Klaas Van Gelder is an Assistant Professor of History at Vrije Universiteit Brussel (VUB) , specializing in early modern history. He is affiliated with the SHOC research group and serves as Archivist at the General State Archives in Brussels. His academic journey includes an MA (2005) and PhD (2012) from Ghent University, followed by postdoctoral fellowships at Ghent and the University of Vienna. He has held visiting roles, including at Saint Mary's University in Halifax (2024). Van Gelder’s research focuses on social, political, and cultural history of early modern Europe, particularly access to justice, litigants’ profiles, and legal rituals. Key projects include the FED-tWIN project ACCESS , examining Brabant’s legal systems, and studies on seigneurial police regulations. He has authored books like Regime Change at a Distance (2016) and edited volumes such as More Than Mere Spectacle (2021). He has received awards including the André Schaepdrijverprijs (2005) and Frans Stephan Preis (2014). His grants and collaborations include leadership roles in projects like Onderzoeksgroep Alliantie VUB-UGent . He co-edits journals and participates in international conferences, addressing topics like AI in historical archives and rural revolts.
Prof. dr. Nico Van de Weghe is a full Professor of GIScience at the University of Ghent (UGent), affiliated with the CartoGIS research unit. His work bridges computer science, social science, and natural science through geospatial information studies, focusing on enabling machines to reason spatially (GeoAI). Since 2004, he has specialized in knowledge-based AI, particularly spatiotemporal reasoning and moving object analysis, with applications in animal behavior, criminology, healthcare, mobility, and sports. Van de Weghe's research emphasizes hybrid GeoAI systems combining knowledge-driven and data-driven approaches. Keywords include GeoAI, GIScience, Spatiotemporal Analysis, Moving Objects, and Data Mining. Recent publications highlight urban road network analysis, hybrid trajectory modeling, BIM semantic enrichment, and cycling safety studies using virtual reality.
David Martens is a Professor of Data Science at the University of Antwerp , where he directs the Applied Data Mining Research Group within the Faculty of Business and Economics . He also serves as Chair of the Department of Engineering Management and Director of the Antwerp Center on Responsible AI . His academic work spans data mining , interpretable machine learning , and the societal impact of AI . PhD in Applied Economic Sciences (KU Leuven, 2008) Director, Antwerp Center on Responsible AI Chair, Department of Engineering Management Martens' research focuses on responsible AI and data ethics , with applications in finance, public policy, and behavioral analysis. His recent publications emphasize counterfactual explanations , LLM interpretability , and privacy implications in AI systems. His articles reveal trends in Explainable AI (XAI) , including narrative-driven explanations , graph neural networks , and ethical challenges like monetization risks and algorithmic bias. Keywords span Computer Science , Artificial Intelligence , and Behavioral Data . Martens is a leading voice in data science ethics , authoring the book Data Science Ethics: Concepts, Techniques, and Cautionary Tales (Oxford University Press, 2022). He combines academic rigor with industry experience, having consulted for banks, telecom firms, and startups in fraud detection and digital advertising .
