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Wim GeversView profile

Professor

• Cognitive control
• Metacognition
• Working memory
• +3 more

Wim Gevers is a faculty member at the Université libre de Bruxelles (ULB) and leads the CS4S – Cognitive Control & Sleep laboratory within the CRCN research centre. His work bridges cognitive psychology, neuroscience and sleep research to understand how the brain exerts control over thoughts and actions and how sleep contributes to these processes. Research Interests Cognitive Control & Metacognition: Investigating how subjective experiences such as confidence and the "urge-to-err" guide strategic adjustments in behaviour. Working Memory & Ordinal Cognition: Examining how order information is maintained and manipulated, and how these processes relate to mathematical competence. Sleep, Memory & Decision Making: Exploring how sleep-dependent consolidation influences motor learning and decision strategies. Across his 2022–2025 publications a clear trend emerges: a focus on metacognitive monitoring —how humans evaluate their own cognitive states—and the role of emotional and temporal context in shaping those evaluations. Studies range from reaction-time introspection and confidence judgements in perceptual tasks to the impact of aging and depression on metacognitive accuracy. Doctoral Supervision & Mentoring Whitney Stee (PhD 2024) – Sleep-dependent structural brain reorganization & motor learning Gaia Corlazzoli (PhD 2024) – Subjective experience in decision-making Myrtille Dewulf (PhD 2023) – Ordinal coding mechanisms in working memory Rebeca Sifuentes-Ortega (PhD 2023) – REM sleep and memory reactivation All dissertations were defended at ULB, Faculté des Sciences psychologiques et de l’éducation, with Wim Gevers formally listed as Promotor . Laboratory & Collaborative Networks As head of CS4S, Gevers coordinates a multidisciplinary team that combines behavioural experimentation, EEG/MEG, computational modelling and sleep polysomnography. The lab is embedded in the larger CRCN ecosystem, fostering collaborations with groups such as CO3 (consciousness), LCLD (language & deafness), and UR2NF (neurofunctional imaging).

Karoline FaustView profile

Associate Professor

• Microbial community dynamics
• Microbial systems biology
• Bioinformatics
• +6 more

Karoline Faust is an Associate Professor at KU Leuven, affiliated with the Laboratory of Molecular Bacteriology (Rega Institute) and the Faculty of Medicine . She contributes to the iSi Health and Leuven One Health institutes, and serves on senior academic councils. Her research spans microbial systems biology, focusing on community dynamics and network analysis. Education: PhD in bioinformatics (2010, KU Leuven) Affiliations: KU Leuven, ISME Journal editorial board, Belgian Society for Microbiology Her research investigates microbial community dynamics , systems biology approaches to microbiomes, and bioinformatics tool development . She specializes in modeling human gut microbiota , synthetic microbial communities , and environmental microbiomes (e.g., microplastic impacts on Daphnia microbiomes). Her work integrates metabolic modeling , network analysis , and experimental systems to understand microbial interactions. Recent publications highlight her contributions to microbial network inference , 16S rRNA sequencing protocols , microfluidics , and ecological modeling of microbiomes. She develops tools like manta , miaSim , and CoNet to analyze community structures. Teaching: Karoline co-teaches courses in microbiology, bioinformatics, and network analysis at KU Leuven, and has contributed to international workshops on microbial network inference. Scientific Engagement: She serves as Senior Editor at ISME Journal and Secretary of the Belgian Society for Microbiology .

Tom DhaeneView profile

Professor

• Data-Efficient Machine Learning
• Surrogate Modeling
• Gaussian Processes
• +3 more

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.

