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.
Daan Christiaens is a tenure track lecturer at KU Leuven's Faculty of Medicine and Faculty of Engineering Sciences. He is affiliated with the Department of Electrical Engineering (ESAT) and Department of Imaging & Pathology, serving as a member of the Medical Imaging Division and the KU Leuven Brain Institute (LBI). His academic responsibilities include membership in the Faculty Councils of Engineering Sciences and Medicine. His research focuses on: Inverse problems in medical imaging reconstruction Neuroimaging techniques for brain analysis Advanced quantitative MRI methodologies Diffusion-weighted imaging for microstructural assessment Dr. Christiaens' recent publications (2023-2025) demonstrate a consistent focus on diffusion MRI innovations, including novel reconstruction algorithms, neonatal brain development mapping, and clinical applications for neurodegenerative disorders. Key technical themes include motion correction, multi-shell modeling, and AI-enhanced image processing, while clinical applications span Alzheimer's disease, cerebral palsy, and autism research. He leads significant research projects including: MRI reconstruction with dynamic field monitoring (2024-2028) Compressed sensing for microstructure imaging (2022-2026) Neonatal diffusion MRI network connectivity analysis (2024-2028) As a core developer of the MRtrix3 software framework for medical image processing, he contributes to essential tools in neuroimaging research.
Yves Wautelet serves as an Associate Professor at the Faculty of Economics and Business at KU Leuven, where he conducts research in conceptual modeling, business process management, and digital transformation. His work addresses critical challenges at the intersection of information systems engineering and business strategy, with particular focus on sustainability-driven modeling approaches and IT governance frameworks. His primary research interests include: Conceptual modeling methodologies and frameworks Business process management and information systems design Digital transformation strategies and implementation IT governance and business-IT alignment Sustainability-driven modeling for circular economy Agile software development practices and methods Requirements engineering with user stories Wautelet's recent publication record demonstrates significant scholarly productivity with numerous 2024-2025 publications spanning conceptual modeling frameworks for sustainability (Circulise), tools for identifying ambiguity in user stories (AmbiTRUS), and approaches to align strategic and operational agility. His work bridges theoretical foundations with practical applications across diverse domains including healthcare, circular economy, software development, and organizational transformation. His research consistently applies model-driven approaches to solve complex real-world problems, often integrating sustainability considerations into information systems engineering. As a promotor and co-promotor, Wautelet currently supervises multiple doctoral research projects including: Automatic generation of conceptual models from textual descriptions (2024-2028) Sustainability-Driven Modeling Assistant for Twin Transition in Vietnam (2024-2028) Home Care Business Process Management using Distributed Ledger Technologies (2024-2028) Teaching Modeling Skills in BPMN formalism (2021-2025) His research is conducted through the Information Systems Engineering Research Group (LIRIS) at KU Leuven's Brussels campus, where he contributes to advancing model-driven approaches for addressing contemporary business and technological challenges.
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.
Ruben Verborgh is a Professor of Decentralized Web Technology at the Ghent University – imec and a Visiting Fellow at the Oxford Martin School (University of Oxford). He leads the Internet Technology and Data Science Lab (IDLab) and co-founded the Solid platform with Tim Berners-Lee to re-decentralize the Web. His research focuses on Linked Data Fragments , a paradigm for Web-scale query execution, and explores decentralized data governance , user-controlled data ownership , and rule-based Web agents for policy enforcement. He has co-authored two books on Linked Data and contributed to over 250 publications. Recent articles highlight trends in decentralized data ecosystems , including ODRL policy interoperability , event notification systems , and personal data vaults . His work bridges Linked Data , hypermedia APIs , and privacy-preserving technologies . Verborgh collaborates with institutions like MIT, Oxford, and the European Commission, and advises companies through Inrupt . His labs ( IDLab , Solid Ecosystem ) focus on sustainable data-driven societies.
