ksgeist/Merrimack_DSE6630
May 2025 – Jun 2025
2 Months active
Languages Used
RMarkdown
Technical Skills
Data AnalysisData CleaningData MergingData PreprocessingData VisualizationDocumentation
Steph Garofalo
PROFILE
Steph Garofalo
Contributed to the ksgeist/Merrimack_DSE6630 repository by building a reproducible analytics foundation for healthcare data, focusing on pneumonia outcomes. Established project scaffolding and robust data pipelines in R, leveraging Tidyverse for data wrangling, cleaning, and preprocessing. Developed spatial regression models, including SAR, SEM, and SDM, to analyze pneumonia readmission patterns and public health outcomes. Enhanced documentation and reproducibility through R Markdown, clarifying model interpretations and improving workflow transparency. Addressed data access and NA handling issues, enabling reliable demos and rapid experimentation. The work emphasized statistical modeling, spatial analysis, and clear documentation to support actionable insights in healthcare analytics.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
11Total
Bugs
1
Commits
11
Features
5
Lines of code
6,717
Activity Months2
Your Network
25 peopleWork History
June 2025
3 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for ksgeist/Merrimack_DSE6630: Focused on delivering business-value through spatial epidemiology analytics and robust data pipelines. Key advancements include spatial regression modeling for pneumonia readmission, a robust data loading/preprocessing pipeline, and documentation enhancements to mortality analysis, enabling reproducibility, clearer interpretation, and faster insight generation for healthcare outcomes.
3 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for ksgeist/Merrimack_DSE6630: Focused on delivering business-value through spatial epidemiology analytics and robust data pipelines. Key advancements include spatial regression modeling for pneumonia readmission, a robust data loading/preprocessing pipeline, and documentation enhancements to mortality analysis, enabling reproducibility, clearer interpretation, and faster insight generation for healthcare outcomes.
June 2025
May 2025
8 Commits • 2 Features
May 1, 2025May 2025: Delivered essential scaffolding and environment setup for the Merrimack_DSE6630 R project, fixed a demo data path/binning issue to ensure reliable data access and NA handling, and completed Project 1 analytics preparation (documentation, pneumonia-focused data wrangling, feature engineering, and modeling plan). These efforts establish a reproducible analytics foundation, enable immediate demos, and set the stage for rapid experimentation and reliable results.
May 2025
8 Commits • 2 Features
May 1, 2025May 2025: Delivered essential scaffolding and environment setup for the Merrimack_DSE6630 R project, fixed a demo data path/binning issue to ensure reliable data access and NA handling, and completed Project 1 analytics preparation (documentation, pneumonia-focused data wrangling, feature engineering, and modeling plan). These efforts establish a reproducible analytics foundation, enable immediate demos, and set the stage for rapid experimentation and reliable results.
Activity
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Quality Metrics
Correctness89.0%
Maintainability85.6%
Architecture80.0%
Performance76.4%
AI Usage36.4%
Skills & Technologies
Programming Languages
MarkdownR
Technical Skills
Data AnalysisData CleaningData MergingData PreprocessingData VisualizationData WranglingDocumentationExploratory Data AnalysisExploratory Data Analysis (EDA)Feature EngineeringMachine LearningProject SetupR DevelopmentR ProgrammingSpatial Analysis
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