• Biomechanics
• Human Movement Science
• Gait Analysis
• +10 more

Friedl De Groote is a Senior Lecturer at KU Leuven's Faculty of Human Movement and Rehabilitation Sciences, Department of Human Movement Sciences, specializing in the biomechanics of human movement. She leads the Biomechanics of Human Movement Research Group and is a member of the iSi Health - KU Leuven Institute for Physics-based Modeling for In Silico Health. Her research focuses on understanding neuromusculoskeletal control of human movement, particularly through computational modeling approaches. She investigates gait disorders in children with cerebral palsy and Duchenne muscular dystrophy, examining how muscle impairments, contractures, and neural control mechanisms contribute to altered movement patterns. Her work combines experimental biomechanics with predictive computer simulations to uncover the underlying mechanisms of movement disorders and develop new rehabilitation approaches. She also studies fundamental aspects of human locomotion, balance control, and energy expenditure during walking. Her recent publications demonstrate a strong emphasis on predictive simulations to understand the relationship between neuromusculoskeletal impairments and movement pathology. Her research spans multiple domains including cerebral palsy, Duchenne muscular dystrophy, gait analysis, balance control, and musculoskeletal modeling. She frequently collaborates with clinical researchers to bridge the gap between computational models and clinical applications. Dr. De Groote is actively involved in various academic councils including the Faculty Council FaBeR, POC Rehabilitation Sciences and Physiotherapy, POC Physical Education and Movement Sciences, and multiple departmental councils within Human Movement Sciences. Her ORCID identifier is 0000-0002-4255-8673 . She currently leads or co-leads numerous research projects funded through KU Leuven and external grants, with a focus on understanding walking control mechanisms, energy expenditure during locomotion, and developing computational models to inform rehabilitation strategies for children with movement disorders. Her research portfolio demonstrates a commitment to translating biomechanical insights into clinically relevant applications.

• Structural Equation Modeling
• Psychometrics
• Statistics
• +5 more

Yves Rosseel is a Professor at Ghent University (UGent) specializing in Structural Equation Modeling (SEM) , Psychometrics , and Statistical Methodology . With over 15 recent publications (2024-2025), he focuses on small-sample SEM solutions, factor score regression, measurement error, and Bayesian extensions. His work bridges Statistics with applications in Psychology , Education , and Neuroimaging . Research Trends Developed Mixture Multigroup SEM for cross-group comparisons Proposed Information-Theoretic Hypergraphs in psychometrics Advanced Two-Stage Estimation for round-robin data Created blavaan R package for Bayesian SEM Investigated Measurement Error in hypothesis testing Scientific Contributions Published 84 Social Sciences papers, 37 Statistics works, and 11 Neuroimaging studies Promoted 8 PhDs including Sara Dhaene and Julie De Jonckere Co-authored 12+ works with Marijke Welvaert and 10+ with Stijn Vanheule

• Photovoltaics
• Solar Energy Systems
• Silicon Solar Cells
• +5 more

Jef Poortmans is a Visiting Professor at KU Leuven, Belgium, specializing in photovoltaic technologies and solar energy systems. His research spans multiple applications including conventional solar installations, agrivoltaics, vehicle-integrated photovoltaics, and tandem solar cell configurations. Affiliated with the Electa department at KU Leuven, he maintains an active research profile with numerous publications extending into 2025. His research interests focus on advancing photovoltaic technology across multiple dimensions. Poortmans investigates thermal modeling to improve energy yield predictions, develops lightweight PV modules for vehicle integration, explores agrivoltaic systems that combine agriculture with solar energy production, and works on next-generation perovskite and tandem solar cell technologies. His work often addresses practical implementation challenges including reliability under various environmental conditions, mechanical integration requirements, and performance optimization for specific applications. Analysis of his recent publications reveals a strong emphasis on practical implementation challenges of photovoltaic systems. His work spans fundamental materials science (particularly for perovskite and thin-film technologies), system integration challenges (especially for vehicle applications), and innovative approaches to land use optimization through agrivoltaics. A recurring theme is addressing reliability and performance issues under real-world operating conditions rather than ideal laboratory settings. Poortmans frequently collaborates with researchers across multiple institutions, indicating strong industry and academic connections within the photovoltaics community. His work appears in high-impact journals including Solar Energy Materials and Solar Cells, Scientific Reports, and Advanced Functional Materials, demonstrating recognition within the field. While specific grant information isn't detailed in the provided materials, his extensive publication record across diverse photovoltaic applications suggests successful funding acquisition for multiple research projects. His involvement in PhD theses supervision indicates active mentorship of next-generation researchers in the photovoltaics field. His research group appears to focus on bridging fundamental photovoltaic science with practical engineering applications, particularly addressing the reliability and integration challenges that prevent wider adoption of solar technologies in non-traditional applications like vehicles and agricultural settings.

