stjude/proteinpaint
Feb 2026 – May 2026
4 Months active
Languages Used
HDF5JavaScriptPythonTypeScriptNone
Technical Skills
Command line interface (CLI)Data processingData validationError handlingHDF5HDF5 handling
Pramesh Shakya
PROFILE
Pramesh Shakya
Over four months, contributed to the stjude/proteinpaint repository by building and enhancing features for data visualization, AI-driven analytics, and backend data processing. Developed robust querying and validation pipelines for DNA methylation data using Python and HDF5, improving data integrity and downstream analytics. Integrated AI chat endpoints and LLM providers, enabling natural language-driven term inference and visualization configuration. Enhanced scatter and matrix plot capabilities, refined entity resolution, and improved user experience through chat UI updates. Applied TypeScript and Node.js for backend and API development, emphasizing clean code, comprehensive testing, and maintainability while addressing both scientific computing and full stack requirements.
Overall Statistics
Feature vs Bugs
78%Features
Repository Contributions
56Total
Bugs
6
Commits
56
Features
21
Lines of code
7,165
Activity Months4
Your Network
46 peopleSame Organization
@stjude.org17
PPTeam CIMember
aacicMember
Andrew WillemsMember
Colleen ReillyMember
Gavriel MattMember
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Haidong YiMember
Jay KnightMember
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Shared Repositories
29
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Airen Zaldivar PerazaMember
Andrew WillemsMember
congyu-luMember
Colleen ReillyMember
Edward MalinowskiMember
Gavriel MattMember
gavrielmMember
Jay KnightMember
Work History
May 2026
15 Commits • 6 Features
May 1, 2026May 2026 monthly summary for stjude/proteinpaint focusing on key features delivered, bugs fixed, impact, and skills demonstrated. Highlights include Scatter Plot Enhancements, Matrix Plot Improvements, Query Filtering and Entity Resolution enhancements, Azure LLM Provider integration, Chat UI Enhancements, and Internal Quality improvements. These efforts delivered tangible business value: improved data visualization accuracy and flexibility, more robust query processing and logging, expanded language model options, a better user experience, and maintainable code quality.
15 Commits • 6 Features
May 1, 2026May 2026 monthly summary for stjude/proteinpaint focusing on key features delivered, bugs fixed, impact, and skills demonstrated. Highlights include Scatter Plot Enhancements, Matrix Plot Improvements, Query Filtering and Entity Resolution enhancements, Azure LLM Provider integration, Chat UI Enhancements, and Internal Quality improvements. These efforts delivered tangible business value: improved data visualization accuracy and flexibility, more robust query processing and logging, expanded language model options, a better user experience, and maintainable code quality.
May 2026
April 2026
26 Commits • 12 Features
Apr 1, 2026April 2026 performance highlights for stjude/proteinpaint focused on accelerating data-driven exploration, stabilizing core plotting/analysis pipelines, and improving developer UX. The team delivered several end-to-end enhancements, improved observability, and tightened quality across the codebase.
April 2026
26 Commits • 12 Features
Apr 1, 2026April 2026 performance highlights for stjude/proteinpaint focused on accelerating data-driven exploration, stabilizing core plotting/analysis pipelines, and improving developer UX. The team delivered several end-to-end enhancements, improved observability, and tightened quality across the codebase.
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for stjude/proteinpaint: Delivered AI-driven enhancements to visualization via a chat-assisted term inference feature. This work adds an AI chat endpoint and backend logic to classify user prompts and infer appropriate term types for visualizations, enabling faster, more accurate data exploration. No major bugs fixed this month. Overall impact includes improved user experience, reduced manual configuration for visualizations, and a stronger foundation for future AI-assisted visualization capabilities. Core technologies demonstrated include AI chat integration, endpoint development, query classification, and backend-visualization interoperability.
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for stjude/proteinpaint: Delivered AI-driven enhancements to visualization via a chat-assisted term inference feature. This work adds an AI chat endpoint and backend logic to classify user prompts and infer appropriate term types for visualizations, enabling faster, more accurate data exploration. No major bugs fixed this month. Overall impact includes improved user experience, reduced manual configuration for visualizations, and a stronger foundation for future AI-assisted visualization capabilities. Core technologies demonstrated include AI chat integration, endpoint development, query classification, and backend-visualization interoperability.
March 2026
February 2026
14 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for stjude/proteinpaint focusing on DNA methylation analytics enhancements and validation/maintenance. Delivered robust data querying for beta-values from HDF5, reinforced data integrity, and improved testing/documentation to support downstream analytics and UI reliability.
February 2026
14 Commits • 2 Features
Feb 1, 2026February 2026 monthly summary for stjude/proteinpaint focusing on DNA methylation analytics enhancements and validation/maintenance. Delivered robust data querying for beta-values from HDF5, reinforced data integrity, and improved testing/documentation to support downstream analytics and UI reliability.
Activity
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Quality Metrics
Correctness87.0%
Maintainability84.0%
Architecture84.4%
Performance84.0%
AI Usage46.8%
Skills & Technologies
Programming Languages
HDF5JavaScriptNonePythonTypeScript
Technical Skills
AI DevelopmentAI IntegrationAI integrationAPI DevelopmentAPI developmentAPI integrationBackend DevelopmentCommand line interface (CLI)Data processingData validationError handlingHDF5HDF5 handlingJSON handlingJavaScript
Repositories Contributed To
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