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Maxime LEFRANCOIS
Associate Professor
IMT - MINES Saint-Étienne - Institut Henri Fayol Member of Laboratoire Hubert Curien - UMR CNRS 5516
158 cours Fauriel – CS 62362
42023 Saint-Étienne Cedex 2 – France |
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Maxime Lefrançois is a former student of the Ecole Normale Supérieure de Cachan, and prepared and passed the Agrégation exam in Mechanics in 2008. He then received a Master degree from Grenoble INP in Signal Processing in 2009, and another from Université Grenoble 2 in Informatics in 2010, while being sessional Lecturer in Mechanics at Université Grenoble 1. During his Ph.D. he prepared in the WIMMICS team, INRIA Sophia-Antipolis, he worked on knowledge representation and reasoning for the Meaning-Text linguistic theory. Between 2014 and 2017, he was a post-doctoral researcher at the École des Mines de Saint-Étienne, and was involved in several bilateral, national, and European projects, including the ITEA2 SEAS project in the context of which he bootstrapped the development of the SEAS ontology: a modular and versioned ontology built on top of the OGC&W3C SOSA/SSN standard, that consists of simple ontology patterns that can be instantiated for different engineering-related verticals. Maxime is one of the co-editors of the SOSA/SSN standard, and leader of ETSI Specialist Task Forces (STF 556 and 578) to consolidate the ETSI SmartM2M Smart Applications REFerence ontology. He also initiated the development of the SPARQL-Generate RDF lifting language, and the cdt:ucum Datatypes. He has experience in organizing workshops and tutorials in international events. Since 2017 he is Associate Professor in the Connected-Intelligence team at the École des Mines de Saint-Étienne, France.
keywords: Web, Knowledge Representation and Reasoning, Knowledge Engineering, Semantic Web, Linked Data, Web of Things, Computational Linguistics
selected research items:
- SAREF Development Framework and Workflow, Streamlining the Development of SAREF and its Extensions;
- The W3C Semantic Sensor Network recommendation;
- The SEAS ontologies;
- SPARQL-Generate: an extension of SPARQL 1.1 to generate RDF from documents in heterogenous formats;
- Lindt: RDF Datatypes that enable lightweight descriptions of useful knowledge on the Web of Data;
- RDF Presentation and RDF Presentation negotiation;
- PhD: Representation of the Meaning-Text Theory Lexical Semantics, and development of the Unit Graphs knowledge representation formalism.