Matthew B. Blaschko is a Professor in the Department of Electrical Engineering at KU Leuven, Belgium. He serves as director of the KU Leuven ELLIS unit and is a fellow in the ELLIS Health program. He is a Core PI in the Flanders AI Research Program, working as a workpackage lead for Decision Support Systems and Medical Imaging. Blaschko is also a member of the KU Leuven Institute for Artificial Intelligence and one of the leaders of the working group on Machine Learning and Data Science. Professor Blaschko received his B.S. from Columbia University, M.S. from the University of Massachusetts Amherst, and Dr. rer. nat. from Technische Universität Berlin (awarded for work at Max Planck Institutes Tübingen). He was a Newton International Fellow at the University of Oxford and received his Habilitation (HDR) from École Normale Supérieure de Cachan. Prior to joining KU Leuven, he was a Permanent Research Scientist in the INRIA Saclay Research Center and a Faculty Member at Ecole Centrale Paris. His research focuses on machine learning techniques applied to visual data, with particular emphasis on calibration in deep learning, medical image analysis, and federated learning. Blaschko's work bridges theoretical foundations with practical applications, as evidenced by technology developed in his research being incorporated into MONA, software for ophthalmic image analysis. His research group has made significant contributions to the fields of model calibration, uncertainty estimation, and medical imaging analysis, with recent publications showing strong trends toward improving reliability of AI systems in medical contexts and advancing theoretical understanding of calibration metrics. Professor Blaschko has been recognized with several awards including the Université Paris-Saclay STIC Doctoral School Best Scientific Contribution Award, Best Paper Award at CVPR 2008, Main Award at DAGM 2008, and Best Student Paper Award at ECCV 2008. Professor Blaschko has supervised numerous PhD and Master's students, with current and former students including Deniz Soysal, Claire Marchal, Dongli Xu, Sebastian Gruber, Jiameng Li, Marco Mezzina, and many others working on diverse topics from Alzheimer's disease analysis to surgical phase recognition. His research has been supported by various funding sources including the Flanders AI Research Program. He has co-organized several influential workshops including the "Another Brick in the AI Wall: Building Practical Solutions from Theoretical Foundations" at CVPR 2025, Commands 4 Autonomous Vehicles workshop at ECCV 2020, and the Learning from Limited Labeled Data workshop series at NIPS 2017 and ICLR 2019. His laboratory focuses on machine learning for medical image analysis, with applications in ophthalmology, neurology, and surgical robotics. The group maintains active collaborations with medical institutions and participates in international challenges such as the KNee OsteoArthritis Prediction (KNOAP2020) challenge.
Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.
Tim Van de Cruys is a Senior Lecturer at the Faculty of Arts, KU Leuven, serving as Head of the Centre for Computational Linguistics (CCL). He maintains significant affiliations with LECTIO (KU Leuven Institute for the Study of the Transmission of Texts, Ideas and Images), Leuven.AI (KU Leuven Institute for Artificial Intelligence), and LILI (KU Leuven Interdisciplinary Language Institute). His work bridges computational linguistics, artificial intelligence, and humanities research with practical applications across multiple disciplines. Dr. Van de Cruys specializes in computational semantics and creative language generation, with particular expertise in applying NLP techniques to historical and classical texts. His research spans multiple domains including: Natural Language Processing for ancient languages (Latin, Ancient Greek) Computational approaches to lexical and compositional semantics Large language models and their applications in humanities research Creative language generation and human-AI collaboration Named entity recognition and disambiguation in historical contexts Non-autoregressive modeling for sequential generation tasks His recent publications demonstrate a strong focus on applying cutting-edge NLP techniques to humanities challenges, particularly in processing ancient languages. He frequently employs transformer models to address named entity recognition, word sense discrimination, and semantic analysis in low-resource language contexts. His work consistently bridges formal linguistic theory with practical computational applications, creating valuable tools for digital humanities scholars. As promotor and co-promotor on numerous research projects extending through 2029, Dr. Van de Cruys supervises PhD students working at the AI-humanities intersection. His current major projects include "Living Corpora" (exploring human-AI collaboration in digital humanities), "Stochastic processes and non-autoregressive models for sequential generation," and "NIKAW" (exploring knowledge networks from classical antiquity). These projects demonstrate his commitment to advancing both theoretical understanding and practical applications of computational linguistics. He teaches various courses including Computational Linguistics, Scripting Languages, Programming for Humanities, Computational Creativity, and AI for Humanities, training students to work at this critical interdisciplinary crossroads. His leadership of the Centre for Computational Linguistics positions him at the forefront of computational linguistics research in Belgium, where he continues to expand the boundaries of what's possible at the intersection of language, computation, and humanistic inquiry.