• Survival Analysis
• Nonparametric Regression
• Semiparametric Regression
• +4 more

Ingrid Van Keilegom is a Full Professor at the Faculty of Economics and Business (FEB) at KU Leuven. She is a member of the LISS – KU Leuven Institute of Sports Science and serves as a program director for the POC Master in Statistics. Senior academic staff member of FEB Council and Campus Council Observer in Faculty of Science Council Member of LStat General Assembly Her research focuses on Survival Analysis and Nonparametric Regression , with expertise in: Dependent Censoring Cure Models Measurement Error Correction Quantile Regression Multivariate Statistical Inference Causal Surrogacy Metrics Recent publications emphasize copula-based methods, quantile regression for censored data, and applications to biomedical and economic forecasting. Key projects include instrumental variable approaches for endogeneity in cure models, bankruptcy prediction via machine learning, and measurement error modeling in multivariate settings. Notable affiliations: Centre for Efficiency and Productivity Analysis Collaborations in pharmaceutical statistics and actuarial science

• Signal processing
• Fault detection and diagnosis
• Rotordynamics
• +7 more

Konstantinos Gryllias is a Professor in the Department of Mechanical Engineering at KU Leuven's Faculty of Engineering Sciences. He leads research in the Mechatronic System Dynamics (LMSD) unit at the Arenberg campus. His academic affiliations extend across multiple KU Leuven institutes including Leuven.AI, Leuven.AM (Additive Manufacturing), and the Gravitation Institute. He serves on important governance bodies as a member of the Faculty Council of Engineering Sciences, Faculty Doctoral Committee of Engineering Sciences, and Departmental Council of Mechanical Engineering. Dr. Gryllias specializes in signal processing, fault detection and diagnosis of rotating machinery, condition monitoring, and machine learning applications in structural health monitoring. His research spans linear and nonlinear vibrations, anomaly detection, rotordynamics, and pattern recognition. His work bridges theoretical signal processing with practical engineering applications in wind turbines, marine propulsion systems, and industrial machinery. His recent publications demonstrate strong focus on deep learning approaches for wind turbine anomaly detection, bearing diagnostics, stern bearing lubrication optimization, and structural health monitoring using advanced signal processing techniques. The research shows increasing integration of explainable AI methods with traditional vibration analysis. Dr. Gryllias teaches advanced courses including Monitoring & Prognostics, Structural Dynamics, Smart Sensing Technologies, and Applied AI perspectives. His teaching portfolio reflects the interdisciplinary nature of his research, connecting mechanical engineering fundamentals with cutting-edge AI methodologies. He currently leads multiple research projects through 2025-2029, primarily as Promotor, focusing on fault detection in gears using fiber optic sensors, multi-sensor monitoring of drivelines, physics-inspired machine learning for condition monitoring, and digital twin applications for wind turbine efficiency improvement.

