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

Updates

I am on sabbatical in Palo Alto for the 2021-22 academic year!
  • 05-15-2022 New paper on model updates and membership-inference attacks!
  • 05-14-2022 One paper acceped to COLT 2022!
  • 04-25-2022 Lydia is receiving the PhD Research Award from Khoury!
  • 11-09-2021 New paper on computationally efficient private covariance estimation!
  • 10-13-2021 I gave a talk at the CMU theory lunch.
  • 09-28-2021 Congratulations to Lydia on her NeurIPS 2021 Spotlight!
  • 09-16-2021 I gave a talk on the complexity of differenital privacy at the Simons Institute.
  • 07-22-2021 Congratulations to Dr. Vikrant Singhal, defender of the thesis!
  • 06-28-2021 New paper with Lydia on private estimation!
  • 06-09-2021 I've been promoted to Associate Professor with tenure! Thanks to everyone who helped me get here!
  • 05-08-2021 One paper acceped to ICML 2021!
  • 04-07-2021 Congratulations to Dr. Albert Cheu, defender of the thesis!

Contact

jullman [at] ccs [dot] neu [dot] edu

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

My research centers on the foundations of privacy for machine learning and statistics, in particular differential privacy and its surprising interplay with other topics in such as statistical validity, robustness, cryptography, and fairness. My background is in theoretical computer science, but increasingly my work spans algorithms, cryptography, machine learning, statistics, and security.

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

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

Advising

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


Teaching

In Fall 2022 I am teaching CS 7800 / CS 4810: Advanced Algorithms

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

I have served on the program committees of many conferences, including: FAccT '22 AAAI '22 CCS '21 (Privacy Track Chair), IEEE S&P '21, CCS '20, ITC '20, FOCS '18, SODA '18, TCC '16, EC '16, TCC '15, STOC '15, and ITCS '15.

Students and Advising

I have been fortunate to work with many talented students and postdocs.


Service



  • Organizer
  • Program Committee Chair / Track Chair
    • Privacy and Anonymity Track Chair, ACM Conference on Computer and Information Security (CCS) 2021
  • Program Committee Member / Area Chair
    • ACM Conference on Fairness, Accountability, and Transparency (FAccT): 2022
    • AAAI Conference on Artificial Intelligence: 2022
    • 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 7880: Privacy in Statistics and Machine Learning


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