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Space has become a major economic and strategic issue. As a member of the European UNIVERSEH Alliance, UNamur explores this space theme in its various departments, from physics to geology, via mathematics, computer science or philosophy. Without forgetting to address the general public, who still dream of the stars...

The TineaDiag project is a research project run by UNamur and ULiège with funding from the SPW Research Win²WAL program. It tackles dermatophytoses, skin infections responsible for ringworm, which can affect both humans and animals. The aim? To identify, in dermatophytes, precise cellular markers in order to detect them with sensitivity and certainty, and thus identify infections caused by antifungal-resistant strains.

A major breakthrough for the health of women on oral contraceptives has been achieved by researchers in Namur. Every year in Europe, more than 22,000 cases of venous thrombosis or embolism occur among contraceptive pill users. A team of researchers from the University of Namur, in collaboration with QUALIblood (spin-off), has conducted an important study, the results of which could transform prescribing recommendations..

Gilles Perrouin has just received the award for the most influential paper at the SPLC2024 conference. This award highlights a successful line of research on software product line testing, already awarded in February 2024.

In late November, the Mont-Saint-Guibert-based company Cellistic® donated equipment it no longer used to UNamur. By enabling the university to give this equipment a second life, Cellistic is making an important gesture in support of the development of university research.

Bringing a new drug to market, particularly when it is intended to treat a pediatric or orphan disease, is a journey fraught with pitfalls. The ERAMET project, coordinated by Professor Flora Musuamba Tshinanu, aims to overhaul the assessment procedures, so that regulatory agencies can take innovative technologies into account and thus make more informed choices.

Can a computer learn a language like a child? A recent study published in the leading journal Computational Linguistics by Professors Katrien Beuls (Université de Namur) and Paul Van Eecke (AI-lab, Vrije Universiteit Brussel) sheds new light on this question. The researchers argue for a fundamental revision of the way artificial intelligence acquires and processes language.

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 The public defense will be followed by a reception.Registration required. I want to register

Founded some 50 years ago, the Laboratoire d'Analyse par Réactions Nucléaires (LARN) in the Department of Physics at the University of Namur is home to a 2MV tandem particle gas pedal named ALTAÏS (Accélérateur Linéaire Tandetron pour l'Analyse et l'Implantation des Solides), in operation since 1999.

The three Belgian scientific experiments selected to be carried out on board the International Space Station (ISS) during astronaut Raphaël Liégeois' mission in 2026 have just been unveiled by the Federal Science Policy Public Service (Belspo). One of them is carried by a team from UNamur for an experiment at the crossroads of biology and physics aimed at analyzing the resistance of the "blob", an atypical unicellular organism.

Researchers from UNamur's Departments of Biology and Physics have conducted a scientific experiment to assess the radioresistance of the common black ant Lasius niger. The results of their work have just been published in the Belgian scientific journal Belgian Journal of Zoology. The Namur-based scientists demonstrate a level of resistance far superior to that of humans. Their spontaneous approach also demonstrates a lesser-known approach to scientific research.

Beautiful victory for Margaux Mignolet, a researcher at the Faculty of Medicine's Unité de Recherche en Physiologie Moléculaire (URPhyM), who wins 1st prize in the Belgian inter-university final of the Ma thèse en 180 secondes (MT180) competition. Her research? To better understand the mechanisms of antibodies active in cases of long COVID. The second prize in this national competition was also won by a candidate from Namur. It was Petra Manja, from the Unité de Recherche en biologie des micro-organismes (URBM), Department of Biology, Faculty of Science, and is pursuing a thesis aimed at understanding resistance mechanisms in the bacterium E. coli. Both are also researchers at the NARILIS Institute.