Program (tentative)

(all listed times are Eastern time)

9:00-9:05 Opening Remarks
9:05-9:45 Low-Communication Algorithms for Private Federated Data Analysis
Kunal Talwar (Invited Speaker)
9:45-10:00 Query Release via the Johnson Lindenstrauss Lemma
Aleksandar Nikolov
10:00-10:30 Break
10:30-12:00 Poster Session 1
12:00-1:30 Lunch Break
1:30-2:10 Private Mean Estimation with Connections to Robustness
Lydia Zakynthinou (Invited Speaker)
2:10-2:40 Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases
Priyanka Nanayakkara, Johes Bater, Xi He, Jessica Hullman, Jennie Rogers

Widespread Underestimation of Sensitivity in Differentially Private Libraries and How to Fix It
Sílvia Casacuberta, Michael Shoemate, Salil Vadhan, Connor Wagaman
2:40-3:00 Virtual Talks 1
3:00-3:25 Break
3:25-3:45 Virtual Talks 2
3:45-4:30 Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, YinTat Lee, Daogao Liu

The Price of Differential Privacy under Continual Observation
Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith

Unlocking High-Accuracy Differentially Private Image Classification through Scale
Soham De, Leonard Berrada, Jamie Hayes, Samuel L Smith, Borja Balle
4:30-6:00 Poster Session 2

Accepted Papers

Accepted papers will be presented as in-person posters or pre-recorded lightning talks. Additionally, six papers were selected as spotlight talks.

Poster Session 1:

Poster Session 2:

Pre-recorded Lightning Talks (Playlist):


Differential privacy is a promising approach to privacy-preserving data analysis. Differential privacy provides strong worst-case guarantees about the harm that a user could suffer from participating in a differentially private data analysis, but is also flexible enough to allow for a wide variety of data analyses to be performed with a high degree of utility. Having already been the subject of a decade of intense scientific study, it has also now been deployed at government agencies such as the U.S. Census Bureau and companies including Apple, Google, Facebook, and Microsoft.

Researchers in differential privacy span many distinct research communities, including algorithms, computer security, cryptography, databases, data mining, machine learning, statistics, programming languages, social sciences, and law. This workshop will bring researchers from these communities together to discuss recent developments in both the theory and practice of differential privacy.

Specific topics of interest for the workshop include (but are not limited to):


The goal of TPDP is to stimulate the discussion on the relevance of differentially private data analyses in practice. For this reason, we seek contributions from different research areas of computer science and statistics.

Authors are invited to submit a short abstract (4 pages maximum, with unlimited references and appendices (only read at reviewer's discretion)) of their work. Submissions are single-blind (non-anonymized), and there is no prescribed style file (though authors should be considerate of reviewers in their selection).

Submissions will undergo a lightweight review process and will be judged on originality, relevance, interest and clarity. Submission should describe novel work or work that has already appeared elsewhere but that can stimulate the discussion between different communities at the workshop. Accepted abstracts will be presented at the workshop either as a talk or a poster.

The workshop will not have formal proceedings and is not intended to preclude later publication at another venue.

Selected papers from the workshop will be invited to submit a full version of their work for publication in a special issue of the Journal of Privacy and Confidentiality.

Call for Papers: PDF

Invited Speakers

Important Dates

Abstract Submission
May 6, 2022 (AoE)
June 13, 2022
July 22, 2022

Organizing and Program Committee

Submission website

OpenReview TPDP 2022
Note the “open” features of OpenReview will not be used, and visibility of all submissions, reviews, and accepted papers will be restricted to the program committee (similar other systems like EasyChair, CMT, HotCRP, etc.).