
Worked extensively on the music-computing/amads repository, delivering robust features for music notation analysis, score comparison, and cross-format I/O. Focused on Python and JavaScript, the work included modernizing MIDI and MusicXML import/export, enhancing timing accuracy, and implementing browser-based and notebook score visualization. Emphasized code quality through comprehensive testing, CI/CD improvements, and detailed documentation. Integrated libraries such as MIDO, music21, and prettymidi to expand compatibility and reliability. Refactored APIs for clarity and maintainability, improved error handling, and streamlined contributor workflows. The engineering approach prioritized data fidelity, extensibility, and reproducibility, enabling researchers and developers to build reliable, scalable music analytics pipelines.
July 2026 performance summary for music-computing/amads: Delivered two core feature updates and updated the CI/testing framework to ensure compatibility with modern runtimes. The changes improve correctness and stability of music notation I/O, strengthen export reliability, and expand the test matrix to reduce release risk.
July 2026 performance summary for music-computing/amads: Delivered two core feature updates and updated the CI/testing framework to ensure compatibility with modern runtimes. The changes improve correctness and stability of music notation I/O, strengthen export reliability, and expand the test matrix to reduce release risk.
June 2026: Delivered core improvements in MIDI I/O, score timing accuracy, and documentation stability for music-computing/amads. The work tightened cross-format interoperability, expanded test coverage, and reduced reliance on a single MIDI backend, enabling safer extensibility and faster onboarding. Key outcomes include a default shift to MIDO for MIDI import/export, support for zero-duration notes in exports, enhanced time-unit handling across formats, improved measure timing for multi-staff scores, and a more stable docs site.
June 2026: Delivered core improvements in MIDI I/O, score timing accuracy, and documentation stability for music-computing/amads. The work tightened cross-format interoperability, expanded test coverage, and reduced reliance on a single MIDI backend, enabling safer extensibility and faster onboarding. Key outcomes include a default shift to MIDO for MIDI import/export, support for zero-duration notes in exports, enhanced time-unit handling across formats, improved measure timing for multi-staff scores, and a more stable docs site.
May 2026 (2026-05) monthly summary for music-computing/amads: Implemented notebook-based music score visualization with integrated I/O workflows, restructured IO to dispatch at high-level by format and preferences and expose low-level conversions, enabling clean, notebook-friendly score displays and image generations. Delivered comprehensive notation import/export enhancements including improved handling of clefs and ornaments, grace notes export, and clarified pitch naming; refactored the Clef module and expanded tests to cover ornament behavior (with caveats for Partitura). Fixed critical MusicXML input issues (tied notes resolution) and introduced notes_compare() to facilitate score-difference analysis, plus remove_overlap() to eliminate unison overlaps across voices. Improved score timing fidelity with better duration calculations, padding of pickup measures, and corrected time maps; added tests for time signatures and maps. Completed documentation updates for event handling and external references. These changes contribute to higher data fidelity, more reliable notebook visualization, and stronger test coverage, enabling researchers to reproduce musical analyses and streamline data pipelines.
May 2026 (2026-05) monthly summary for music-computing/amads: Implemented notebook-based music score visualization with integrated I/O workflows, restructured IO to dispatch at high-level by format and preferences and expose low-level conversions, enabling clean, notebook-friendly score displays and image generations. Delivered comprehensive notation import/export enhancements including improved handling of clefs and ornaments, grace notes export, and clarified pitch naming; refactored the Clef module and expanded tests to cover ornament behavior (with caveats for Partitura). Fixed critical MusicXML input issues (tied notes resolution) and introduced notes_compare() to facilitate score-difference analysis, plus remove_overlap() to eliminate unison overlaps across voices. Improved score timing fidelity with better duration calculations, padding of pickup measures, and corrected time maps; added tests for time signatures and maps. Completed documentation updates for event handling and external references. These changes contribute to higher data fidelity, more reliable notebook visualization, and stronger test coverage, enabling researchers to reproduce musical analyses and streamline data pipelines.
April 2026 monthly summary for music-computing/amads: Delivered browser-based OSMD Score Display, hardened the Sequence.slice API, and streamlined CI/CD to accelerate feedback. The work advances accessibility, API reliability, and release velocity, delivering clear business value for users and stakeholders.
April 2026 monthly summary for music-computing/amads: Delivered browser-based OSMD Score Display, hardened the Sequence.slice API, and streamlined CI/CD to accelerate feedback. The work advances accessibility, API reliability, and release velocity, delivering clear business value for users and stakeholders.
February 2026: Delivered key features and reliability improvements for the AMADS project. Implemented display and I/O enhancements for musical scores with cross-format support (PDF and MuseScore), and performed substantial cleanup of the read_score/write_score utilities. Strengthened CI and testing reliability by conditioning test runs on available dependencies (R, LilyPond), suppressing GUI apps during tests, and updating configuration to skip tests when dependencies are missing, resulting in more stable CI across environments. Expanded tonal analysis capabilities and R scripting utilities, including improved pitch-class distribution handling, integration of self-organizing maps for tonal analysis, and new R script helpers with better module organization. Outcome: clearer, more usable score I/O, faster-safe CI cycles, and enhanced analysis capabilities enabling more robust music analytics.
