Data Privacy Collaborative

Current Members


Analyzing sensitive data without revealing private information is crucial for extracting valuable insights on workplace inequalities, transportation policieshealth care outcomes, and more.

Researchers at the Hariri Institute are harnessing the power of big data while maintaining privacy protection, through secure multiparty computation (MPC), which allows collaborative data analysis without revealing private data in the process.

The Data Privacy Collaborative at the Hariri Institute, led by Mayank Varia, aims to foster cooperation among the Institute, industry, other nonprofits, and government entities to further the development of open-source platforms and to deploy at-scale software pilots that demonstrate and promote the responsible use of private data assets in real-world applications.

Members with interest in secure MPC and related privacy-enhancing technologies can join forces and work together toward the modernization and maintenance of privacy-preserving technologies. Members will meet twice annually to discuss common goals, shape research questions, and share in the communication of research results.

Interested in becoming a member of the Data Privacy Collaborative?
Learn more.

The Data Privacy Collaborative will:

• Promote the adoption of best practices for data privacy
• Develop and maintain open-source software platforms for the purposes of collaboration
• Bring secure multiparty computation, differential privacy, and blockchain technologies to bear on real-world problems
• Integrate state-of-the-art cryptographic techniques focused on security and privacy into modern big data workflows
• Enhance accessibility and usability of software tools and platforms focused on data privacy
• Demonstrate practicality of privacy-preserving solutions through pilots targeting public good applications
• Support curricular, extracurricular, and experiential learning opportunities focused on data privacy

Click here to view our multi-party computation tools on GitHub.