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

Updates

  • 02-17-2021 New paper on private synthetic data!
  • 02-16-2021 New paper with Konstantina on fair cohort selection!
  • 02-06-2021 Congrats to Albert on his STOC 2021 paper!
  • 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!

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
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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 7880: Privacy in Statistics and Machine Learning

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 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