In this talk, I'll give a general presentation of my past and present research topics. This ranges from answering counting queries on description logic knowledge bases to dealing with inconsistent streams of data, via exploring circumscription on the guarded fragment of first-order logic. The common denominator is the addition of features to the Ontology-Mediated Query Answering framework (OMQA) for which a precise understanding of the underlying models is required. To this end, I develop techniques to manipulate models while preserving their key-properties which further allow me to identify the exact complexity of the reasoning task. I'll also present possible extensions of this line of research that could be investigated in the future.
Short bio: Quentin Manière is a postdoctoral researcher, member of the center for Scalable Data analyticS and Artificial Intelligence (ScaDS.AI) at Leipzig University (Germany). He received his PhD from the University of Bordeaux (France) in 2022. His research focuses on Ontology-Mediated Query Answering (OMQA) in the context of Knowledge Representation and Reasoning (KRR). Quentin Manière has been mostly investigating how to enrich various OMQA settings with meaningful features, such as more expressive query languages or non-monotonic aspects, and the consequences of those extensions in terms of computational complexity.
