Cheu, PhD Student (G5)
    • Vikrant Singhal, PhD Student (G5)
    • Lydia Zakynthinou, PhD Student (G4), co-advised with Huy Nguyen  Facebook Fellow
    • Konstantina Bairaktari, PhD Student (G1), co-advised with Huy Nguyen
    • Tatiana Ediger, Undergraduate
    • Stanley Wu, Undergraduate, co-advised with Alina Oprea
  • Former
    • Audra McMillan, Postdoc, 2018–2020 → Research Scientist at Apple
    • Jeff Champion, Undergraduate, 2018–2019 → Ph.D. Student at UT Austin  CRA Outstanding Undergraduate Researcher Award Finalist
    • Mitali Bafna, Undergraduate, 2016, → Ph.D. Student at Harvard University

Service



  • Organizer
  • Program Committee / Track Chair
    • Privacy and Anonymity Track Chair, ACM Conference on Computer and Information Security (CCS) 2021
  • Program Committee Member
    • IEEE Symposium on Security & Privacy (S&P): 2020, 2021
    • ACM Conference on Computer and Information Security (CCS): 2020
    • Information Theoretic Cryptography Conference (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
    • ACM 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

Teaching

I am currently teaching CS 3000: Algorithms & Data


Research Papers

Each list is in reverse chronological order.
Authors are ordered alphabetically unless otherwise noted.
Papers are tagged with Paper Code Media Misc when available

  • 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