Patrick Willems is a full Professor at KU Leuven's Faculty of Engineering Sciences, Department of Civil Engineering. He serves as the head of the Hydraulics Subdivision within the Hydraulics and Geotechnics unit. Professor Willems holds multiple significant roles including chairman of the ADS Bureau, member of the Faculty Council of Engineering Sciences, and participant in the Leuven One Health Institute and KU Leuven Institute for Urban Studies (LUSI). His work addresses critical global water management challenges through advanced hydrological modeling and climate change adaptation strategies. Professor Willems' research spans several critical areas in water resources engineering. His primary expertise includes urban hydrology and river engineering, statistical hydrology with focus on flood prediction and risk analysis, integrated river basin management, precipitation analysis, and climate change impacts on hydrological extremes. He employs both traditional hydrological modeling approaches and innovative machine learning techniques to develop practical solutions for flood warning systems, urban water management, and climate adaptation planning. His research integrates statistical methods, numerical modeling, and data science to address complex water management problems across multiple geographical contexts. Professor Willems leads multiple major international research projects examining hydrological extremes in transboundary river basins, natural climate adaptation measures, hydrological modeling of peatland areas, and deep learning-based prediction of hydrological extremes. His work spans various geographical contexts including Belgium, Vietnam, Bolivia, Tanzania, and the Congo Basin, demonstrating both local relevance and global applicability of his research. Within KU Leuven, Professor Willems teaches diverse courses including Environmental Problems and Techniques, Statistics and Data Science, Stochastic Hydrology, Urban and River Hydrology and Hydraulics, River Modeling, and Probability and Statistics. He also leads the Hydraulic Engineering Project course and an Artificial Intelligence Project course, reflecting his commitment to integrating traditional engineering knowledge with modern computational approaches. As head of the Hydraulics Subdivision, he oversees research activities focused on developing advanced water engineering tools and methodologies that bridge theoretical advancements with practical applications for water management authorities.
Johan Driesen is a full Professor at KU Leuven's Faculty of Engineering Sciences, where he serves as Department Head of Electrical Energy Systems and Applications (ELECTA) and Director of the KU Leuven Institute for Energy and Society (KIEM). He also holds leadership positions at EnergyVille as Division Head and Subdivision Head. His work spans both academic and applied research in electrical energy systems. His research interests focus on renewable energy integration, power electronics, electrical drives, electric vehicles, and smart grids. Driesen's work particularly emphasizes distributed generation of electricity, with significant contributions to floating photovoltaics, offshore wind integration, and low-voltage DC systems. His research group actively investigates the optimization of grid integration for renewable energy sources and the development of advanced power electronic converters. Driesen's recent publications reveal a strong emphasis on practical applications of renewable energy systems, with particular focus on reliability analysis of low-voltage DC systems, optimization of PV-battery systems, and integration of electric vehicles with renewable energy sources. His work bridges theoretical analysis with real-world implementation challenges. Laureate prize of the Belgian Royal Society of Electrotechnics (KBVE/SRBE) 'Research and Development' for master theses 1996 2nd place in final round IEEE Region 8 Student Paper Contest 1997 in München, Germany Laureate biannual prize 'R.Sinave' of the Belgian Royal Society of Electrotechnics (KBVE/SRBE) for best PhDs 2002 Driesen has supervised numerous students and researchers, including J. Despeghel who completed work on residential PV-battery system optimization. His current research portfolio includes substantial projects such as Flux50 (working on the future energy system), solar and wind energy in the Belgian marine zone, and smart charging solutions that integrate e-mobility with renewable energy. He serves as promoter or co-promoter on multiple major research initiatives with funding extending through 2028. At EnergyVille, Driesen leads research teams working on cutting-edge energy solutions, with particular focus on DC systems, grid integration challenges, and the development of innovative power electronic solutions for renewable energy applications. His work has significant industrial relevance and practical implementation potential.
