Yoan Chabot

Yoan Chabot

AI Researcher and Project Manager

Teaching

👩‍🎓👨‍🎓 Students (current)

  • [2024- ] Thesis co-director of Camille Barboule for his PhD co-supervised with Benjamin Piwowarski (ISIR), “Information Extraction in Long Multimodal Documents”
  • [2023- ] Thesis co-director of Lucas Jarnac for his PhD co-supervised with Miguel Couceiro (LORIA), “Reconciling uncertain knowledge to improve knowledge graphs”
  • [2024- ] Apprenticeship supervisor of LĂ©na Abel at UTBM, “DĂ©veloppement d’outils de construction de graphes de connaissances d’entreprise”. Co-supervision with FrĂ©dĂ©ric DeuzĂ©.
  • [2023- ] Member of the supervisory committee of Duo Yang for his PhD on Automated Knowledge Graph construction at KU Leuven
  • [2024- ] Member of the supervisory committee of Jean Meunier-Pion for his PhD on Failure-awareness learning for the design of resilient infrastructures using natural language processing at UniversitĂ© Paris-Saclay

👩‍🎓👨‍🎓 Students (past)

  • [2020-2024] Thesis co-director of Lionel Tailhardat for his PhD co-supervised with RaphaĂ«l Troncy (EURECOM), “Synergy between knowledge graphs and machine learning for the detection of anomalies”
  • [2024] Supervision of Boumediene Sari for his final year internship at University of Montpellier, “DĂ©veloppement de robots pour l’enrichissement de graphe de connaissances d’entreprise”
  • [2023] Co-supervision (main supervisor: Lionel Tailhardat) of Benjamin Stach for his final year internship at UTBM University of Technology, “Development of a solution for collecting and annotating activity traces for an illicit activity detection platform using knowledge engineering and machine learning techniques”
  • [2023] Co-supervision (main supervisor: Antoine Py) of Yassine Trabelsi for his final year internship at Esprit School of engineering, “DĂ©veloppement d’outils web de visualisation et d’interrogation de graphes de connaissances”
  • [2020-2023] Thesis co-director of Jixiong Liu for his PhD co-supervised with RaphaĂ«l Troncy (EURECOM), “Production and valorization of semantic annotation on structured datasets through a recommendation process based on graph embedding techniques” Here are the three main contributions of his PhD in few words + links:
    • This journal providing a fine grained classification of table types that one can harvest in the wild, on the Web and tools to pre-process them
    • A system for automatically interpreting tables based on a target knowledge graph. DAGOBAH has won the last 2 editions of the SemTab challenge. API avalaible here
    • A plugin system that leverages knowledge graph embeddings for improving the disambiguation step. Open source
  • [2020] Supervision of Antoine Py for his final year internship at University De Franche-ComtĂ©, “Development of a Web application for annotation and semantic integration of tabular data”
  • [2019] Supervision of Jixiong Liu for his final year internship at ESIGELEC Rouen, “Implementation of a prototype for annotating tabular data using semantic models”
  • [2018] Supervision of Nicolas Geist for his final year internship at INSA Lyon, “Development of a platform for detecting illegal activities using knowledge engineering and machine learning”

👨‍🏫 Courses