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TERATEC 2019 Forum
Workshops - Wednesday June 12

Workshop 5 - 14:00 to 17:30
Machine learning & Maintenance prédictive
Chaired by Erick JONQUIERE, AFNet et Jean-Laurent PHILIPPE, Intel

Predictive maintenance solution without additionnal sensors

By Christophe BIERNACKI, Head of MODAL research team, INRIA and Margot CORREARD, co-founder DiagRAMS Technologies (start-up INRIA)

Today, a considerable amount of data related to production is contained in every industrial equipement, but are not fully exploited. Thanks to the analysis of these complex data, predictive maintenance takes off. It enables industrials assets global monitoring without installing additionnal sensors. That’s what DiagRAMS Technologies offers to tackle failures. We are an Inria spin-off, based on the research of Modal team, expert in data science. Modal is especially focused on probabilistic methods in order to reach some mathematical guarantees on estimation efficiency while considering ‘raw’ data as widespread in realistic applications. Our Machine Learning algorithms monitor in real-time operating conditions to detect early anomalies, predict and diagnose failures.

Biography : After several years in charge of technology transfer at Inria, Margot CORREARD decides to create DiagRAMS Technologies, a spin-off from the latest research of Modal team. Margot has a business and R&D partnerships culture, she worked for the European Commission before joining the world of research..
Biographie : Christophe Biernacki est Professeur de statistique à l’Université de Lille. Il est responsable scientifique de l’équipe de recherche Modal chez Inria et directeur scientifique du centre de recherche Inria Lille. Sa recherche est focalisée sur la classification non supervisée à base de modèles probabilistes. Son objectif est de traiter dans ce cadre rigoureux les données dites complexes, mais prédominantes aujourd’hui, que représentent la volumétrie (dont la grande dimension), la perte d’information (données manquantes, données incertaines) et l’hétérogénéité des attributs (mélange de données continues et catégorielles par exemple). Il est également impliqué dans le développement de logiciels (Mixmod, Mixtcomp) qui permettent de rendre accessible ces outils issus de la recherche au plus grand nombre.

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For any other information regarding the workshops, please contact :

Jean-Pascal JEGU
Tel : +33 (0)9 70 65 02 10
2, rue de la Piquetterie


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