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cpz2024

PROFILE

Cpz2024

Developed privacy-preserving graph and manifold learning modules for the secretflow/spu repository, focusing on secure analytics for enterprise environments. The work introduced implementations of Dijkstra’s algorithm, Isomap, and Spectral Embedding, as well as a privacy-preserving variant of Floyd-Warshall, all designed to operate within secure multi-party computation frameworks. Leveraging Python and Bazel, the developer ensured that each module aligned with strict privacy requirements while maintaining performance goals. Comprehensive end-to-end tests and emulations were added to validate both privacy guarantees and correctness, resulting in robust, production-ready features that enable secure dimensionality reduction and graph analytics in privacy-sensitive applications.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,531
Activity Months1

Your Network

27 people

Work History

April 2025

1 Commits • 1 Features

Apr 1, 2025

April 2025 — Delivered privacy-preserving graph and manifold learning capabilities in secretflow/spu, with new modules for Dijkstra, Isomap, and Spectral Embedding, alongside a privacy-preserving Floyd-Warshall variant. Implemented end-to-end tests and emulations to verify privacy guarantees. Focused on enabling secure graph analytics with enterprise-grade privacy.

Activity

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Quality Metrics

Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

BazelPython

Technical Skills

BazelDimensionality ReductionGraph AlgorithmsMachine LearningPythonSecure Multi-Party Computation (MPC)

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

secretflow/spu

Apr 2025 Apr 2025
1 Month active

Languages Used

BazelPython

Technical Skills

BazelDimensionality ReductionGraph AlgorithmsMachine LearningPythonSecure Multi-Party Computation (MPC)