Senior Postdoctoral Researcher at University of Houston
Ferney-Voltaire, Auvergne-Rhône-Alpes, France
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Summary
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Senior
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Fabio Catalano is a senior postdoctoral researcher with nine years of experience applying C++ and Python to high-energy physics analyses and machine-learning integration for the ALICE experiment at CERN. Based at University of Houston and frequently working on-site at CERN, he has coordinated ML efforts across ALICE and the LHC Inter-Experimental ML Working Group, leading a 40-person analysis team and organizing international workshops. His contributions span from core back-end development in O2 and AliPhysics to DevOps work enabling ONNXRuntime and ML models in the ALICE software stack, demonstrating expertise that bridges analysis code, build systems, and ML deployment. Fabio’s research focuses on charmed-hadron measurements where he implemented ML-driven selection and systematic-error treatments (notably for Ds and Dplus analyses) now used by collaborators. He combines rigorous academic output—peer-reviewed papers and conference talks—with hands-on mentoring and system administration for research computing. Colleagues rely on him for both technical depth in detector-scale software and practical leadership in collaborative, multinational projects.
9 years of coding experience
1 year of employment as a software developer
High School Diploma, Scientific High School, 97/100, High School Diploma, Scientific High School, 97/100 at IIS Arimondi-Eula
Master's degree, Nuclear and Subnuclear Physics, 110/110 cum laude and honour mention, Master's degree, Nuclear and Subnuclear Physics, 110/110 cum laude and honour mention at Università degli Studi di Torino
Doctor of Philosophy - PhD, Physics, Cum laude, Doctor of Philosophy - PhD, Physics, Cum laude at Politecnico di Torino
Contributions:334 reviews, 8 commits, 143 PRs in 2 years 1 month
Contributions summary:Fabio contributed to the ALICE O2 analysis repository by implementing and modifying code related to Dplus analysis. Their work included updating selection criteria for the Dplus flag, adding analysis variables, and updating histograms within the Dplus task. Furthermore, they added a Dplus to piKpi selector and implemented MC matching capabilities. These contributions suggest a focus on physics analysis and data processing within the ALICE O2 framework.
Contributions:13 reviews, 88 commits, 55 PRs in 3 years 2 months
Contributions summary:Fabio's contributions focused on adding systematic errors related to the Ds meson in pp collisions at 5 TeV, specifically incorporating Machine Learning techniques. They implemented and modified code related to systematic error calculations, which included the addition of new flags and function calls within the `AliHFSystErr.cxx` file. The work also included modifications to the `AliHFSystErr.h` file to incorporate the use of machine learning and BDT selection criteria.
physicspythoncernanalysisalice
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