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Something for everyone 09:30 | Welcome ceremony for new students11:00 | Back-to-school celebration at Saint-Aubain Cathedral (Place Saint-Aubain - 5000 Namur), followed by student welcome by the Cercles. Read more

BNAIC/BeNeLearn 2025 will be held at the University of Namur under the auspices of the Belgian-Dutch Association for Artificial Intelligence (BNVKI) and the Dutch Research School for Information and Knowledge Systems (SIKS). The conference aims at presenting an overview of state-of-the-art research in artificial intelligence and machine learning in Belgium, The Netherlands, and Luxembourg. More information and registration

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

Contact Secretariat +32 (0)81 72 52 52 secretariat.info@unamur.be Student secretariat Baccalaureate and Master's students in daytime classes isabelle.daelman@unamur.be Students of the Certificate in Data Science, Master in Cybersecurity, Master in Computer Systems Architecture "Masi" in day classes amelie.notaro@unamur.be Students on shift work and BAGI master's students benjamine.lurquin@unamur.be Address Faculty of Computer ScienceRue Grandgagnage, 21B-5000 Namur

Useful links RegulationsRèglement des études et évaluations (REE)PhD regulationsCode of good conductInternal Regulations of the Faculty of Computer Science (ROI)Everyday lifeSpecial needs students - EBSLGBTQI Circle of NamurThe LGBTQIA+ youth guideCommunication awareness sheetLa Protection Harcèlement Etudiant - PHARECultural workshopsBrochure SI (licenses and software) Corporate Relations Companies, administrations and organizations wishing to obtain information or consider collaborating with the faculty are invited to contact us via the address entreprise.info@unamur.be. UNamur, like other French-speaking universities, has equipped itself with a tool to help its students and graduates develop their professional careers. The UNamur Career Center platform lets you refine your professional project, prepare for interviews and find the ideal internship or job. More about Namur Career Center Prize list for "memoirs Each year, the Faculty of Computer Science awards a prize for a dissertation that particularly stands out for its quality, originality, rigor and the scope of the results obtained. Created in 2013 as a tribute to Professor Emeritus Jean Fichefet, who played a leading role in the founding and consolidation of the Faculty of Computer Science, this prize salutes the spirit of innovation, enterprise, investing in new fields and new avenues. Since 2023, the prize has been renamed and divided into two categories:Computing dissertation prize, societal impact: a prize that tends to promote dissertations distinguished by their societal character. The themes focus on a technology or development that improves the quality of life together, or on an ethical reflection based on a technology or development studied.Computer Science dissertation prize, general impact: prize that tends to promote dissertations in all themes studied within the Faculty of Computer Science, including societal themes. Read more Map of the Faculty of Computer Science Ground Floor2nd Floor2nd floor FSESG3rd floor4th floor

As it does every year, the Faculty of Computer Science is organizing a job fair dedicated to digital professions. It's the UNamur IT Jobs Fair 2025, on Thursday 13/11 at the Arsenal.

As it does every year, the Faculty of Computer Science is organizing a job fair dedicated to digital professions. It's the UNamur IT Jobs Fair 2024, on Tuesday 12/11 at the Arsenal.