February 2026: Delivered key features and reliability improvements for the AMADS project. Implemented display and I/O enhancements for musical scores with cross-format support (PDF and MuseScore), and performed substantial cleanup of the read_score/write_score utilities. Strengthened CI and testing reliability by conditioning test runs on available dependencies (R, LilyPond), suppressing GUI apps during tests, and updating configuration to skip tests when dependencies are missing, resulting in more stable CI across environments. Expanded tonal analysis capabilities and R scripting utilities, including improved pitch-class distribution handling, integration of self-organizing maps for tonal analysis, and new R script helpers with better module organization. Outcome: clearer, more usable score I/O, faster-safe CI cycles, and enhanced analysis capabilities enabling more robust music analytics.
January 2026 performance summary for music-computing/amads: Delivered a new Musical score comparison module with enhanced IO for MIDI/XML import/export, boosting interoperability and data handling. Established default readers/writers (pretty_midi for MIDI, music21 for XML) and hardened IO with broader test coverage and configurable IO warnings, increasing reliability of data pipelines. Also stabilized cross-version compatibility and test reliability across Python versions. Addressed Python 3.10-related test issues by converting numpy floats to Python floats, fixed a merge-induced demo break (amads.utils/core.utils integration) that affected 334 tests, and implemented robust key number validation to avoid floating-point edge-case issues. Enhanced documentation, CI/CD workflows, and code quality checks. Added typing_extensions, improved mkdocs build stability, and updated test infrastructure to run with temporary test files. These changes improve maintainability, accelerate onboarding for contributors, and reduce risk for users relying on accurate score IO and cross-version demos.
January 2026 performance summary for music-computing/amads: Delivered a new Musical score comparison module with enhanced IO for MIDI/XML import/export, boosting interoperability and data handling. Established default readers/writers (pretty_midi for MIDI, music21 for XML) and hardened IO with broader test coverage and configurable IO warnings, increasing reliability of data pipelines. Also stabilized cross-version compatibility and test reliability across Python versions. Addressed Python 3.10-related test issues by converting numpy floats to Python floats, fixed a merge-induced demo break (amads.utils/core.utils integration) that affected 334 tests, and implemented robust key number validation to avoid floating-point edge-case issues. Enhanced documentation, CI/CD workflows, and code quality checks. Added typing_extensions, improved mkdocs build stability, and updated test infrastructure to run with temporary test files. These changes improve maintainability, accelerate onboarding for contributors, and reduce risk for users relying on accurate score IO and cross-version demos.
May 2025 focused on strengthening MIDI ingestion and parsing robustness in the music-computing/amads repo, delivering substantial improvements in performance, reliability, and cross-compatibility for downstream workflows.
May 2025 focused on strengthening MIDI ingestion and parsing robustness in the music-computing/amads repo, delivering substantial improvements in performance, reliability, and cross-compatibility for downstream workflows.
April 2025: Implemented a major overhaul of AMADS core music representation, standardized plotting interfaces, modernized the Pitch API, and added robust initialization defaults. These changes improve correctness, consistency, and developer experience, enabling faster feature delivery and fewer runtime errors in downstream users.
April 2025: Implemented a major overhaul of AMADS core music representation, standardized plotting interfaces, modernized the Pitch API, and added robust initialization defaults. These changes improve correctness, consistency, and developer experience, enabling faster feature delivery and fewer runtime errors in downstream users.
March 2025 monthly summary for music-computing/amads: Key feature delivered: Documentation Workflow Enhancements for Contributors. Updated guidelines cover installation via pip, pre-commit workflow, upstream integration, and added live-reload during docs development through sphinx-autobuild. No major bugs fixed this month. Overall impact: streamlined contributor onboarding and faster documentation iteration, improving collaboration and project sustainability. Technologies/skills demonstrated: Sphinx documentation, sphinx-autobuild live-reload, pip packaging, pre-commit integration, upstream workflows, Git hygiene.
March 2025 monthly summary for music-computing/amads: Key feature delivered: Documentation Workflow Enhancements for Contributors. Updated guidelines cover installation via pip, pre-commit workflow, upstream integration, and added live-reload during docs development through sphinx-autobuild. No major bugs fixed this month. Overall impact: streamlined contributor onboarding and faster documentation iteration, improving collaboration and project sustainability. Technologies/skills demonstrated: Sphinx documentation, sphinx-autobuild live-reload, pip packaging, pre-commit integration, upstream workflows, Git hygiene.
In 2025-01, delivered a centralized algorithm implementations tracking reference for the music-computing/amads project, enabling transparent progress tracking and assignment visibility via a dedicated Google Sheet. This governance/utility feature improves planning accuracy, onboarding speed, and cross-team coordination. The month focused on process improvements and documentation rather than feature-heavy changes, establishing foundational artifacts for future automation and reporting.
In 2025-01, delivered a centralized algorithm implementations tracking reference for the music-computing/amads project, enabling transparent progress tracking and assignment visibility via a dedicated Google Sheet. This governance/utility feature improves planning accuracy, onboarding speed, and cross-team coordination. The month focused on process improvements and documentation rather than feature-heavy changes, establishing foundational artifacts for future automation and reporting.
December 2024 monthly summary for music-computing/amads. Focused on delivering distribution modeling capabilities and 2D analysis for MIDI note durations, with reusable plotting-ready APIs and improved plotting workflow. Implemented a unified Distribution API to support both 1D and 2D visualizations and updated example scripts to demonstrate the end-to-end flow. Also started refining core dependencies to optimize load time for plotting.
December 2024 monthly summary for music-computing/amads. Focused on delivering distribution modeling capabilities and 2D analysis for MIDI note durations, with reusable plotting-ready APIs and improved plotting workflow. Implemented a unified Distribution API to support both 1D and 2D visualizations and updated example scripts to demonstrate the end-to-end flow. Also started refining core dependencies to optimize load time for plotting.

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