Title Promoter Affiliations Abstract "COMPASs - COMbining interdisciplinary Perspectives on Artificial intelligent Systems: navigating towards human-centred Artificial Intelligence" "Jan Danckaert" "Informatics and Applied Informatics, Electronics and Informatics, Mathematics, Communication Sciences, Business technology and Operations, Applied Physics and Photonics, Physics" "In this project we want to contribute to the development and the deployment of human-centred Artificial Intelligent systems. Despite tremendous progress in the past few years, the field is currently facing some of the most important challenges at the interface between theoretical computer science, applied data science, and sociotechnical studies. Indeed, the most successful machine learning models (deep neural networks) are non-transparant, highly non-intuitive, and therefore difficult to understand. Here, we join forces to tackle this problem on three different levels. First, we want to use different techniques to overcome the traditional interpretability vs learning performance trade-off, e.g., through the identification of novel neural network building blocks and through the implementation of causal inference techniques in neural networks. Then, we want to develop tools to interrogate true black box systems, i.e., systems where only the outcome is observed (and nothing of the internal process). This will be done through test data set optimization and the training of a meta-neural network, an algorithm that learns to predict the internal structure of a black box. Finally, we want to find efficient ways to valorise the academic insights in society through the development of recommendations and tools that can be used to train and validate trustworthy neural networks in a real-life environment. The integration of these actions will ideally ensure that Artificial Intelligence will be applied in a more conscious way and more aligned with our values." "Intelligent contracting: legal aspects of the precontractual use of artificial intelligence" "Bernard Tilleman" "Faculty of Law and Criminology, Kulak Kortrijk Campus, Centre for Methodology of Law, Electronic Circuits and Systems (ECS)" "The precontractual use of artificial intelligence (AI) systems is on the rise. Parties increasingly often use such systems as a source of information, or they delegate the negotiation and formation of the contract to AI systems. Alternatively, they may leave it to the AI system to determine certain elements of their agreement, to avoid having to determine them themselves. This is highly problematic, as the application of the legal regime to such uses of AI systems is ambiguous. This is caused by the focus of the existing legal regime on humans. Consequently, concepts like ‘diligence’, ‘fault’ and even ‘human will’ are hard to apply to AI systems.The present research aims to eliminate this ambiguity. To this end, the application of these legal rules to AI systems is considered. Subsequently, it is considered whether this application can be positively evaluated. To the extent that this is not the case, adaptations to the contract law framework are proposed, that will help the existing legal system deal with current and future technological evolutions." "The KU Leuven Institute for Artificial Intelligence (Leuven.AI): an interdisciplinary collaboration regarding artificial intelligence." "Luc De Raedt" "Declarative Languages and Artificial Intelligence (DTAI)" "The mission of Leuven.AI is to 1) Unite AI and its renowned AI experts at KU Leuven in an interdisciplinary centre of excellence. 2) Foster AI research by providing a forum for exchanging ideas and for initiating projects and collaborations on AI.3) Foster AI education by offering courses and contributing to education programmes.4) Offer expertise on all aspects of AI, including on the possibilities and limitations of AI and its implications from an ethical, legal and societal perspective.The initial project is concerned with the building up phase of the institute, and its primary scientific goal is to identify, exploit and help developnew show-case applications of AI within the KU Leuven itself.   " "Military artificial intelligence beyond autonomous weapons: an examination of the legal implications of using non-weaponised artificial intelligence in armed conflict" "Jan Wouters" "Institute for International Law" "The development and deployment of artificial intelligence in the military domain (military AI) encompasses a broad range of applications, including autonomous weapons and non-weaponised AI, which may impact how States make warfare decisions and thus whether they comply with international law. Despite the extensive applications of military AI, scholarly research has narrowly focused on autonomous weapons, overlooking the implications of non-weaponised AI for the application of international law. This doctoral project aims to fill this knowledge gap by assessing whether existing international law rules are fit to regulate the use of non-weaponised AI in armed conflict. The researcher will analyse the applicable rules of jus ad bellum, jus in bello, state responsibility and international criminal law, and assess whether they are sufficient and appropriate to regulate the use of non-weaponisedAI. The researcher will also formulate recommendations on how the international community should approach the regulation of non-weaponised AI." "eXplainable Artificial Intelligence to embed new-generation Artificial Intelligence architectures for brain signal analysis in clinical scenarios" "Mario Cimino, Maarten De Vos" "Dynamical Systems, Signal Processing and Data Analytics (STADIUS)" "This research project aims to find new, effective, and trustable data-driven approaches to correctly classify human physiological signals, performing classification and outlier detection. The above can effectively support the medical diagnosis of cognitive and psychological disorders such as anxiety, autism, or depression in biomedical applications. Furthermore, the project aims to construct explainable methods to correctly identify and clarify the classification process, to let those methods be integrated into biomedical scenarios." "Artificial intelligence in education" "Tom Madou" "Onderwijsinnovatie, Business Management" "It is impossible to imagine the educational landscape without digital learning resources. Educational institutions invest heavily in technology and rightly expect a return on investment. Making learning processes more efficient and effective is one of the benefits that is pursued. This project aims to increase the return on investments made in educational technology by integrating artificial intelligence (AI) in digital education. AI techniques are used to gain insight into the learning process that students go through. An automated (artificially intelligent) form of learning analytics should provide teachers with the information they need about the learning behavior of their students to make learning activities more effective and efficient. The intended finality consists of an accessible step-by-step plan for teachers to get started with AI and a well-functioning back end that makes this possible. This project is primarily relevant for all teaching staff at VIVES University of Applied Sciences. The translation to other educational institutions, both at KU Leuven association level and beyond, can be made quickly." "Utilizing Behavior-Based Artificial Intelligence Against Cyber-Industrial Attacks (GAICIA)" "Daniel Du Seuil, Kurt Schoenmaekers" "Researchgroup Applied Informatics, HOWEST, UGent -> UGENT Vakgroep Industriële Systemen en Productontwerp" "How can we protect industrial networks from cyberattacks by using artificial intelligence to predict hackers' behavior? GAICIA (Utilizing Behavior-Based Artificial Intelligence Against Cyber-Industrial Attacks) seeks to answer this question during this research. The goal is to provide tailored solutions for Flemish SMEs (often through their system integrators) for the successful implementation of an OT network monitoring tool and the application of artificial intelligence for detecting cyberattacks in an industrial process. We will transfer the acquired knowledge to Flemish manufacturing companies and also train and involve the system integrators working for them in the project. Thanks to the acquired knowledge and open-source software components, non-R&D intensive companies will be able to defend themselves against cyberattacks." "PRIMORDIAL – An artificial intelligence (AI) driven prediction model to detect risk factors for medication-related osteonecrosis of the jaws." "Reinhilde Jacobs" "Oral and Maxillo-facial Surgery - Imaging & Pathology (OMFS-IMPATH), Universiteit Antwerpen" "Bone health equilibrium can be altered by disease and the use ofmedication. Antiresorptive drugs are frequently used and highlyeffective to prevent bone metastasis in patients with cancer. Yet,their use is associated with the occurrence of medication-relatedosteonecrosis of the jaw (MRONJ), a potentially debilitating sideeffect characterized by exposed necrotic bone in the oral cavity,infection, and painAlthough research on advanced MRONJ lesions have beenpublished, so far little is known on the early disease stages, the initialimaging features and potential preventive measures related to earlydetection and disease prediction. Likewise, radiological risk factors toidentify a successful outcome or therapy resistance have not yetbeen described. Therefore, the main objective of this project is tobuild an automated prediction model (radiomics) to allow predictionof MRONJ induction and its response to treatment. This could bereached by the following subobjectives:1. To