Léo Sénique
About Léo Sénique
Léo Sénique is an engineer specializing in software research and development, currently employed at Inria in Montbonnot-Saint-Martin, France. He has a background in physics and extensive experience in Java DevOps, contributing to projects that enhance urban mobility solutions.
Work at Inria
Léo Sénique has been employed at Inria as an Ingénieur en recherche et développement logiciels since 2021. His role involves significant contributions to software development projects, particularly in the domain of urban mobility solutions. He works in Montbonnot-Saint-Martin, Auvergne-Rhône-Alpes, France, where he is responsible for developing a new platform that integrates micro-mobility and public transport data with existing traffic analysis platforms.
Previous Experience at Irstea
Before joining Inria, Léo Sénique worked as an Étudiant stagiaire at Irstea for six months in 2019. This internship took place in the Région de Grenoble, France, where he gained practical experience in research and development within a scientific environment.
Education and Expertise
Léo Sénique has a diverse educational background. He studied at Université Grenoble Alpes, where he earned a Licence in Physique from 2012 to 2015. He then pursued a Master de Physique at Université de Montpellier from 2017 to 2019. Additionally, he completed a Formation in Java DevOps at Dta ingénierie, Diginamic, which lasted for 11 months in 2020.
Experience at DTA Ingénierie
Léo Sénique worked at DTA Ingénierie as an Ingénieur d'Etudes et Développement Java DevOps for four months in 2020. This position allowed him to apply his skills in software development and deepen his expertise in Java and DevOps practices.
Contributions to Urban Mobility Projects
Léo Sénique is actively involved in the Grenoble Mobility Lab project, which focuses on enhancing urban mobility solutions. His work includes maintaining two traffic analysis and prediction platforms, Grenoble Traffic Lab and GTL-ville, which aim to improve traffic management and urban planning by analyzing data from various sources.