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

Updates

  • 10-01-2019 New paper on local differential privacy.
  • 11-19-2019 Congrats to Albert on his new student-only paper!
  • 10-01-2019 I received the Ruth and Joel Spira Outstanding Teacher Award!
  • 09-26-2019 New paper on manipulation attacks in local differential privacy.
  • 09-03-2019 Congratulations to Vikrant on his NeurIPS paper!
  • 07-30-2019 Congratulations to Jeff on his CCS paper!
  • 05-28-2019 New paper on secure computation for differential privacy with undergraduate Jeff Champion!
  • 05-28-2019 Two new papers on private statistics: one, two!
  • 04-18-2019 Congratulations to Vikrant on his COLT paper!
  • 03-23-2019 My daughter Miriam was born!
  • 02-08-2019 Congratulations to Audra on her STOC paper!
  • 01-29-2019 Congratulations to Albert on his Eurocrypt 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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Bio
CV
Google Scholar

Research

I am a theoretical computer scientist. The focus of my research is how to make data analysis more reliable and better aligned with societal values. A particular focus of mine is statistical data privacy, which studies how and when we can analyze a dataset without revealing information about the individuals in that dataset. I am also interesting in how to prevent false discovery in the empirical sciences. I study these and other questions using tools from cryptography, machine learning, algorithms, and game theory.

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've taught a number of courses, including:

Service

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

I also organize the Workshop on Theory and Practice of Differential Privacy

Students and Advising

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


Service



  • Organizer
  • Program Committee Member
    • 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
    • International Conference on Machine Learning (ICML) 2018
    • 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.


  • Manuscripts
  • Conference Publications
  • Journal Publications
    • 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, 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
  • Workshop Publications
    • Private Identity Testing for High-Dimensional Distributions arXiv
      Clément Canonne, Gautam Kamath, Audra McMillan, Jonathan Ullman, and Lydia Zakynthinou
      Workshop on Privacy in Machine Learning (PriML'19)
    • Manipulation Attacks Against Locally Differentially Private Algorithms
      Albert Cheu, Adam Smith, and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'19)
    • Private Identity Testing for High-Dimensional Distributions arXiv
      Clément Canonne, Gautam Kamath, Audra McMillan, Jonathan Ullman, and Lydia Zakynthinou
      Workshop on Theory and Practice of Differential Privacy (TPDP'19)
    • Efficiently Estimating Erdős-Rényi Graphs with Differential Privacy arXiv
      Adam Sealfon and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'19)
    • Distributed Differential Privacy via Shuffling arXiv
      Albert Cheu, Adam Smith, Jonathan Ullman, David Zeber, and Maxim Zhilyaev
      Workshop on Theory and Practice of Differential Privacy (TPDP'18)
    • Privately Learning High-Dimensional Distributions arXiv Talk Video
      Gautam Kamath, Jerry Li, Vikrant Singhal, and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'18)
    • Local Differential Privacy for Evolving Data arXiv
      Matthew Joseph, Aaron Roth, Jonathan Ullman, and Bo Waggoner
      Workshop on Theory and Practice of Differential Privacy (TPDP'18)
      Selected for a Contributed Talk
    • Competitive Differentially Private Algorithms for Interactive Queries
      Aleksandar Nikolov and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'17)
    • Some Pairs Problems arXiv
      Jeffrey D. Ullman and Jonathan Ullman
      ACM Workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR'16)
    • Make Up Your Mind: The Price of Online Queries in Differential Privacy arXiv
      Mark Bun, Thomas Steinke, and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'16)
      Selected for a Contributed Talk
    • Between Pure and Approximate Differential Privacy arXiv
      Thomas Steinke and Jonathan Ullman
      Workshop on Theory and Practice of Differential Privacy (TPDP'15)
    • On the Zero-Error Capacity Threshold for Deletion Channels arXiv
      Ian Kash, Michael Mitzenmacher, Justin Thaler, and Jonathan Ullman
      Information Theory and Applications Workshop (ITA'11)
  • Surveys and Other Writings
    • Technical Perspective: Building a Safety Net for Data Reuse CACM
      Jonathan Ullman
      Communications of the ACM, 2017
    • Exposed! A Survey of Attacks on Private Data ARSIA
      Cynthia Dwork, Adam Smith, Thomas Steinke, and Jonathan Ullman
      Annual Review of Statistics and its Applications