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Bartosz Bosak

PROFILE

Bartosz Bosak

During a three-month period, Bartosz Bosak contributed to the UCL-CCS/EasyVVUQ repository, focusing on enhancing stability, compatibility, and reliability in scientific computing workflows. He upgraded core dependencies and refactored the MCSampler API to streamline configuration and reduce maintenance overhead, using Python and TOML for dependency management and library maintenance. Bartosz addressed robustness in uncertainty quantification by fixing correctness issues in Sobol’ index bootstrapping and aligning internal components with upstream changes. He also improved error handling in PCE analysis, ensuring smoother data pipelines by returning empty arrays for missing distributions. His work demonstrated depth in numerical analysis and software engineering.

Overall Statistics

Feature vs Bugs

40%Features

Repository Contributions

6Total
Bugs
3
Commits
6
Features
2
Lines of code
218
Activity Months3

Work History

June 2025

1 Commits

Jun 1, 2025

June 2025 monthly summary for UCL-CCS/EasyVVUQ focusing on reliability improvements in data analysis pipelines and robust handling of incomplete data scenarios.

May 2025

2 Commits • 1 Features

May 1, 2025

Monthly summary for 2025-05 focusing on the EasyVVUQ work within UCL-CCS. This period highlights targeted fixes and upstream-aligned refactors that improve the reliability and business value of uncertainty quantification workflows. Highlights include: - Key features delivered: upstream alignment and robustness refactor across ensemble bootstrapping, campaign management, and internal data handling to align with upstream EasyVVUQ changes; improves compatibility and long-term maintainability. - Major bugs fixed: correctness fix for Sobol' index generation/application in QMC analysis bootstrapping, ensuring proper resampled matrices per bootstrap iteration and improving the accuracy of QMC-based uncertainty estimates. - Overall impact: enhanced reliability and accuracy of UQ analyses, reduced risk in production pipelines, and smoother upgrades with upstream changes, enabling more trustworthy decision support. - Technologies/skills demonstrated: Python-based refactoring, bootstrapping methodologies, Sobol' index handling, QMC analyses, upstream compatibility, and robustness improvements for production workflows.

April 2025

3 Commits • 1 Features

Apr 1, 2025

April 2025: Consolidated stability and compatibility for EasyVVUQ through targeted dependency upgrades and API cleanup. Delivered updated core deps, streamlined versioning strategy, and simplified the MCSampler API to reduce confusion and maintenance burden.

Activity

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Quality Metrics

Correctness86.8%
Maintainability93.4%
Architecture83.4%
Performance86.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

PythonTOML

Technical Skills

Data AnalysisDependency ManagementError HandlingLibrary MaintenanceMonte Carlo MethodsNumerical AnalysisRefactoringScientific ComputingSensitivity AnalysisSoftware DevelopmentSoftware Engineering

Repositories Contributed To

1 repo

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

UCL-CCS/EasyVVUQ

Apr 2025 Jun 2025
3 Months active

Languages Used

PythonTOML

Technical Skills

Dependency ManagementMonte Carlo MethodsRefactoringSoftware EngineeringLibrary MaintenanceNumerical Analysis

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