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Our training center offers a wide range of training courses for teaching and support professionals.The training courses we offer are created on the basis of emerging needs in the field, our research findings and recent scientific literature updating promising practices for professionals.

This specialization master's program is designed for higher education teachers working either in university teaching (assistants and professors) or in higher education outside universities (Hautes écoles). It aims to carry out applied research, in the professional field of the program's students.

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.

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

Instantly obtain a translation in sign language (LSFB) of a word written in French: that's what MOSI (Du mot au signe) makes possible. This new tool is the fruit of a collaboration between the University of Namur, the asbl École et Surdité and the asbl LSFB, supported by the King Baudouin Foundation.

François Briard graduated in Law and Management of Information Technology (DGTIC) in 1994 after obtaining his bachelor's and master's degrees in computer science in 1993. He works at CERN, the European Organization for Nuclear Research in Geneva, the world's largest particle physics laboratory. During his schooling, which was 100% at UNamur, he was vice-president of the Namur Region and student delegate during his application years in economic and social sciences, computer science option. Thanks to the multidisciplinary training provided at UNamur, he was able to seize several opportunities to reorient his career within CERN.

A choir of robots sounds like science fiction! Yet it is a reality at the University of Namur. In the robotics laboratory of the Faculty of Computer Science, researchers from the naXys institute, led by professors Elio Tuci and Timoteo Carletti, some members of TRAKK, some artists and external partners collaborated on the "Synthetic Choirs" project.

Take part in our open morning Given the works in the rue de Bruxelles and the renovation of part of the University parking lots, we invite you to use public transport whenever possible (train or bus) to reach Namur. UNamur boasts an ideal location, in the heart of the city just a five-minute walk from the TEC and SNCB train stations.If you're coming by car, take a look at the parking map provided. Look forward to seeing you on Saturday, June 29!

In late November 2024, UNamur hosted the 23rd BENEVOL Congress, an annual research seminar that provides an opportunity for international researchers to meet and discuss new ideas, important issues and cutting-edge research in the field of software engineering, maintenance and evolution.

Save the date! On Saturday June 28, 2025, from 1pm to 5pm, UNamur once again opens its doors to you before the summer vacations.At the programProfessors, assistants, students and staff members look forward to welcoming you to answer all your questions about your future studies;share with you their experience of university life and its many opportunities for fulfillment;guide you through your final practical steps: registration, preparatory courses, finding accommodation, financial aid and more.Forthcoming informationThe afternoon's detailed program will be available some ten days before the event. Find out more about the open house

A program for every discipline During late August and early September, UNamur offers rheto students preparatory courses tailored to their future training.These revision sessions are specially designed to support students in their transition to university. By reinforcing their foundations in the key subjects of their future discipline, they enable them to approach their first year with confidence. These preparatory courses are also an excellent opportunity to discover the campus, meet future classmates and familiarize themselves with the learning methods specific to higher education. Discover the preparatory courses Preparation for the medical entrance exam For students wishing to begin studying medicine, two sessions are also organized according to a specific timetable to prepare for the entrance exam. Discover the preparatory courses for the entrance exam to medicine