Julie Dethier is a Research Fellow at the University of Liège, affiliated with the Faculty of Applied Sciences and Montefiore Institute. Her research bridges cellular neuroscience and network dynamics, with focus on pathological rhythms in Parkinson's disease and brain-machine interface development. She completed her Ph.D. in 2015 under Prof. Sepulchre's supervision. Her academic journey includes: Ph.D. in Systems and Modeling (2015), University of Liège with Princeton University research stay (2014-2015) Master of Science in Bioengineering (2011), Stanford University (Brains in Silicon lab) Master of Applied Sciences in Biomedical Engineering (2010, summa cum laude), University of Liège Bachelor of Applied Sciences (2008, summa cum laude), University of Liège Dr. Dethier investigates how cellular feedback mechanisms generate pathological beta oscillations in basal ganglia circuits, disrupting motor function in Parkinson's disease. Her computational approaches model the transition from unicellular rhythms to network-level oscillations, with implications for deep-brain stimulation therapies. She integrates electrophysiological data with dynamical systems theory to explain robustness and modulation in neural circuits. Her publication record demonstrates evolving expertise from brain-machine interface hardware (2011-2012) to fundamental neural mechanism studies (2013-2015). Key themes include spiking neural network decoders, cellular feedback loops, and pathological oscillation generation. Work spans computational modeling, neuromorphic engineering, and translational neuroscience with applications in neuroprosthetics. Major recognitions include: WBI excellence grant for Princeton research (2014) LEAR Foundation Fellowship for Cambridge research (2013) Audience Award at ULg thesis competition (2013) IEEE EMBS Best Poster Award (2011) Fulbright Honorary Fellowship and Rotary International Fellowship (2010) Funded by competitive F.R.S.-FNRS and international fellowships, her research involved cross-institutional collaboration with Princeton, Cambridge, and Stanford teams. While no formal advisees are listed, her publications reflect mentorship through co-supervised projects and conference presentations. Current work extends her doctoral thesis on multiscale neural dynamics. She maintains active ties with the Systems and Modeling Research Unit at Liège, Brains in Silicon lab at Stanford, and participates in Benelux neuroscience networks through the Montefiore Institute.
Prof. Ilse Dewachter is the head of the Biomed Neuroscience research group at Hasselt University (UHasselt), specializing in Alzheimer’s therapy and prevention for over 25 years. Her work focuses on multi-targeted therapies targeting tau, inflammation, and ApoE, alongside pioneering research into disease prevention via blood-based biomarkers. Recent studies explore a protective APOE3ch mutation that halted Alzheimer’s progression in a patient, offering hope for new treatments. Research Interests: - Alzheimer’s disease mechanisms (Abeta, tau, inflammation) - Multi-target therapies and biomarker development - Neurodegenerative disease prevention strategies - Genetic mutations impacting disease progression Articles Overview: Her most recent work (2025-2022) addresses neuroinflammation, tau propagation models, and AI-driven neuroimaging. Key themes include APOE genetics, blood-brain barrier dynamics, and exercise impacts on cognition. Funding & Grants: Current projects require significant investment for advanced biomarker equipment and clinical trials. A notable €300,000 grant funded research on brain lipid metabolism’s role in Alzheimer’s. Labs & Teams: Leads the BIOMED Neuroscience group at UHasselt, collaborating internationally on preclinical models and drug development.
Tom Dhaene is a Full Professor at Ghent University, affiliated with the Department of Information Technology (INTEC-IDLab) within the Faculty of Engineering and Architecture (FEA). He also holds a position at imec, a research and innovation hub in nanoelectronics and digital technologies. Research Unit: Internet Technology and Data Science Lab (IDLab) Academic Rank: Full Professor Affiliations: Ghent University, imec His research focuses on data-efficient machine learning, surrogate modeling, Gaussian processes, Bayesian optimization, and system identification. He has developed widely used software tools such as the SUMO toolbox and ooDACE, and holds 5 U.S. patents. His work bridges theoretical advancements with practical applications in engineering and biomedical domains. Recent publications highlight his contributions to physics-informed machine learning, antenna design, microwave optimization, and healthcare applications. Notably, he explores Bayesian active learning, multi-objective optimization under uncertainty, and efficient modeling techniques for complex systems. Prof. Dhaene's research has been recognized through over 500 peer-reviewed publications and collaborations across academia, industry, and government sectors globally.
