Mickael Coustaty

La Rochelle Université

Research Units

Member In the research unit:

Research Teams

Member In the research team:

Disciplines, scientific fields, research areas

  • Mathematics & Information Sciences
    • Computer and information sciences
      • Artificial intelligence, intelligent systems, multi agent systems
      • Computer graphics, computer vision, multimedia, computer games
      • Machine learning and data processing
      • Natural language processing and signal processing (e.g. speech, image, video)

Keywords

  • AI
  • Document Analysis
  • Computer Vision
  • Natural Language Processing
  • Digital Humanities

Bio

Mickaël Coustaty is a tenured Associate Professor at the L3i laboratory of La Rochelle University since 2015. He is specialized in complex document analysis by using multimodal approaches mixing textual and visual content. He initially worked on historical documents, extended its techniques to administrative documents, and included NLP approaches. He always worked in collaboration with experts or end-users in order to extract information, to index the content and to assess its relevance / trustability. He has been participating in ten externally funded projects, cross-disciplinary research projects and currently serves as the head of a joint private-public lab between L3i and the Yooz Company, co-funded by the French National Research Agency, the Région Nouvelle-Aquitaine and the Yooz Company. Finally, since 2016, he is in charge of a Master degree in digital law where he proposed the first French Master degree mixing computer science classes and law classes in collaboration with the French National Trusted Third-party association in order to connect different fields and to bond academic and industrial fields. He received the 2021 IAPR/ICDAR Young Investigator Award and is the President of a European Association bringing together academics and companies in the field of document analysis

Degrees

Phd in Computer Sciences, 2011

News about me & my work

New French Reseach project funded by ANR on historical document analysis for genealogy purposes