Lauren Hay is a postdoctoral researcher and experimental high-energy physicist with eight years of experience probing QCD using CMS data and developing computational solutions for future HEP experiments. Based at Brown after completing a PhD at the University at Buffalo and research stints at CERN, she blends hands-on detector analysis with software engineering to push storage and runtime limits. Her contributions to the widely used CMS Offline Software (cmssw), including hardening the UniqueMerger class, show a practical focus on robustness and maintainability in critical experiment code. She also brings teaching and mentoring experience from UB and a knack for applying AI and novel computational techniques to real-world physics workflows.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Elementary Particle Physics, Doctor of Philosophy - PhD Elementary Particle Physics at University at Buffalo
Contributions:13 reviews, 35 commits, 21 PRs in 2 years 7 months
Contributions summary:Lauren primarily worked on the `UniqueMerger` class within the `CommonTools/UtilAlgos` directory. Their contributions include implementing protection against invalid pointers, fixing code checks, and adding flags for skipping and warning. The user also addressed header file inclusions. These changes suggest a focus on improving the stability and robustness of the CMS offline software.
Contributions:3 PRs, 73 pushes, 1 branch in 3 years 5 months
pythonjetmeasurementgluonmass
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