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Wassila Ouerdane. Lecturer at CentraleSupélec


I am an Assistant Professor (Lecturer, MCF) in Computer Science at  CentraleSupélec, and a member of the MICS (Mathématiques et Informatique pour la Complexité et les Systèmes) Lab, within the Research Group LOGIMICS (LOGIcal approaches for Modelling, data Interpretation and Complex Systems) since February 2019. Previously, I was in the Industrial Engineering Lab at CentraleSupélec (Spet. 2010- January 2019), within the Decision Aid team. I hold a PhD on Computer Science from University of Paris Dauphine in December 2009, on the subject "Multiple Criteria Decision Aiding: a dialectical Perspective". My research activities are across two fields: Artificial Intelligence and Decision Theory. I am interested in questions related to Knowledge Representation and Reasoning within the context of Explainable AI. I investigates several questions among them: using argumentation theory as a tool to both specify agent reasoning (resolving conflicts, explaining decisions, etc.) and facilitate agent interaction (dialogue protocol). I am also interested by applying decision aiding methodologies within real context. 

Research Interests: 

  • Multiple Criteria Deciison aiding 
  • Artificial Intelligence (knowledge representation and reasoning)

Web site: https://wassilaouerdane.github.io


Mathieu Dernis   

Conference papers2 documents

  • Mathieu Dernis, Wassila Ouerdane, Ludovic-Alexandre Vidal, Pascal da Costa, Franck Marle. Assessment of Ssustainable strategies based on DMM approach and value creation. 19th Dependency and Structure Modelling Conference (DSM), Sep 2017, Helsinki, Finland. ⟨hal-01589594⟩
  • Mathieu Dernis, Ludovic-Alexandre Vidal, Franck Marle, Wassila Ouerdane, Pascal da Costa. Aide à la sélection de stratégies pour apporter des valeurs durables à des pays hôtes en contexte pétrolier. Congrès International de Génie Industriel CIGI, May 2017, Compiègne, France. ⟨hal-01559093⟩