Nicolas Gilet
About Nicolas Gilet
Nicolas Gilet is a research engineer specializing in epidemic propagation simulation, currently working at Inria in Saclay, France. He has a strong academic background in applied mathematics and has contributed to significant projects involving high-performance computing and machine learning.
Work at Inria
Nicolas Gilet currently serves as an Ingénieur de Recherche en simulation de propagation d'épidémie at Inria, a position he has held since 2021. Based in Saclay, Île-de-France, he focuses on developing simulation models for epidemic propagation. His work involves utilizing advanced computational techniques and high-performance computing resources to enhance the accuracy and efficiency of epidemic simulations.
Previous Experience at CNRS
Before joining Inria, Nicolas Gilet worked at CNRS - Centre national de la recherche scientifique in various roles. He served as an Expert en Calcul Scientifique for 11 months in 2020, and as an Ingénieur de Recherche en Développement Numérique for 11 months in 2016. He also completed a doctoral research project in numerical modeling of space instrument measurements from 2017 to 2019, contributing significantly to the field of scientific computing.
Education and Expertise
Nicolas Gilet has a strong educational background in applied mathematics. He earned a Diplôme d'Ingénieur from Institut national des Sciences appliquées de Toulouse, where he studied from 2011 to 2014. He also completed a Master de Recherche in Mathématiques Appliquées at Université Paul Sabatier (Toulouse III) in 2014. His academic training has equipped him with expertise in numerical analysis, simulation modeling, and high-performance computing.
Research Contributions
Nicolas Gilet has made notable contributions to research in epidemic modeling. He developed a simulation model for the SARS-CoV-2 epidemic using stochastic models and Monte-Carlo methods, implemented in Julia. His research utilized the Joliot-Curie/Irene-Rome supercomputer, where he was allocated 6 million core hours for simulations. Additionally, he has worked on models for satellite data calibration and applied machine learning techniques for data processing in space missions.
Internships and Early Career
Nicolas Gilet began his career with various internships that laid the foundation for his expertise in applied mathematics and research. He worked at the Danish Meteorological Institute as an engineering researcher in applied mathematics in 2013. He also completed a stage at CNRS focusing on the controllability of partial differential equations in 2014, which provided him with practical experience in scientific research and numerical analysis.