Bruno Volckaert is a Professor in the Department of Information Technology at Ghent University and Senior Researcher at imec. He obtained his Master of Computer Science (2001) and PhD in Grid Computing Resource Management (2006) from Ghent University. His research focuses on distributed cloud systems for Smart Cities and Industry 4.0 applications. Volckaert's expertise spans: Reliable distributed cloud backend systems Autonomous optimization of cloud applications Cybersecurity through machine learning IoT data processing architectures Kubernetes-based container orchestration Edge-to-cloud continuum computing His publications demonstrate strong focus on: cloud-native technologies, Kubernetes optimization, cybersecurity frameworks, and distributed AI systems. Recent work emphasizes reinforcement learning for auto-scaling, secure edge computing, and intrusion detection systems. He has contributed to over 40 national/international research projects and authored 100+ publications. Current affiliations include leadership roles in: IDLab Research Unit (Ghent University) imec Research Center
Hans Steenackers is an Associate Professor at the Faculty of Bioscience Engineering, KU Leuven, where he leads the MICA Lab within the Department of Microbial and Molecular Systems. His research focuses on innovative antimicrobial strategies targeting microbial communities, including socio-active, anti-resistance, and observation-guided approaches. Key research areas include biofilm dynamics antimicrobial resistance evolution in situ microbial monitoring Salmonella Typhimurium pathogenesis anti-virulence therapies His recent publications highlight advancements in biofilm inhibition, triggered antimicrobial release systems, and evolutionary robustness of probiotics. The majority of his work involves interdisciplinary collaborations, particularly in projects like TARDIS, ULTiMatE-MS, and MICROTUNe, with a focus on translating fundamental research into clinical applications. As an educator, he teaches advanced courses in microbial physiology, biofilm research, and applied biotechnology. The MICA Lab actively partners with academic and industrial stakeholders in initiatives such as the Flemish Scientific Research Network on Biofilms and the Bioclean H2020 project.
Charles-Henry Bertrand Van Ouytsel is a Research Assistant and Visiting Lecturer at Université catholique de Louvain , affiliated with the Louvain Polytechnic School (EPL) and the Computer Engineering Center (INGI) . His work focuses on malware analysis , symbolic execution , and machine learning for cybersecurity applications. Research Areas : Packing detection, intrusion detection systems, side-channel security, and adversarial machine learning. Teaching : Involved in courses like Secured systems engineering (LINFO2144) and Software engineering and programming systems seminar (LINFO2359) . His recent publications emphasize malware obfuscation techniques and security evaluation frameworks . Collaborations with Axel Legay and others highlight his contributions to tool development (e.g., Packing-Box , SEMA ). No scientific awards are explicitly mentioned.
Steven Devleminck is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Technology, concurrently serving as coordinator of the School of Arts (Associated Faculty) in Brussels. His dual appointment bridges engineering and arts through the Human-Computer Interaction (HCI) group at Group T Leuven Campus and Unit Art & Technology in Brussels, with active membership in DigiSoc – KU Leuven Digital Society Institute. His research centers on human-centered computing and speculative design methodologies , with core expertise in tangible interaction for emotion regulation and multispecies futures. Key themes include biofuturing as co-creative response to climate crises, squeeze-based interfaces for workplace stress, and artistic AI collaborations. His work uniquely integrates computer science with choreography, film studies, and anthropology through projects like “Youth TikTok production as public pedagogy” and “Imagining the Post-Anthropocene in BioFutures Living Lab”. Analysis of recent publications reveals three dominant trajectories: (1) Advancement of squeeze interaction techniques for affective computing, (2) Development of biofuturing frameworks for multispecies speculation, and (3) Critical examinations of AI's role in artistic mediumship. Cross-cutting themes include post-anthropocentric design, climate-responsive technologies, and decolonial approaches to digital pedagogy. Devleminck actively mentors doctoral candidates including Ula Sickle (choreographic exhibitions) and J. Verbesselt (cinema studies), while leading major funded projects such as: Living Corpora (2025-2029): Pioneering human-AI collaboration in digital humanities as Co-promotor Experiential Futuring (2022-2026): Co-creative methodology for social media outage response as Co-promotor Deradicalizing the City (2021-2025): Urban intervention research as Promotor He serves on the Computer Science Department Council and Doctoral Committee for the Associated Faculty of Arts. His laboratory ecosystem spans the HCI Group T Leuven Campus for technical development, Brussels-based Unit Art & Technology for artistic integration, and BioFutures Living Lab for participatory multispecies experimentation. This tripartite structure enables transdisciplinary work connecting squeeze sensor engineering with climate futures speculation and museum interface design.
