
Over six months, contributed to the IMSA-CMS/CMSAnalysis repository by developing and refining data analysis workflows for high energy physics, focusing on background and signal modeling for Higgs and Dark Photon studies. Leveraged C++ and the ROOT framework to automate background fitting, parameterize histograms across channels, and enhance data visualization and plotting logic. Refactored particle data structures to streamline analysis pipelines and improved error handling, logging, and resource efficiency throughout the codebase. The work emphasized reproducibility, traceability, and maintainability, reducing manual steps in analysis and supporting robust, scalable workflows for complex particle physics datasets without introducing new bugs.
December 2025: Focused refactor in IMSA-CMS/CMSAnalysis to streamline particle representation for analysis by removing dxy and dz parameters from particle classes and methods. This reduces data complexity, accelerates analysis pipelines, and lowers maintenance burden while preserving essential attributes.
December 2025: Focused refactor in IMSA-CMS/CMSAnalysis to streamline particle representation for analysis by removing dxy and dz parameters from particle classes and methods. This reduces data complexity, accelerates analysis pipelines, and lowers maintenance burden while preserving essential attributes.
In November 2025, delivered consolidated Higgs fitting workflow enhancements for IMSA-CMS/CMSAnalysis, addressing both signal and background paths. The work tightened function call structure, clarified parameter handling during function creation, ensured consistent channel naming, and added enhanced logging to streamline debugging. Background improvements focused on fit function creation and histogram loading to support robust fitting workflows. Together, these changes improve fitting reliability, enable faster issue diagnosis, and lay groundwork for future extensions.
In November 2025, delivered consolidated Higgs fitting workflow enhancements for IMSA-CMS/CMSAnalysis, addressing both signal and background paths. The work tightened function call structure, clarified parameter handling during function creation, ensured consistent channel naming, and added enhanced logging to streamline debugging. Background improvements focused on fit function creation and histogram loading to support robust fitting workflows. Together, these changes improve fitting reliability, enable faster issue diagnosis, and lay groundwork for future extensions.
October 2025 Monthly Summary for IMSA-CMS/CMSAnalysis: Delivered Dark Photon Analysis plotting and data-loading enhancements, enabling end-to-end Dark Photon workflows with clear labeling of signal, background, and data. The work improved plotting configurability and data handling, enhancing reproducibility and collaboration for DP studies.
October 2025 Monthly Summary for IMSA-CMS/CMSAnalysis: Delivered Dark Photon Analysis plotting and data-loading enhancements, enabling end-to-end Dark Photon workflows with clear labeling of signal, background, and data. The work improved plotting configurability and data handling, enhancing reproducibility and collaboration for DP studies.
Month: 2025-09 — Focused on delivering scalable Higgs histogram parameterization and enhancing DarkPhoton data handling to improve modeling fidelity and analysis throughput. No standalone bug fixes were required this month; several enhancements addressed robustness and resource efficiency across the IMSA-CMS/CMSAnalysis repo, with direct business value in faster, more reliable fits and easier maintenance.
Month: 2025-09 — Focused on delivering scalable Higgs histogram parameterization and enhancing DarkPhoton data handling to improve modeling fidelity and analysis throughput. No standalone bug fixes were required this month; several enhancements addressed robustness and resource efficiency across the IMSA-CMS/CMSAnalysis repo, with direct business value in faster, more reliable fits and easier maintenance.
August 2025 — IMSA-CMS/CMSAnalysis: Implemented automated Higgs background fitting workflow and cross-year histogram aggregation to streamline background estimation, reducing manual steps and improving analysis readiness.
August 2025 — IMSA-CMS/CMSAnalysis: Implemented automated Higgs background fitting workflow and cross-year histogram aggregation to streamline background estimation, reducing manual steps and improving analysis readiness.
June 2025 — IMSA-CMS/CMSAnalysis delivered a set of enhancements to Drell-Yan background fitting and EventDumpModule, aimed at improving accuracy, provenance, and traceability to strengthen the reliability of background modeling and downstream physics results. Key outcomes include starting the fit range at 50 to reduce low-statistics bias, updating output naming for mapped vs standard fits, enabling weighted fits with proper Sumw2 histogram error handling, and reconfiguring the EventDumpModule with filters/parameters to improve statistical precision and traceability. Commits: 098364a941148c7d7b52220ee6123e715dde999a; 150de5f3d5ba26aecbc5c4991a87ca4c870a5262.
June 2025 — IMSA-CMS/CMSAnalysis delivered a set of enhancements to Drell-Yan background fitting and EventDumpModule, aimed at improving accuracy, provenance, and traceability to strengthen the reliability of background modeling and downstream physics results. Key outcomes include starting the fit range at 50 to reduce low-statistics bias, updating output naming for mapped vs standard fits, enabling weighted fits with proper Sumw2 histogram error handling, and reconfiguring the EventDumpModule with filters/parameters to improve statistical precision and traceability. Commits: 098364a941148c7d7b52220ee6123e715dde999a; 150de5f3d5ba26aecbc5c4991a87ca4c870a5262.

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