
During November 2024, Yen-Jie Lee developed end-to-end analysis capabilities for the MITHIGAnalysis2024 repository, focusing on high energy physics workflows. He built a Z-hadron correlation analysis framework and enhanced D meson analysis by implementing kinematic-bin filtering, ROOT ntuple output, and RooFit-based mass fitting. Leveraging C++ and shell scripting, he introduced parallel processing to accelerate data throughput and designed a project environment setup script for streamlined deployment. His work emphasized reproducible, configurable workflows and robust data handling, enabling cross-collision-type analysis. The depth of engineering addressed both performance and scientific rigor, supporting systematic studies and efficient physics analysis cycles.

This month delivered end-to-end analysis capabilities and production-quality data products for MITHIGAnalysis2024, with clear business value through faster insights, reproducible workflows, and cross-collision-type analysis readiness.
This month delivered end-to-end analysis capabilities and production-quality data products for MITHIGAnalysis2024, with clear business value through faster insights, reproducible workflows, and cross-collision-type analysis readiness.
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