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
An Verberckmoes is an Associate Professor at Ghent University in the Faculty of Engineering and Architecture, specifically within the Department of Materials, Textiles and Chemical Engineering. She is affiliated with multiple research units including the Biomolecules Center for Sustainable Chemistry, ChemTech Materials, and the Industrial Catalysis and Adsorption Technology group. Her research expertise centers on heterogeneous catalysis with a strong focus on sustainable chemical processes. Dr. Verberckmoes specializes in catalyst synthesis, particularly zeolite-based catalysts for bio-alcohol conversion and lignin valorization. Her work bridges fundamental catalyst design with practical applications in biomass conversion, aiming to develop more efficient and environmentally friendly processes for producing renewable chemicals and materials. Analysis of her recent publications (2024-2025) reveals a dominant research trajectory focused on lignin depolymerization technologies, with particular emphasis on catalytic approaches using noble and non-noble metals. She has made significant contributions to understanding reaction mechanisms in zeolite catalysis, especially for dehydration reactions of bio-alcohols to valuable chemicals like butadiene. Her work often combines experimental approaches with kinetic modeling to optimize both catalyst performance and process conditions. Dr. Verberckmoes collaborates extensively within Ghent University and with external partners on projects related to sustainable chemistry and biomass conversion. Her research group appears to focus on developing integrated approaches that combine catalyst design, process engineering, and advanced analytical techniques to advance lignin valorization and sustainable chemical production.
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.
Bruno Tiago da Silva Gomes is a Researcher in the Department of Electronics and Informatics at Vrije Universiteit Brussel (VUB), Belgium. His work focuses on FPGA-based hardware acceleration, biomedical signal processing, and embedded systems. He leads several high-impact projects, including ENACT (environmental health interventions) and Tech4Health (future health technologies). His research spans FPGA design, machine learning acceleration, and real-time signal processing. Education: PhD in Electronics and Informatics (2019, VUB), supervised by Professors Touhafi and Braeken. His thesis addressed streaming application acceleration on FPGAs. Research interests include Field-Programmable Gate Arrays (FPGA), biomedical sensors (e.g., photoplethysmography), beamforming, and high-level synthesis. He has co-authored over 60 publications and holds an h-index of 439. Key projects include OZR4103 (power-efficient AI for biomedical applications) and NSIS3 (decarbonisation technologies). His work integrates hardware-software co-design for edge computing and secure TinyML systems. Advising includes a Master’s thesis on PPG signal analysis. He contributes to datasets like the AMIVU Acoustic Map Imaging Dataset.
Peter Karsmakers serves as Associate Professor at KU Leuven's Department of Computer Science within the Faculty of Engineering Technology, based at the Geel Campus. He coordinates the Declarative Languages and Artificial Intelligence (DTAI) research group and holds leadership roles including coordinator of Research and Education for Computer Science across Geel and Diepenbeek Campuses. Karsmakers earned his PhD in Engineering Science in May 2010, focusing on kernel-based learning algorithms for sparse modeling and efficient predictions from large datasets. His doctoral work established foundations for his current research trajectory in resource-constrained machine learning systems. His research integrates machine learning with signal processing for real-time sensor data interpretation, specializing in anomaly detection from acoustic, radar, and accelerometer signals on embedded devices. Current projects address industrial condition monitoring, elderly care systems, and livestock facility monitoring through three main tracks: acoustic monitoring (e.g., SINS, WATCHDOG), radar-based systems (e.g., FARADAY, NextPerception), and smart electronics for power converters. Recent publications demonstrate strong trends in constraint-guided deep learning architectures for industrial applications, cross-environment robustness in sensor systems, and domain-knowledge integration to reduce data requirements. His work consistently bridges theoretical machine learning with practical implementations in resource-constrained environments. No scientific awards or fellowships were mentioned in the provided materials. Karsmakers supervises over 10 master's theses annually and coordinates a research team of 10 PhD students and a post-doc within DTAI-ADVISE. He has secured approximately 2.3 million euros in funding through VLAIO, EU-ECSEL, and bilateral industry contracts, including 10 active projects such as AutoEdgeML (2024-2028) and Fault Tolerant Neural Networks for Space Applications (2024-2027). He leads the DTAI-ADVISE research group focused on developing software that attaches semantics to sensor data on resource-constrained devices. The team operates across multiple campuses with specialized labs for acoustic monitoring (Geel), radar-based systems (in collaboration with ESAT-TELEMIC), and smart electronics (with Electrical Engineering department), maintaining strong industry partnerships with companies in healthcare, manufacturing, and agriculture sectors.
