mozilla/gecko-dev
Jun 2025 – Jul 2025
2 Months active
Languages Used
JavaScript
Technical Skills
Click-Through Rate (CTR) ModelingData ModelingDifferential PrivacyJavaScript DevelopmentNewtab PersonalizationBug Fixing
Rolf Rando
PROFILE
Rolf Rando
Worked on privacy-preserving personalization features in the mozilla/gecko-dev repository, focusing on click-through rate (CTR) modeling for newtab experiences. Developed and integrated a new CTR model type that applies differential privacy by injecting Laplace noise into click and impression data, enabling privacy guarantees while maintaining data utility. Enhanced the inferred newtab pipeline to support this model, preparing it for deployment and collaborating closely with reviewers to validate correctness. Addressed reliability by fixing bugs in interest randomization and CTR telemetry, ensuring accurate handling of zero-value cases. Utilized JavaScript and data modeling skills to improve telemetry, model implementation, and web development workflows.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
1
Lines of code
599
Activity Months2
Your Network
876 peopleSame Organization
@mozilla.com376
Shared Repositories
500
Work History
July 2025
3 Commits
Jul 1, 2025Performance-review ready monthly summary for 2025-07 focused on delivering reliability improvements and telemetry enhancements in mozilla/gecko-dev.
3 Commits
Jul 1, 2025Performance-review ready monthly summary for 2025-07 focused on delivering reliability improvements and telemetry enhancements in mozilla/gecko-dev.
July 2025
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 performance summary focused on business impact and technical achievements in privacy-preserving personalization. Delivered a new CTR model type for inferred newtab personalization with differential privacy (DP), integrating Laplace noise into CTR calculations (clicks/impressions) and enabling noise scaling for privacy guarantees. Implemented privacy-preserving noise on Merino requests as part of the DP CTR workflow (Bug 1968369), ensuring data collection preserves user privacy while maintaining utility. Prepared the inferred newtab pipeline for deployment by integrating the new model type into mozilla/gecko-dev and coordinating with reviewers. Overall, the work strengthens personalized experiences with strong privacy protections and demonstrates end-to-end DP-enabled CTR personalization from data collection to inference.
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 performance summary focused on business impact and technical achievements in privacy-preserving personalization. Delivered a new CTR model type for inferred newtab personalization with differential privacy (DP), integrating Laplace noise into CTR calculations (clicks/impressions) and enabling noise scaling for privacy guarantees. Implemented privacy-preserving noise on Merino requests as part of the DP CTR workflow (Bug 1968369), ensuring data collection preserves user privacy while maintaining utility. Prepared the inferred newtab pipeline for deployment by integrating the new model type into mozilla/gecko-dev and coordinating with reviewers. Overall, the work strengthens personalized experiences with strong privacy protections and demonstrates end-to-end DP-enabled CTR personalization from data collection to inference.
Activity
Loading activity data...
Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture82.6%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScript
Technical Skills
Bug FixingClick-Through Rate (CTR) ModelingData ModelingData PrivacyDifferential PrivacyJavaScriptJavaScript DevelopmentModel ImplementationNewtab PersonalizationTelemetryWeb Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline