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A lifelong video game enthusiast, Fanny Barnabé, a researcher at the CRIDS research center (Namur Digital Institute) and lecturer at the University of Namur, explores behind the scenes of a major cultural phenomenon: video game streaming on Twitch. Between humor, irony and toxic discourse, she deciphers the issues at stake in a digital space in the throes of change.

High-Sensitivity Birefringence Mapping Using Near-Circularly Polarized Light I will describe several techniques for mapping a two-dimensional birefringence distribution, which can be classified according to the optical schemes and principles of work:Illumination geometry (transmitted light/reflected light)Image acquisition (sequential acquisition/simultaneous acquisition)Polarization control (electrically controlled variable retardance/mechanical rotation).This classification facilitates a comparative analysis of the capabilities and limitations in these methods for birefringence characterization. Polychromatic polarizing microscopy (PPM) provides unique capabilities to alternative methods. It leverages vector interference to generate vivid, full-spectrum colors at extremely low retardances, down to < 10 nm. PPM is a significant departure from conventional polarizing microscopes that rely on Newton interference, which requires retardances above 400 nm for color formation. Furthermore, PPM's color output directly reflects the orientation of the birefringent material, a feature absent in conventional microscopy where color is solely determined by retardance.Joint seminar of ILEE & NISM!The seminar is open to external people too, no need to register. More info

On December 11, 2024, the University of Reims-Champagne-Ardenne hosted the launch event for the ORION project, in which the University of Namur is a partner. This project, financed for 4 years by ERDF and INTERREG funds, aims to improve water management in the Val de Meuse while preserving the ecosystems of the Val de Meuse, a river running through France and Belgium.

Max Collinet, professor of geology at the Faculty of Science and researcher at the Institute of Life, Earth and Environment (ILEE), has just been awarded equipment funding (EQP) from the F.R.S - FNRS following calls whose results were published in December 2024.

From March 31 to April 4, 2025, a Belgian delegation, including UNamur Rector Annick Castiaux, took part in a royal mission to Vietnam aimed at strengthening economic, academic and scientific ties between the two countries. The mission was punctuated by several milestone events highlighting UNamur's fruitful collaborations with Vietnamese institutions.

An international research team led by the Swedish University of Agricultural Sciences has uncovered how pharmaceutical pollution alters the behaviour and migration patterns of Atlantic salmon in nature. Professor Eli Thoré, from the Department of Biology and the ILEE research institute at the University of Namur, contributed to this groundbreaking field study, which has just been published in Science.

Synopsis The spreading of internet-based technologies since the mid-90s has led to a paradigm shift from monolithic centralized information systems to distributed information systems based upon the composition of software components, interacting with each other and of heterogeneous natures. The popularity of these systems is nowadays such that our everyday life is touched by them.Classically concurrent and distributed systems are coded by using the message passing paradigm-according to which components exchange information by sending and receiving messages. In the aim of clearly separating computational and interactional aspects of computations, Gelernter and Carriero have proposed an alternative framework in which components interact through the availability of information placed on a shared space. Their framework has been concretized in a language called Linda. A series of languages, referred to nowadays as coordination languages, have been developed afterwards. In addition to providing a more declarative framework, such languages nicely fit applications like Facebook, LinkedIn and Twitter, in which users share information by adding it or consulting it in a common place. Such systems are in fact particular cases of so-called socio-technical systems in which humans interact with machines and their environments through complex dependencies. As coordination languages nicely meet social networks, the question naturally arises whether they can also nicely code socio-technical systems. However, answering this question first requires to see how well programs written in coordination languages can reflect what they are assumed to model.This thesis aims at addressing these two questions. To that end, we shall use the Bach coordination language developed at the University of Namur as a representative of Linda-like languages. We shall extend it in a language named Multi-Bach to be able to code and reason on socio-technical systems. We will also introduce a workbench Anemone to support the modelling of such systems. Finally, we will evidence the interest of our approach through the coding of several social-technical systems. The Jury Prof. Wim Vanhoof - University of Namur, BelgiumProf. Jean-Marie Jacquet - University of Namur, BelgiumProf. Katrien Beuls - University of Namur, BelgiumProf. Pierre-Yves Schobbens - University of Namur, BelgiumProf. Laura Bocchi - University of Kent, United KingdomProf. Stefano Mariani - UNIMORE University, Italy Participation upon registration. Register here

