Paul Novello is an ML Research Engineer with eight years of experience bridging scientific machine learning and trustworthy AI, currently leading research and coordination efforts at IRT AESE/ANITI in Toulouse. He specializes in XAI, robustness, and uncertainty quantification, spearheading an open-source post-hoc OOD detection library (oodeel) and leading industry-collaborative projects with Airbus, Renault and MILA. Paul holds a PhD in Applied Mathematics from École Polytechnique where he embedded neural surrogates into large HPC simulations for CFD, and he brings hands-on engineering experience deploying ML in Fortran/C++ production codes. Known for translating rigorous research into usable tools, he also mentors PhD candidates and regularly reviews for top ML conferences.
8 years of coding experience
2 years of employment as a software developer
PhD, MATHEMATICS AND STATISTICS, PhD, MATHEMATICS AND STATISTICS at École Polytechnique
Master’s Degree, Mathematics and Statistics, Master’s Degree, Mathematics and Statistics at Télécom Paris
Master of Science - MSc, Mathematical Statistics and Probability, Master of Science - MSc, Mathematical Statistics and Probability at Imperial College London
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