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Privacy Enhancing Technologies (PETs) for Public Health Challenge 

Unlocking Data, Advancing Impact

A global competition to create privacy-enhancing technologies to accelerate data-driven decision making in epidemiology.
The Challenge will award up to five winners USD 50,000 each.

About the Challenge

data.org is partnering with Mastercard, Harvard OpenDP, researchers from the Pontifical Javeriana University, and Sloan Foundation, to run a Privacy-Enhancing Technologies (PETs) for Public Health Challenge to unlock innovation.

While PETs have been around for a while, they have largely been a frontier technology that only a select number of regulators and a few companies in the private sector have had an interest in exploring and the luxury of doing so. But that has changed in recent years. At a global level, the G7 Data Protection and Privacy Authorities in 2023 endorsed a plan that included promoting the development and use of emerging technologies, including PETs, that can build trust and protect privacy.

PETs empower practitioners to drive progress by drawing meaningful statistical information from sensitive data while offering strong privacy guardrails. The innovation challenge will help to bring these technologies to practical applications that provide a real benefit for countries, companies and individuals.

Learn more about the application process

Challenge Timeline

Phase 1

    • Challenge Launch: January 17, 2024

    • Mandatory virtual Q&A and onboarding session for all interested participants on March 14, 2024: Please send an email with “Registration” in the subject line to petschallenge@data.org to receive information about the event.

    • Application submission ends: 7pm EST on April 25, 2024
      You can get support with your questions on Differential Privacy at the OpenDP Community

    • Awardees announcement: June 6, 2024
      Awardees are selected based on technical rigor, efficiency, usability, and value.

Phase 2

    • Tool Development: June 13 – October 30, 2024 
      Participants will work remotely to implement their proposals and develop a suite of OpenDP-based tools ready for application on data.

    • Tools Verified and Applied to Data: November 2024 
      Apply tools on data under expert guidance during a one-week in-person interactive session.

Challenge Judges

Bubacarr Bah, Ph.D.

Associate Professor and Head of Data Science

Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine

Bubacarr Bah has recently been appointed as Associate Professor and Head of Data Science in the Medical Research Council (MRC) Unit – The Gambia, at the London School of Hygiene & Tropical Medicine.

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Sean Cavany, Ph.D.

Mathematical Modeller, Nuffield Department of Medicine

University of Oxford

Dr. Sean Cavany is a mathematical modeler based in Ben Cooper’s Drug-Resistant Infections and Disease Dynamics (DRIaDD) group in the NDM Centre for Global Health Research at the University of Oxford.  

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John Derrico

Vice President, Data Strategy

Mastercard

John Derrico is Vice President of Data Sourcing and Emerging Technologies at Mastercard, where he’s responsible for the enterprise data sourcing strategy, working to create the next generation of products and solutions.

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Chapin Flynn

Senior Vice President, Transit and Urban Mobility

Mastercard

Chapin Flynn is a Senior Vice President in Mastercard Enterprise Partnerships. In that role, he is responsible for building enterprise-level partnerships that deliver growth with new revenue streams and reduce costs by driving operational efficiencies.

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Christine Task, Ph.D.

Director of Privacy Solutions and Synthetic Data

Knexus

Dr. Task’s work spans two domains at Knexus: Privacy Technology, and AI Algorithms. Regarding privacy, she researches and develops usable privacy technology solutions to real-world data privacy problems.

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Charlie Whittaker, Ph.D

Sir Henry Wellcome Research Fellow

Imperial College London

Dr. Charlie Whittaker is a Sir Henry Wellcome Research Fellow in mathematical modeling and infectious disease epidemiology at the MRC Centre for Global Infectious Disease Analysis, where his research centers around mathematical modeling of infectious disease transmission, with a focus on the detectability, dynamics, and control of pathogens with pandemic potential. 

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