Vincent Bonin is a Senior Lecturer in the Department of Biology at KU Leuven's Faculty of Sciences. He is affiliated with the VIB-KU Leuven Center for Neuro Electronics Research Flanders (NERF) and the KU Leuven Brain Institute (LBI). His research focuses on neural circuits and visual neuroscience, with an emphasis on cortical and subcortical mechanisms of perception and plasticity. Research Interests: Vincent investigates visual coding, cortical connectivity, and brain circuit dynamics. His work spans topics like: Role of non-hierarchical visual pathways in perception Dendritic processing in the superior colliculus Cell type-specific connectivity in layer 2/3 visual cortex Astrocyte-mediated cortical plasticity Development of high-resolution intracortical visual prosthetics Recent Projects: • The contributions of non-hierarchical visual pathways to visual coding and perceptual behavior (2025-2028) • An investigation into cell type-specific connectivity rules in visual cortex (2024-2027) • Short- and long-term circuit mechanisms of motor rehabilitation after spinal cord injury (2024-2027)
Lucca Geurts is a Senior Lecturer at the Faculty of Industrial Engineering Sciences at KU Leuven, where he is affiliated with the Department of Computer Science. He serves as chairman of the Leuven Centre for Accessible Health Technology, subdivision head of Subdivision 3, Campus Group T Leuven, and Head of Education of the OC Innovative Health Technology. Additionally, he is an active member of DigiSoc – KU Leuven Institute for Digital Society. His research focuses on Technology for Tangible and Playful Interactions, particularly in healthcare applications. Dr. Geurts leads numerous research projects including therapeutic games for children with visual disorders, flexible activity measurement systems, intimate interactive systems, and early-stage glaucoma screening platforms. His work bridges human-computer interaction with accessible health technology, emphasizing user-centered design principles and practical healthcare solutions. Dr. Geurts' publication record demonstrates a consistent trajectory from fundamental interaction techniques to applied healthcare contexts. His recent work shows increasing sophistication in squeeze interactions, emotion regulation through tangible interfaces, and medical applications of interactive technology. The research trends indicate a growing focus on accessible medical diagnostics, therapeutic applications, and user experience in healthcare technology. As an educator, Dr. Geurts teaches across multiple domains including Electronics, Computer Architectures, Health Entrepreneurship, Sensors and Circuits for Healthcare Applications, and Extended Reality. His educational leadership extends to Master's theses and internships in health engineering, reflecting his commitment to training the next generation of healthcare technologists. Committee for Culture, Art and Heritage Faculty Council of Industrial Engineering Sciences Evaluation Committee of the Faculty of Industrial Engineering Sciences POC Advanced Education Faculty of Industrial Engineering Sciences Secretary of the OC Innovative Health Technology Departmental Council for Computer Science Interfaculty Council for Global Development (as substitute member) Dr. Geurts maintains an active research profile with numerous publications in top-tier human-computer interaction conferences and journals. His work shows a clear progression toward increasingly impactful healthcare applications, with strong emphasis on accessibility and user experience in medical technology development.
