Summary
Pierre Faure-Giovagnoli is a data scientist and engineer with a PhD in computer science who blends rigorous research on hydraulic time series, domain-knowledge integration and explainable ML with hands-on applied projects in NLP, image analysis and sensor signal processing. Based in Lyon, he brings eight years of experience spanning academia (INSA Lyon, LIRIS), industry R&D (Worldline, INSAVALOR) and a unique creative practice as a professional photographer and graphic designer. His doctoral work—done in partnership with Compagnie Nationale du Rhône—focused on extracting actionable knowledge from multivariate hydraulic data, reflecting a rare combination of environmental domain expertise and advanced data-science methods. He has published practical approaches to reducing annotation needs for microscopy by leveraging synthetic images, and teaches core CS subjects with over 200 hours of instruction experience. Comfortable moving from deep learning for images and diatom detection to production-ready NLP pipelines, he is pragmatic about model explainability and embedding real-world constraints into ML workflows. Outside pure engineering, his musical and visual-arts background informs an aesthetic, human-centered approach to data-driven products.
8 years of coding experience
5 years of employment as a software developer
Scientific Baccalaureate, Science, Honors, Scientific Baccalaureate, Science, Honors at Guez de Balzac High School, Angoulême, France
Master of Science, Computer Science, GPA: 4/4, Master of Science, Computer Science, GPA: 4/4 at Georgia Institute of Technology
DNOP Violon, DNOP Electroacoustique, CEM FM, DNOP Violon, DNOP Electroacoustique, CEM FM at Conservatoire Gabriel Fauré, Angoulême
Egineering degree in Computer Science (R&D and Art option), Computer Science, Obtenu, Egineering degree in Computer Science (R&D and Art option), Computer Science, Obtenu at INSA Lyon - National Institute of Applied Sciences
English, French, German