Search results

A new platform dedicated to research in the humanities and social sciences (SHS) is being launched at UNamur. The aim? To offer SHS researchers methodological support tailored to their needs and strengthen SHS excellence at UNamur. This platform, SHS Impulse, will provide various services such as financial support for training, consultancy, access to resources, or co-financed software purchases.

For Bruno Dumas, computer science fits in with the principles of applied psychology Artificial intelligence (AI) is interfering in our professional as well as our private lives. It both seduces and worries us. On a global scale, it is at the heart of major strategic, societal or economic issues, still being debated in mid-February 2025, at the AI World Summit in Paris. But how can we, as users, avoid being subjected to it? How can we gain access to the necessary transparency of its workings? By placing his research prism on the user's side, Bruno Dumas is something of a "computer psychologist". An expert in human-computer interaction, co-president of the NaDI Institute (Namur Digital Institute), he defends the idea of a reasoned and enlightened use of emerging technologies.

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.

This summer's third and final focus on the NaDI-CeRCLe research center, which has gained international recognition in recent weeks thanks to awards won by three young researchers in service management. Following on from Floriane Goosse and Victor Sluÿters, we invite you to discover the work of Florence Nizette, a young researcher working on Artificial Intelligence technologies.

The program 09:30 | Welcome speech and coffee10:00 | Presentation of the platforms11:00 | Group visit of the platforms12:00 | Lunch and networking Pysico-Chemical Characterization (PC²)The PC² platform comprises a wide range of instruments, including: liquid and solid-state nuclear magnetic resonance spectrometers, X-ray diffractometers for single crystals and powders, instruments for analyzing textural properties (nitrogen physisorption, mercury porosimetry, etc.), instruments for analyzing chemical composition (combustion chemical analysis, ICP-OES, etc.), as well as various separation techniques (chromatography, centrifugation, etc.).), instruments for analyzing chemical composition (combustion chemical analysis, ICP-OES, etc.), and various separation techniques (chromatography, centrifugation, etc.). The combination of these techniques with the presence of two research logisticians and a technician dedicated to sample analysis, as well as highly qualified researchers for the development of advanced applications, reflects the strategic intent of this platform. Among these characterization techniques, solid-state NMR and X-ray diffraction are the most advanced and unique characterization tools.Synthesis, Irradiation and Analysis of Materials (SIAM)The SIAM platform specializes in the advanced synthesis and characterization of materials and nanomaterials. It actively contributes to fundamental research in (bio)materials science, particularly in terms of characterizing surfaces, interfaces and ion/material interactions, in collaboration with international university laboratories. SIAM's analytical capabilities enable it to study a wide range of samples from fields as diverse as materials science, life sciences and heritage science. One of SIAM's key assets is its recognized expertise in spectroscopy (XPS and ToF-SIMS), which can be coupled with nuclear analysis (Ion Beam Analysis or IBA). Thanks to state-of-the-art equipment, all support is provided by a highly qualified team in a dynamic of continuous development and innovation. As part of the University of Namur, SIAM is a privileged partner both for academic research projects and for the provision of services to industrial and institutional players.Lasers, Optics and Spectroscopies (LOS)The LOS platform is developing its expertise around optical methods for the study of materials. LOS recently acquired a Raman scattering microscope for the analysis of liquids, powders, solids and thin films, both organic and inorganic. This technique can be used to identify a sample's chemical composition and structure, as well as certain properties of the medium. Raman spectroscopy can be used to characterize polymers, nanomaterials, pharmacological compounds, geological materials, precious stones, heritage objects and food products, to name but a few. In imaging mode, this technique can map the distribution of a compound in a heterogeneous sample, as well as detect traces. Practical information Registration required before November 4, 2025. I want to register Find out more about UNamur's technology platforms Contact Research Administration | Business Developer - Joël Marinozzi : joel.marinozzi@unamur.be

A flurry of awards for the NaDI-CeRCLe research center in recent weeks. The service management research of three young doctoral students from the EMCP Faculty has been recognized by their peers at leading international scientific events: Floriane Goosse, Victor Sluÿters and Florence Nizette. This summer, we invite you to discover their careers and their work.

Abstract Deep learning has become an extremely important technology in numerous domains such as computer vision, natural language processing, and autonomous systems. As neural networks grow in size and complexity to meet the demands of these applications, the cost of designing and training efficient models continues to rise in computation and energy consumption. Neural Architecture Search (NAS) has emerged as a promising solution to automate the design of performant neural networks. However, conventional NAS methods often require evaluating thousands of architectures, making them extremely resource-intensive and environmentally costly.This thesis introduces a novel, energy-aware NAS pipeline that operates at the intersection of Software Engineering and Machine Learning. We present CNNGen, a domain-specific generator for convolutional architectures, combined with performance and energy predictors to drastically reduce the number of architectures that need full training. These predictors are integrated into a multi-objective genetic algorithm (NSGA-II), enabling an efficient search for architectures that balance accuracy and energy consumption.Our approach explores a variety of prediction strategies, including sequence-based models, image-based representations, and deep metric learning, to estimate model quality from partial or symbolic representations. We validate our framework across three benchmark datasets, CIFAR-10, CIFAR-100, and Fashion-MNIST, demonstrating that it can produce results comparable to state-of-the-art architectures with significantly lower computational cost. By reducing the environmental footprint of NAS while maintaining high performance, this work contributes to the growing field of Green AI and highlights the value of predictive modelling in scalable and sustainable deep learning workflows. Jury Prof. Wim Vanhoof - University of Namur, BelgiumProf. Gilles Perrouin - University of Namur, BelgiumProf. Benoit Frénay - University of Namur, BelgiumProf. Pierre-Yves Schobbens - University of Namur, BelgiumProf. Clément Quinton - University of Lille, FranceProf. Paul Temple- University of Rennes, FranceProf. Schin'ichi Satoh - National Institute of Informatics, Japan