Privacy-Preserving Advertising Measurement

Enabling accurate advertising measurement while protecting user privacy at TikTok.

Overview

At TikTok Privacy Innovation Lab, I work on developing privacy-preserving technologies for advertising measurement. This project addresses the critical challenge of measuring advertising effectiveness while protecting user privacy.

Research Areas

Differential Privacy for Ad Measurement

Developing differentially private mechanisms for:

  • Conversion attribution
  • Reach and frequency measurement
  • Audience analytics

Privacy-Utility Trade-offs

Analyzing and optimizing the balance between:

  • Privacy guarantees for users
  • Accuracy requirements for advertisers
  • Scalability for production systems

Impact

This work contributes to the broader industry effort to transition to privacy-preserving advertising measurement, including:

  • Supporting privacy regulations (GDPR, CCPA)
  • Enabling measurement without third-party cookies
  • Building trust with users through transparent privacy practices

Experience

Research Intern, TikTok (Summer 2023)

  • Developed privacy-preserving measurement systems
  • Collaborated with cross-functional teams
  • Published internal research findings