Jef VandemeulebrouckeView profile

Researcher

• Medical Imaging
• Computer Vision
• Artificial Intelligence
• +3 more

Jef Vandemeulebroucke is a researcher at the Department of Electronics and Informatics , Vrije Universiteit Brussel (VUB) , specializing in medical imaging, computer vision, and augmented reality applications in healthcare. His work bridges artificial intelligence with radiology and biomechanics , focusing on automated segmentation, predictive modeling, and real-time surgical navigation systems. Research interests include: Medical image analysis for disease prognosis (e.g., COVID-19 severity , neurosurgical drains ) Development of MedShapeNet , a 3D medical shape dataset for computer vision Augmented reality systems in orthopedic and neurosurgical interventions AI-driven fluorescence endoscopy and dynamic CT for joint kinematics Key trends in his 140+ publications emphasize deep learning , image registration , and 4D-CT applications . Supervised theses include brain age prediction and chest radiography automation. Active in 38 projects (e.g., AI-NIMO , TumorScope ), he collaborates with institutions like the Universitair Ziekenhuis Brussel (UZB) and FWO (Fund for Scientific Research-Flanders).

• Coastal Engineering
• Numerical Modeling
• Nature-Based Solutions
• +4 more

Tomohiro Suzuki is an Associate Professor at KU Leuven and Ghent University (UGent) , affiliated with the Department of Civil Engineering under the Faculty of Engineering Science (KU Leuven) and Faculty of Engineering and Architecture (UGent) . With 25 years of expertise in coastal engineering, he specializes in wave overtopping , wave-structure interactions , and Nature-Based Solutions for coastal management. Key research areas: Numerical Modeling (DualSPHysics, SWASH), Wave-Current-Vegetation Interaction , Coastal Flood Resilience Teaching roles: Project Hydraulic Engineering 3 , Hydraulic Structures , Hydrodynamics His recent projects include: INTEGRATOR (2024–2026): Integrated coastal hydrodynamics modeling Numerical Coastal Basin (2021–2025): Virtual testing for floating structures Wind Generation System (2025–2028): Fan Array Wind Tunnel for Coastal & Ocean Basin Publications focus on 3D wave-vegetation dynamics , SPH-based coastal simulations , and shallow foreshore resilience against extreme waves. No scientific awards are explicitly mentioned.

Wout WeijtjensView profile

Research Fellow

• Structural Health Monitoring
• Offshore Wind Turbines
• Fatigue Analysis
• +2 more

Wout Weijtjens is a Research Fellow at Vrije Universiteit Brussel, affiliated with the Acoustics & Vibration Research Group in Applied Mechanics. His research focuses on structural health monitoring (SHM) of offshore wind turbines, fatigue analysis, and vibration-based damage detection using advanced signal processing and machine learning techniques. Current projects include FIRMEST (fatigue assessment of offshore wind turbine substructures) and FOOS (Forced Oscillations in turbines). His research interests span: Operational modal analysis for offshore structures Machine learning applications in SHM Fatigue life prediction under environmental variability Sensor networks for infrastructure monitoring Wind turbine dynamics under harsh conditions Recent publications demonstrate a consistent focus on developing predictive maintenance frameworks through multivariate sensor data analysis, uncertainty quantification in SHM systems, and validation of computational models against full-scale field measurements. Article trends emphasize machine learning integration with physical models for improved fatigue life assessment. Awards and recognitions include: Best Paper Award (2nd place, 2022) Poster Award (2017) Solvay Award (2015) As principal investigator on multiple grants including VLADBC7 and VLADBC9 projects, he supervises PhD candidates in vibration-based SHM and leads experimental validation at OWI-Lab's Large Climate Chamber. His team develops IoT monitoring solutions for civil infrastructure through the SMART TOWERS initiative.

