Résultats de recherche

Pour Bruno Dumas, l’informatique s’inscrit dans les principes de la psychologie appliquée L’intelligence artificielle (IA) s’immisce dans nos vies professionnelles comme dans nos vies privées. Elle nous séduit comme elle nous inquiète. À l’échelle mondiale, elle est au cœur d’importants enjeux stratégiques, sociétaux ou économiques, débattus encore mi-février 2025, lors du sommet mondial de l’IA à Paris. Mais comment ne pas la subir en tant qu’utilisateur ? Comment avoir accès à cette nécessaire transparence de son fonctionnement ? En plaçant son prisme de recherche du côté de l’utilisateur, Bruno Dumas est en quelque sorte « un psychologue de l’informatique ». Expert en interaction humain-machine, co-président de l’Institut NaDI (Namur Digital Institut), il défend l'idée d'une utilisation raisonnée et éclairée des technologies émergentes. 

Le professeur Elio Tuci vient d'obtenir un financement Crédit de Recherche du FNRS. L'institut naXys s'est spécialisé dans l'analyse des systèmes complexes, qu'il s'agisse d'astronomie et de cosmologie dynamique, de biologie mathématique, d'optimisation en optique, de complexité économique ou encore de l'étude de la stabilité et de la robustesse de ces systèmes. L’institut est structuré en 6 axes de recherche : Space, Bio, Optics, Eco, Robust et Robotics. 

The workshop will feature:A keynote presentation on public value and AI implementation at VRT.Sessions on discoverability, user agency, and explainability.Discussions on regulation, including perspectives on the AI Act and transparency in media.An interactive session showcasing AI-driven prototypes.The event will also highlight our project’s latest findings. Join us for a day of thought-provoking discussions, knowledge exchange, and networking opportunities!Would you like to attend? Places are limited and will be allocated on a first-come, first-served basis, so register as soon as possible. Registration will close on April 11, 2025. More information here

This thesis presents a novel approach to address the challenges of deploying and managing Network Functions Virtualization (NFV) in resource-constrained and multi-domain environments. The proposed solution leverages a Raspberry Pi clusterbased approach for NFV deployment in resource-constrained environments, combined with a deployable Sidecar VNF (S-VNF) coordinator for multi-domain NFV orchestration.The thesis demonstrates the feasibility of integrating NFV into edge computing environments by successfully deploying and managing Network Services (NSs) on a Raspberry Pi cluster. The S-VNF coordinator facilitates efficient cross-cloud VNF deployment and management while ensuring security and interoperability.While the obtained deployment and scaling delays in the testbed setup were significant due to the bare-metal deployment process used, the proposed solution remains valuable in environments where service maintenance time is a critical factor.By automating deployment and scaling, organizations can minimize the impact of service maintenance time, improve customer satisfaction, and enhance system resilience. Moreover, the solution enables NFV to be deployed effectively in edge environments, providing benefits such as reduced latency and improved network performance.Overall, this thesis contributes to the advancement of NFV by providing innovative solutions for deployment and management in challenging environments. The proposed framework has the potential to enable the widespread adoption of NFV and drive the development of new network services.Dirigée par le Prof. Laurent SCHUMACHER et le Prof. Sokchenda SRENG.Devant un jury composé de :Prof. Wim VANHOOF, Président, Université de NamurProf. Laurent SCHUMACHER, Co-Promoteur, Université de NamurProf. Sokchenda SRENG, Co-Promoteur, ITC Graduate School (Cambodge)Prof. Florentin ROCHET, Membre interne, Université de NamurProf. Johann MARQUEZ-BARJA, Membre externe, Université d’AnversProf. Bruno QUOITIN, Membre externe, Université de MonsProf. Raveth HIN, Membre externe, ITC Graduate School (Cambodge)Vous êtes cordialement invités à un drink, qui suivra la soutenance publique.Pour une bonne organisation, merci de donner votre réponse pour le jeudi 20 mars.Contact : Daelman Isabelle – isabelle.daelman@unamur.be

