ksgeist/Merrimack_DSE6630
May 2025 – Jul 2025
3 Months active
Languages Used
RTextHTMLR Markdown
Technical Skills
Data AnalysisData CleaningData PreprocessingData VisualizationData WranglingExploratory Data Analysis
Jason Cicero
PROFILE
Jason Cicero
Jason Cicero developed a suite of data analytics and educational resources in the ksgeist/Merrimack_DSE6630 repository, focusing on public health and bioinformatics applications. He built R Markdown notebooks for hospital readmission analysis, spatial epidemiology, and gene expression workflows, applying R, Tidyverse, and machine learning techniques such as support vector machines and random forests. His work emphasized reproducible research, robust data cleaning, and clear documentation, consolidating educational content across R Markdown and HTML formats. By streamlining data preprocessing and visualization, Jason enabled faster onboarding for analysts and students, while ensuring that analytical pipelines remained transparent, maintainable, and aligned with stakeholder needs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
20Total
Bugs
0
Commits
20
Features
8
Lines of code
23,951
Activity Months3
Your Network
12 peopleWork History
July 2025
7 Commits • 1 Features
Jul 1, 2025July 2025: Deliverables focused on enriching educational materials in ksgeist/Merrimack_DSE6630. Implemented comprehensive updates to Demo_3 across R Markdown and HTML, consolidating content for differential gene expression, PCA and volcano plots, and model reporting (Random Forest, SVM). Enhanced DESeq2 comparison explanations, kernel performance insights, and author/content notes to improve educational value and consistency. The work included rigorous doc synchronization across formats to ensure learners have a coherent, up-to-date resource. Business value includes clearer learning paths, improved content quality, faster onboarding for analysts/students, and improved content reproducibility.
7 Commits • 1 Features
Jul 1, 2025July 2025: Deliverables focused on enriching educational materials in ksgeist/Merrimack_DSE6630. Implemented comprehensive updates to Demo_3 across R Markdown and HTML, consolidating content for differential gene expression, PCA and volcano plots, and model reporting (Random Forest, SVM). Enhanced DESeq2 comparison explanations, kernel performance insights, and author/content notes to improve educational value and consistency. The work included rigorous doc synchronization across formats to ensure learners have a coherent, up-to-date resource. Business value includes clearer learning paths, improved content quality, faster onboarding for analysts/students, and improved content reproducibility.
July 2025
June 2025
6 Commits • 2 Features
Jun 1, 2025June 2025 (Month: 2025-06) performance summary for ksgeist/Merrimack_DSE6630. Delivered two feature demos in R Markdown: Demo 2 Spatial Analysis: Public Health & Epidemiology and Gene Expression Analysis Demo Update. No major bugs fixed this month. Business value delivered includes expanded analytics capabilities for public health insights and faster, reproducible research workflows. Technologies demonstrated include R Markdown, data preparation, mapping, spatial regression with population density as explanatory variable, RNA sequencing methods, normalization, and differential expression analysis.
June 2025
6 Commits • 2 Features
Jun 1, 2025June 2025 (Month: 2025-06) performance summary for ksgeist/Merrimack_DSE6630. Delivered two feature demos in R Markdown: Demo 2 Spatial Analysis: Public Health & Epidemiology and Gene Expression Analysis Demo Update. No major bugs fixed this month. Business value delivered includes expanded analytics capabilities for public health insights and faster, reproducible research workflows. Technologies demonstrated include R Markdown, data preparation, mapping, spatial regression with population density as explanatory variable, RNA sequencing methods, normalization, and differential expression analysis.
May 2025
7 Commits • 5 Features
May 1, 2025Month: 2025-05 | Merrimack_DSE6630 delivered five features across data artefact management, demo readiness, and health analytics exploration. No major bug fixes were identified this month. The work strengthens business value by improving bookkeeping artefacts, accelerating live demos, enabling readiness for predictive modeling, and packaging assets for distribution and reuse.
7 Commits • 5 Features
May 1, 2025Month: 2025-05 | Merrimack_DSE6630 delivered five features across data artefact management, demo readiness, and health analytics exploration. No major bug fixes were identified this month. The work strengthens business value by improving bookkeeping artefacts, accelerating live demos, enabling readiness for predictive modeling, and packaging assets for distribution and reuse.
May 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability82.0%
Architecture77.0%
Performance70.4%
AI Usage30.0%
Skills & Technologies
Programming Languages
HTMLRR MarkdownText
Technical Skills
BioinformaticsData AnalysisData CleaningData PreprocessingData VisualizationData WranglingDifferential Gene Expression AnalysisDocumentationExploratory Data AnalysisFile ManagementHTMLMachine LearningPublic Health AnalyticsRR Markdown
Repositories Contributed To
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