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An international team of researchers has just published an article in the prestigious journal Light: Science & Applications (LSA) from the Nature group.  The teams led by Professors Michaël Lobet and Alexandre Mayer (University of Namur) collaborated with the team led by Professor Shanhui Fan, one of the leading experts in the field, from the prestigious Stanford University in California (USA).  The result: an article entitled ‘Twist-Induced Beam Steering and Blazing Effects in Photonic Crystal Devices’, or the study of beam deflection by twisting in photonic crystal devices.  Come on, let's twist light again at UNamur! 

An international team of physicists led by Dr Michaël Lobet, lecturer at UNamur, re-examines the foundations of quantum physics from the point of view of momentum in the prestigious journal Nature Light Science & Applications. The researchers investigated what happens when this momentum is reduced to zero. Some interesting things happen! Explanations.

Let's go and discover the qualified researchers of UNamur, winners of the funding granted by the FNRS in 2022. Today, we meet Michaël Lobet, currently a lecturer at UNamur, who will begin his new mandate as a qualified FNRS researcher at the NISM Institute next fall. The subject of his research: twisted optics for the manipulation of slow photons or how to create light traps. Explanations.

What is a perfect fluid? It is a theoretical model of a fluid that allows us to assume that the fluid is not viscous, that it does not conduct heat, that it is incompressible and does not create vortices. It is therefore an approximation of reality that simplifies theoretical predictions of fluid flows. For the first time, an international team has experimentally demonstrated this same behaviour for light immersed in a medium of low refractive index.

On 21 and 22 September 2023, for the 4th year running, Belgian researchers came together for the bePOM conference. The format was original, with a virtual day and a hybrid day combining virtual and face-to-face sessions. A great success, and a Belgian network that is growing from strength to strength.

This is a great recognition of research at UNamur: three Marie Skłodowska-Curie Doctoral Networks (DN) projects have just been awarded, with a key contribution from researchers in Namur! The first, in chemistry, involves Professor Stéphane Vincent; the second, focused on ecosystem resilience, involves Professor Frédérik de Laender; and the third, in the field of photonics, benefits from the expertise of FNRS-qualified researcher Michaël Lobet.

The F.R.S.-FNRS has just published the results of its various 2024 calls. Equipment calls, research credits and projects, FRIA doctoral grants and Mandant d'Impulsion Scientifique (MIS), there are many instruments to support fundamental research. Find out more about UNamur's results.

Jamie Wright, a researcher at the Namur Digital Institute at UNamur, participated in a study conducted by Pompeu Fabra University (UPF) in Barcelona and published in the prestigious journal *Nature Human Behaviour*.  The study shows that languages around the world tend towards lexical economy, reusing words to denote different concepts when doing so does not lead to communicative confusion.

The result of a collaboration with Isabelle Frochot of the University of Burgundy Europe, a study in which Alain Decrop, a marketing professor at the EMCP Faculty, participated, shows that the mountains foster a genuine reconnection with oneself, with others, and with one’s environment. The results of this research were published in the prestigious journal *Recherche et Applications en Marketing* (RAM).

At UNamur, research is not confined to laboratories. From physics to political science, robotics, biodiversity, law, AI, and health, researchers collaborate daily with numerous stakeholders in society. The goal? Transform ideas into concrete solutions to address current challenges. 

Through research, teaching, and knowledge sharing, Wafa Hammedi, a professor at Sciences Po’s Faculty of Economics, Management, and Communication (EMCP), has charted a path guided by her convictions. Far from the performance-driven clichés typically associated with marketing, she advocates for socially engaged research that serves society, equity, and inclusion.

Abstract Deep learning has become a central part of everyday life, and has given us powerful digital tools such as machine translators, voice assistants, and large language models. The Deaf communities, however, benefit verylittle from this progress. Sign languages are full natural languages, but they have no widely used written form, so the large text corpora and pretrained models that support these tools for spoken languages have no direct equivalent. As a result, sign language processing is held back by two related problems: a persistent shortage of annotated data, and a lack of tools to analyze the languages themselves.This thesis focuses on one component of the sign language processing pipeline that has received comparatively little attention: sign language segmentation, the temporal partitioning of a continuous signing video into individual sign units. Segmentation sits between raw video and almost every symbolic task built on top of it, yet it remains poorly understood. The goal of this work is twofold: to advance the segmentation task itself, and to turn sign language processing research into tools that are usable by the Deaf community, with French Belgian Sign Language (LSFB) as the main setting.The central contribution of this thesis is a set of segmentation models. We first study approaches based on recurrent neural networks, and show that their main difficulty lies in the modeling of the transitions between signs, the brief ambiguous movements that separate one sign from the next and that are easily confused with the signs themselves. This insight motivates the Hydra framework, a new approach that detects each sign as a whole unit rather than deciding, frame by frame, whether a sign is being produced. Concretely, instead of classifying every frame, the model predicts the distance from each frame to the nearest sign boundaries, which makes it less sensitive to the ambiguous regions and improves consistently over prior methods. Around this core, we present further contributions: a sign language-to-text dictionary that recognizes signs from an ordinary webcam, supporting work on isolated sign recognition, and a collaborative platform that gathers new sign data as a side effect of everyday use. Together, these contributions narrow the gap between sign language processing research and the people whose language it concerns. Jury Prof. Benoit Frénay - University of Namur, BelgiumProf. Anthony Cleve - University of Namur, BelgiumProf. Katrien Beuls - University of Namur, BelgiumProf. Barbara Hammer - Bielefeld University, GermanyProf. Michèle Gouiffès - Paris-Saclay University, FranceDr. Mathieu De Coster - Ghent University, Belgium I am registering to attend Pierre Poitier's thesis defense