identify the radiological and genetically predisposing factors todevelop MRONJ2. To describe risk factors influencing treatment outcome in patientswith MRONJIn order to obtain the subobjectives, 2 studies will be carried out:o A prospective cohort study to follow-up patients at risk for MRONJdevelopment enabling to identify risk factors.o A retrospective cohort study in patients MRONJ that underwentsurgical or conservative treatment to identify radiological featuresassociated with treatmentTitle of your research proposalEnglish Title PRIMORDIAL – An artificial intelligence (AI) driven prediction modelto detect risk factors for medication-related osteonecrosis of the jaws.Dutch Title PRIMORDIAL – Een voorspellingsmodel op basis van artificiëleintelligentie (AI) om risicofactoren voor medicatie-gerelateerdeosteonecrose van de kaken op te sporen.GENERAL- 1" "Artificial Intelligence Data Analysis" "Giovanni Lapenta" Plasma-astrophysics "AIDA brings a transformational innovation to the analysis of heliophysics data in four steps.First, AIDA will develop a new open source software called AIDApp written in Python (a free language) and capable ofcollecting, combining and correlating data from different space missions. AIDApp wants to replace mission-specific toolswritten for costly languages (such as IDL) that exclude many scientists, students and amateur space enthusiasts fromexploring the data, with a much-needed single platform where methods are shared and continuously improved by the wholecommunity.Second, AIDA will introduce modern data assimilation, statistical methods and machine learning (ML) to heliophysics dataprocessing. Unlike traditional methods based on human expertise, these methods rely on statistics and information theory toextract features that are hidden in the data.Third, AIDA will combine real data from space missions with synthetic data from simulations developing a virtual satellitecomponent for AIDApp. This feature will be demonstrated in the comparison with existing mission data and in the planning ofnew missions (e.g. ESA’s THOR).Fourth, AIDA will deploy in AIDApp methods of Artificial Intelligence (AI) to analyse data flows from heliophysics missions.This task requires bridging together competences in computer science and in heliophysics and pushes well beyond thecurrent state of the art in space data analysis, connecting space researchers with AI, one of the fastest growing trends inmodern science and industrial development.AIDA will use the new AIDApp in selecting key heliophysics problems to produce a database (AIDAdb) of new high-leveldata products that include catalogs of features and events detected by ML and AI algorithms. Moreover, many of the AImethods developed in AIDA will themselves represent higher-level data products, for instance in the form of trained neuralnetworks that can be stored and reused as a database of coefficients." "Artificial Intelligence Inspiration" "Gilles Depypere" "Researchgroup Research, Services and Entrepreneurship, Researchgroup Sizing Servers, Breda Robotics, Avans Hogeschool / Stichting Avans, Provinciaal netwerk van stedelijke ondernemingscentra (OC West), Odisee, TUA West, Vives, Fontys Hogeschool" "The project 'Artificial Intelligence Inspiration' (Art-Ie) aims to strengthen the cross-border region of Flanders-Netherlands in the field of digital innovation, with a focus on Artificial Intelligence (AI). It primarily seeks to bring together small and medium-sized enterprises (SMEs) with knowledge institutions. Digital innovation has become integral to our society and will only increase in importance. Although the COVID-19 crisis has accelerated the trend of digitization in both Flanders and the Netherlands, there are still numerous challenges, especially for the many SMEs in West and East Flanders and Brabant. This project aims to strengthen the cross-border region of Flanders-Netherlands and, in particular, bring SMEs together with knowledge institutions. Central to this project are the Flemish and Dutch universities of applied sciences, which, with their expertise and state-of-the-art infrastructure, are well-placed to introduce companies to innovative digital technologies, especially their practice-oriented research in AI. As a stepping stone to collaboration with universities, we aim to inspire SMEs in the field of innovative digital technologies and introduce them to our universities as seamlessly as possible, along with their expertise and infrastructure in innovative digital technologies in general and AI in particular. We will establish three cross-border AI labs, each with its specific expertise. We provide SMEs with the opportunity to actively collaborate with a university of applied sciences by addressing an innovation challenge in one of the cross-border labs. We focus on various aspects of AI with applications in different domains."