chanzuckerberg/cz-benchmarks
May 2025 – May 2025
1 Month active
Languages Used
DockerfilePythonShellYAML
Technical Skills
BioinformaticsCI/CDCLI DevelopmentCommand-line Interface DevelopmentData ComparisonData Integration
prathap sridharan
PROFILE
Prathap Sridharan
During May 2025, Priya Sridharan enhanced the chanzuckerberg/cz-benchmarks repository by developing a cross-species analysis feature for the CLI, enabling multi-dataset benchmarking across species. She implemented a Python-based tool for comparing metrics between runs, supporting both JSON and YAML formats to standardize performance evaluation. Priya also updated the CI/CD workflow using Docker and GitHub Actions to automate building and pushing the transcriptformer image to ECR, improving container delivery reliability. Her work addressed reproducibility in machine learning by ensuring deterministic label prediction and stabilized Docker image builds, reflecting a strong focus on robust, maintainable bioinformatics and data science workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
7Total
Bugs
3
Commits
7
Features
3
Lines of code
385
Activity Months1
Your Network
35 people
Work History
May 2025
7 Commits • 3 Features
May 1, 2025May 2025: Key features delivered include cross-species task for cz-benchmarks CLI enabling multi-dataset cross-species analysis; CI/CD workflow updated to build/push transcriptformer image to ECR; and a cross-run metrics comparison tool to standardize benchmarking across runs. Major bugs fixed include correcting silhouette score computation for clustering evaluation, ensuring reproducibility in label prediction via deterministic RandomForestClassifier, and stabilizing Docker image builds for transcriptformer and UCE. Overall impact: enhanced cross-dataset analytical capabilities, reliable CI/CD and container delivery, and robust benchmarking with reproducible metrics and cross-run comparisons. Technologies/skills demonstrated: Python scripting, scib_metrics integration, machine learning reproducibility, Docker, GitHub Actions, ECR, CLI extensions, and multi-format metric comparisons (JSON/YAML).
7 Commits • 3 Features
May 1, 2025May 2025: Key features delivered include cross-species task for cz-benchmarks CLI enabling multi-dataset cross-species analysis; CI/CD workflow updated to build/push transcriptformer image to ECR; and a cross-run metrics comparison tool to standardize benchmarking across runs. Major bugs fixed include correcting silhouette score computation for clustering evaluation, ensuring reproducibility in label prediction via deterministic RandomForestClassifier, and stabilizing Docker image builds for transcriptformer and UCE. Overall impact: enhanced cross-dataset analytical capabilities, reliable CI/CD and container delivery, and robust benchmarking with reproducible metrics and cross-run comparisons. Technologies/skills demonstrated: Python scripting, scib_metrics integration, machine learning reproducibility, Docker, GitHub Actions, ECR, CLI extensions, and multi-format metric comparisons (JSON/YAML).
May 2025
Activity
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Quality Metrics
Correctness91.4%
Maintainability94.2%
Architecture91.4%
Performance85.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
DockerfilePythonShellYAML
Technical Skills
BioinformaticsCI/CDCLI DevelopmentCommand-line Interface DevelopmentData ComparisonData IntegrationData ScienceDevOpsDockerFile ParsingMachine LearningPythonScriptingTask Management
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