SynopsisA honeypot is a security tool deliberately designed to be vulnerable, thereby enticing attackers to probe, exploit, and compromise it. Since their introduction in the early 1990s, honeypots have remained among the most widely used tools for capturing cyberattacks, complementing traditional defenses such as firewalls and intrusion detection systems. They serve both as early warning systems and as sources of valuable attack data, enabling security professionals to study the techniques and behaviors of threat actors.While conventional honeypots have achieved significant success, they remain deterministic in their responses to attacks. This is where adaptive or intelligent honeypots come into play. An adaptive honeypot leverages Machine Learning techniques, such as Reinforcement Learning, to interact with attackers. These systems learn to take actions that can disrupt the normal execution flow of an attack, potentially forcing attackers to alter their techniques. As a result, attackers must find alternative routes or tools to achieve their objectives, ultimately leading to the collection of more attack data.Despite their advantages, traditional honeypots face two main challenges. First, emulation-based honeypots (also known as low- and medium-interaction honeypots) are increasingly susceptible to detection, which undermines their effectiveness in collecting meaningful attack data. Second, real-system-based honeypots (also known as high-interaction honeypots) pose security risks to the hosting organization if not properly isolated and protected. Since adaptive honeypots rely on the same underlying systems, they also inherit these challenges.This thesis investigates whether it is possible to design a honeypot system that mitigates these challenges while still fulfilling its primary objective of collecting attack data. To this end, it proposes a new abstract model for adaptive self-guarded honeypots, designed to balance attack data collection, detection evasion, and security preservation, ensuring that it does not pose a risk to the rest of the network.Jury membersProf. Wim VANHOOF, President, University of NamurProf. Jean-Noël COLIN, Promoter, University of NamurProf. Florentin ROCHET, Internal Member, University of NamurProf. Benoît FRENAY, Internal Member, University of NamurProf. Ramin SADRE, External Member, Catholic University of LeuvenDr. Jérôme FRANCOIS, External Member, University of LuxembourgYou are cordially invited to a drink, which will follow the public defense. For good organization, please give your answer by Tuesday, May 20, 2025. I want to register

Synopsis deep learning methods have become increasingly popular for building intelligent systems. Currently, many deep learning architectures constitute the state of the art in their respective domains, such as image recognition, text generation, speech recognition, etc. The availability of mature libraries and frameworks to develop such systems is also a key factor in this success.This work explores the use of these architectures to build intelligent systems for sign languages. The creation of large sign language data corpora has made it possible to train deep learning architectures from scratch. The contributions presented in this work cover all aspects of the development of an intelligent system based on deep learning. A first contribution is the creation of a database for the Langue des Signes de Belgique Francophone (LSFB). This is derived from an existing corpus and has been adapted to the needs of deep learning methods. The possibility of using crowdsourcing methods to collect more data is also explored.The second contribution is the development or adaptation of architectures for automatic sign language recognition. The use of contrastive methods to learn better representations is explored, and the transferability of these representations to other sign languages is assessed.Finally, the last contribution is the integration of models into software for the general public. This led to a reflection on the challenges of integrating an intelligent module into the software development life cycle.Jury membersProf. Wim VANHOOF, President, University of NamurProf. Benoît FRENAY, Promoter, University of NamurProf. Anthony CLEVE, Co-promoter, University of NamurProf. Laurence MEURANT, Internal Member, University of NamurProf. Lorenzo BARALDI, External Member, University of ModenaProf. Annelies BRAFFORT, External Member, University of Paris-SaclayProf. Joni DAMBRE, External Member, University of GhentYou are cordially invited to a drink, which will follow the public defense. For a good organization, please give your answer by Friday June 6. I want to register

From 2020 to 2025, as part of her doctoral thesis in history, researcher Julie Duchêne conducted a ground-breaking investigation blending history and biology to trace the cohabitation between humans and wolves in Wallonia and Luxembourg, from the 18th to the early 20th century. Thanks to an innovative interdisciplinary approach, including DNA analysis of naturalized 19th-century specimens, her work sheds light on the mechanisms that led to the local extinction of the species. This research was made possible thanks to the support of numerous scientific and cultural partners.

Professor Eli Thoré and Justine Bélik have just been honoured by the Adrien Bauchau Fund (FAB). Created in memory of the founder of the Biology Department at UNamur, the FAB has been promoting excellence in education and research in the life sciences since 1989.

An unusual piece of research recently mobilized teams from UNamur's Biology Department. Genetic analyses carried out by the Environmental and Evolutionary Biology Research Unit (URBE) were able to confirm the protected status of a herd of wild mouflons based in Gesves, and thus highlight the importance of saving them.