Sébastien DESTERCKE Chercheur CNRS

Responsable de l'équipe CID (Intelligence Artificielle) | Génie Informatique (GI) | Heuristique et Diagnostic des Systèmes Complexes

I currently work at the Laboratoire Heuristique et Diagnostic des Systèmes Complexes (Heudiasyc), and am emplyed by French National Centre for Scientific Research (CNRS). My research focuses on uncertainty reasoning and modelling.

Compétences clés

Connaissances Incertitudes Données intelligence artificielle apprentissage automatique Modélisation
Sebastien Destercke graduated in 2004 as an engineer from the Faculté Polytechnique de Mons in Belgium. In 2008, he earned a Ph.D. degree in computer science from Université Paul Sabatier, in Toulouse (France). He now works as a researcher for the French National Research Center (CNRS), in the Heuristic and Diagnostic of Complex Systems (Heudiasyc) Laboratory. His main research interests are in the field of uncertainty reasoning with imprecision-tolerant models (DS theory, imprecise probabilities, possibility theory, ...), with a focus on issues related to reliability and risk analysis, decision making and machine learning.

Sébastien Destercke has a strong background in the imprecise probability theories complementing probability theory, and is one of the few researchers in the world to span the whole set of such theories. His research ranges from handling severe uncertainties in engineering applications (risk and reliability analysis, knowledge management) to artificial intelligence, and quite recently to machine learning issues. His main recognized achievements so far are:

  •  Advancing in the understanding of abstract notions such as conflict or the value of imprecision,
  • Clarifying the differences between imprecise probabilistic approaches, and unify them when possible,
  • Proposing uncertainty models, and recently learning methods, whose properties make them tractable

His current interests include:

  • Application of imprecise probability theory and machine learning to various areas, including autonomous vehicles, connected buildings, agronomic applications (ACV, cheese production, ...),
  • Problems involving inferences over combinatorial and complex structures, including graphs, preferences, boolean functions, ...
Sébastien Destercke


Sébastien Destercke
Chargé de recherche CNRS

UTC - UMR 7253 Heudiasyc
57 Avenue de Landshut,
Compiègne, 60203

Tel: +33 (0)3 44 23 79 85