Abstract Plastic pollution has emerged as a pervasive environmental threat, with micro- and nanoplastics (MPs and NPs) accumulating across ecosystems and organisms, including humans. Their ability to adsorb and transport contaminants raises critical concerns for both environmental and public health.This thesis investigates the developmental neurotoxicity of MPs and NPs in zebrafish (Danio rerio), emphasizing the influence of particle size and mixture toxicity. NPs were shown to cross the embryonic chorion, disrupt physiological functions, and induce anxiety-like behaviour, whereas MPs mainly altered gene expression related to neurodevelopment. When co-exposed with methylmercury (MeHg), NPs enhanced MeHg accumulation in the brain and sensory organs, exacerbating its neurotoxic effects. Notably, the mixture induced severe hypoactivity, impaired lipid metabolism and neurotransmission, and increased mortality.These findings highlight the critical need to assess plastic particle toxicity not only in isolation but also in environmentally relevant mixtures. NPs, due to their small size and high reactivity, may act as vectors for toxicants like MeHg, amplifying their effects during sensitive developmental stages. Jury Prof. Frédéric SILVESTRE (UNamur), PrésidentProf. Patrick KESTEMONT (UNamur), SecrétaireDr Valérie CORNET (UNamur)Prof. Eli THORÉ (UNamur)Prof. Jérôme CACHOT (Université de Bordeaux)Dr Krishna DAS (Université de Liège) Inscription obligatoire. Je m'inscris

C’est une belle reconnaissance pour l’excellence de la recherche menée à l’Université de Namur : la faculté d’informatique a été sollicitée pour rejoindre le prestigieux réseau Informatics Europe, qui rassemble les départements et facultés d’informatique les plus dynamiques à travers l’Europe.

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BNAIC/BeNeLearn 2025 will be held at the University of Namur under the auspices of the Belgian-Dutch Association for Artificial Intelligence (BNVKI) and the Dutch Research School for Information and Knowledge Systems (SIKS). The conference aims at presenting an overview of state-of-the-art research in artificial intelligence and machine learning in Belgium, The Netherlands, and Luxembourg. More information and registration

Abstract In recent decades, the volume of data generated worldwide has grown exponentially, significantly accelerating advancements in machine learning. This explosion of data has led to an increased need for effective data exploration techniques, giving rise to a specialized field known as dimensionality reduction. Dimensionality reduction methods are used to transform high-dimensional data into a low-dimensional space (typically 2D or 3D), so that it can be easily visualized and understood by humans. Algorithms such as Principal Component Analysis (PCA), Multidimensional Scaling (MDS), and t-distributed Stochastic Neighbor Embedding (t-SNE) have become essential tools for visualizing complex datasets. These techniques play a critical role in exploratory data analysis and in interpreting complex models like Convolutional Neural Networks (CNNs). Despite their widespread adoption, dimensionality reduction techniques, particularly non-linear ones, often lack interpretability. This opacity makes it difficult for users to understand the meaning of the visualizations or the rationale behind specific low-dimensional representations. In contrast, the field of supervised machine learning has seen significant progress in explainable AI (XAI), which aims to clarify model decisions, especially in high-stakes scenarios. While many post-hoc explanation tools have been developed to interpret the outputs of supervised models, there is still a notable gap in methods for explaining the results of dimensionality reduction techniques. This research investigates how post-hoc explanation techniques can be integrated into dimensionality reduction algorithms to improve user understanding of the resulting visualizations. Specifically, it explores how interpretability methods originally developed for supervised learning can be adapted to explain the behavior of non-linear dimensionality reduction algorithms. Additionally, this work examines whether the integration of post-hoc explanations can enhance the overall effectiveness of data exploration. As these tools are intended for end-users, we also design and evaluate an interactive system that incorporates explanatory mechanisms. We argue that combining interpretability with interactivity significantly improves users' understanding of embeddings produced by non-linear dimensionality reduction techniques. In this research, we propose enhancements to an existing post-hoc explanation method that adapts LIME for t-SNE. We introduce a globally-local framework for fast and scalable explanations of t-SNE embeddings. Furthermore, we present a completely new approach that adapts saliency map-based explanations to locally interpret non-linear dimensionality reduction results. Lastly, we introduce our interactive tool, Insight-SNE, which integrates our gradient-based explanation method and enables users to explore low-dimensional embeddings through direct interaction with the explanations. Jury Prof. Wim Vanhoof - University of Namur, BelgiumProf. Benoit Frénay - University of Namur, BelgiumProf. Bruno Dumas - University of Namur, BelgiumProf. John Lee - University of Louvain, BelgiumProf. Luis Galarraga - University of Rennes, France La défense publique sera suivie d'une réception.Inscription obligatoire. Je m'inscris