Marian Verhelst is a Professor at KU Leuven's Faculty of Engineering Science, renowned for her research in hardware-efficient computing and dedication to STEM education. Her work spans hardware acceleration for machine learning, edge AI, and in-memory computing, with a focus on energy optimization and algorithm-hardware co-design. Her research interests include: Designing flexible hardware for ultra-low-power edge AI systems Optimizing sparsity-aware architectures for deep learning workloads Advancing chiplet-based and 3D memory technologies Co-designing algorithms and hardware for probabilistic AI Pioneering STEM outreach through KU Leuven InnovationLab Recent publications (2023–2025) demonstrate strong trends in: Hardware-software co-optimization for edge ML systems Efficient data movement in heterogeneous accelerators Low-precision and sparse computation techniques RISC-V based customizable SoCs Sustainable AI accelerator design Awards & Honors: Young Academy of Europe Award (2021) for science communication and STEM advocacy She leads significant educational initiatives, including the KU Leuven InnovationLab which has engaged 150 schools and 13,000 students since 2014. The program develops hands-on STEM projects (e.g., AI-powered wheelchairs, sustainable energy systems) and provides teacher training to inspire youth in engineering.
Kevin Van Geem is a full professor at Ghent University's Faculty of Engineering and Architecture, leading the Laboratory for Chemical Technology (LCT) and directing the Center of Sustainable Chemistry. His research focuses on thermochemical reaction engineering, transitioning fossil-based processes to renewable feedstocks, and integrating machine learning with chemical analysis. Director of Ghent University's pilot plants for steam cracking and chemical recycling Author of over 400 publications and founder of a spin-off company Specializes in kinetic modeling, process intensification, and sustainable chemistry His work spans chemical recycling, olefin production, and advanced analytical techniques for complex hydrocarbon mixtures. Recent articles highlight AI-driven catalysis, pyrolysis of polymers, and plasma-assisted CO2 utilization. Scientific awards include: Fulbright Research Scholar He bridges academia and industry through patented technologies and collaborative pilot-scale projects.
Dr. Alison Mary is an FNRS Research Associate at the Université Libre de Bruxelles (ULB), Faculty of Psychological and Educational Sciences, Department of Neuropsychology, since October 2023. She is affiliated with the Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), which operates within the Centre de Recherche Cerveau et Cognition (CRCN) and the ULB Neurosciences Institute (UNI). Her research focuses on memory processes and their cerebral underpinnings, particularly in the context of healthy aging and resilience following acute stress. Dr. Mary completed her PhD in January 2016 at UR2nF/CRCN under Professor Philippe Peigneux. From November 2016 to October 2019, she conducted postdoctoral research at the U1077 Unit (Neuropsychology and Imaging of Human Memory – NIMH) in Caen, France, under Dr. Pierre Gagnepain, investigating neurobiological markers of resilience in survivors of the 2015 Paris terrorist attacks. Dr. Mary's research centers on understanding brain mechanisms supporting memory processes in healthy aging using functional connectivity and resting state networks. She investigates non-pharmacological stimulation strategies, particularly transcutaneous vagal nerve stimulation, to promote neuroplasticity and memory in aging populations. Her work examines how sleep architecture, meditation, and cognitive training impact memory processes in older adults, employing advanced neuroimaging techniques including MEG and EEG. Analysis of Dr. Mary's recent publications reveals a strong focus on the intersection of memory, aging, and neuroimaging. Her research increasingly incorporates transcutaneous vagal nerve stimulation to enhance memory processes, while examining how sleep architecture relates to memory consolidation. She also investigates cognitive resilience following acute stress and trauma, exploring neural mechanisms that preserve memory function despite traumatic experiences. FNRS Research Associate Fellowship (2023-present) FNRS Postdoctoral Fellowship (2019-2023) Dr. Mary actively supervises doctoral research, including Benkirane's work on sleep fragmentation and cognition, and Hamel's research on sleep characteristics in older adults. She collaborates extensively within the UR2NF research unit and with international colleagues on memory, aging, and neuroimaging projects. Her laboratory utilizes MEG, EEG, and functional MRI to investigate brain mechanisms underlying memory processes, with future work likely focusing on personalized non-pharmacological interventions for cognitive aging.
