Discover PC², SIAM and the new RAMAN microscope (LOS)
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
See content
First MG-ERC conference brings together the world's inorganic chemistry elite
In early September, the University of Namur hosted the first Main-Group Elements Reactivity Conference (MG-ERC). Over 100 researchers from 12 countries and 32 institutions gathered around Professor Guillaume Berionni. An event hailed as "one of the best chemistry conferences" by its prestigious guests.
See content
Public defense of doctoral thesis in computer science - Antoine Gratia
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
See content
EMCP Faculty: three award-winning researchers - #2 Victor Sluÿters, the doctoral student who deciphers employee behavior in crisis situations
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.
See content
From video games to artificial intelligence, a stopover in Japan
Japan is almost 10,000 kilometers from Belgium, a country that fascinates, not least for its rich culture full of contrasts. Researchers at UNamur maintain close ties with several Japanese institutions, particularly in the fields of computer science, mathematics and video games. Let's take a look at some of these collaborations..
See content