Thomas Vuillaume is a research engineer and astrophysicist with 10 years' experience building AI-driven data analysis pipelines for physics experiments at CNRS, notably for the Cherenkov Telescope Array. He combines a PhD-level research background with hands-on software development—contributing to prominent open-source projects like Gammapy and ctapipe where he improved gamma-ray analysis tools, visualization, and model-training utilities. Based in Annecy, he routinely bridges instrument-level data processing and applied machine learning while also training students and early-career researchers. Pragmatic and detail-oriented, he brings both production-grade coding practices (unit tests, documentation, geometry handling) and domain expertise in high-energy astrophysics to complex data challenges.
10 years of coding experience
3 years of employment as a software developer
Doctorat de philosophie, Doctorat de philosophie at Université Grenoble Alpes
Diplôme d'ingénieur, Diplôme d'ingénieur at Grenoble INP - Phelma
Bachelor's degree, Bachelor's degree at Lycée Victor Hugo
Low-level data processing pipeline software for CTAO or similar arrays of Imaging Atmospheric Cherenkov Telescopes
Role in this project:
Back-end Developer
Contributions:56 reviews, 31 commits, 21 PRs in 4 years 5 months
Contributions summary:Thomas primarily focused on improving the `RegressorClassifierBase` class and adding example notebooks to the project. They introduced feature dictionaries to track used features for model training and implemented unit tests for the `show_importances` method. Additionally, the user added an example notebook to convert hex camera geometry to square grid and back, demonstrating the handling of camera geometries. They also updated the documentation and corrected the line length in the example notebook, showing attention to code quality.
Contributions:10 reviews, 5 commits, 2 PRs in 4 years 7 months
Contributions summary:Thomas primarily contributed to the `gammapy` repository by implementing and refining functionality related to the analysis of gamma-ray astronomy data. This involved adding and modifying methods for theta2 distribution analysis within the `EventList` class. The contributions included the introduction of new features, such as plotting theta2 distributions, refining existing methods and adding flexibility through arguments like center, and updating relevant documentation. These commits show the user's focus on enhancing data visualization and analysis tools within the project.
gamma-rayraypythonnumpyastrophysics
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Thomas Vuillaume - Ingénieur De Recherche at IDEFICS