Liane GaboraView profile

Professor

• Creativity
• Cultural Evolution
• Cognitive Science
• +5 more

Liane Gabora is a Full Professor in the Department of Psychology at the University of British Columbia's Okanagan Campus, affiliated with the Irving K. Barber Faculty of Arts and Social Sciences. She holds additional research affiliations with the Australian National University's School of Music, University of Waterloo's Institute for Complexity & Innovation, and Free University of Brussels' Centre Leo Apostel for Interdisciplinary Studies. Her educational background includes a BSc from the University of Western Ontario, PhD from the Free University of Brussels, and postdoctoral positions at UC Berkeley and the Free University of Brussels. Gabora's research program explores creativity, cultural evolution, and cognitive transitions through interdisciplinary approaches. Her work examines: How concepts combine and adapt to new contexts The origins of modern cognition and human creativity Computational models of cultural evolution Quantum formalisms for concept interactions Self-Other Reorganization (SOR) theory of cultural evolution Honing theory of creativity integrating complex systems and memory Her publications demonstrate strong cross-disciplinary integration spanning psychology, physics, anthropology, and computer science. Major research awards include the 2011 Berlyne Award from the American Psychological Association for outstanding research by a junior scholar. She has secured over $1 million in funding from NSERC, SSHRC, and private donors. Gabora supervises graduate students in Psychological Science and Digital Humanities programs and leads research on cognitive transitions underlying cultural evolution. Her laboratory focuses on mathematical and computational modeling of creativity mechanisms, with ongoing projects exploring AI creativity, quantum models of cognition, and the evolution of behavioral modernity through autocatalytic network frameworks.

• Riemannian Optimization
• Matrix Manifolds
• Low-Rank Matrix Completion
• +4 more

Pierre-Antoine Absil is a Full Professor at the Louvain Polytechnic School (EPL) , part of the Université catholique de Louvain (UCLouvain) , affiliated with the Mathematical Engineering Center (INMA) and the Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM) . His research spans Riemannian optimization , matrix manifolds , and low-rank approximation with applications in astronomical imaging , signal processing , and environmental data imputation . His work emphasizes Riemannian optimization algorithms matrix and tensor completion geometric data analysis applications in astrophysics and bioinformatics Recent publications focus on Stiefel and Grassmann manifolds , variable projection methods , and exoplanet detection via alternating minimization . While no explicit scientific awards are listed, his collaborations with institutions like IEEE and Springer highlight his impact in computational mathematics and engineering. He has supervised researchers such as Simon Vary , Guillaume Olikier , and Valentin Christiaens through projects in direct imaging , economic dispatch , and graph-based data processing . His laboratory, INMA , drives methodological advances in manifold-valued data analysis and nonlinear optimization .

• Psychopathology
• Eating Disorders
• Non-suicidal Self-injury
• +5 more

Laurence Claes is a Professor and Head of Clinical Psychology at KU Leuven's Faculty of Psychology and Educational Sciences. His academic career spans multiple research domains with a focus on psychopathology, particularly eating disorders and non-suicidal self-injury (NSSI), examined through the lens of identity formation processes. He maintains strong affiliations with the LC&Y - KU Leuven Institute for Child and Youth and serves on several important committees including the Faculty Doctoral Committee for Psychology and Educational Sciences as ombudswoman for KU Leuven staff. Professor Claes' research primarily investigates the complex relationship between identity development and various forms of psychopathology, with special attention to adolescents and emerging adults. His work consistently demonstrates how identity processes serve as both risk and protective factors across multiple clinical presentations. He employs diverse methodologies including longitudinal studies, ecological momentary assessment, and both community and clinical samples to examine these relationships. Analysis of his recent publications reveals consistent thematic patterns across his work. His research shows strong connections between identity functioning and eating disorders, non-suicidal self-injury, body image concerns, and personality pathology. He frequently examines how identity processes mediate relationships between other psychological constructs and clinical outcomes. His work spans multiple contexts including cancer survivorship, athletic performance, and digital environments. Professor Claes actively supervises numerous doctoral candidates and collaborates extensively with researchers both within KU Leuven (particularly with Koen Luyckx) and internationally. His work appears in high-impact journals across psychology, psychiatry, and related fields, demonstrating the transdisciplinary nature of his research. His teaching responsibilities include courses on clinical diagnostics for adults and the elderly (P0V88A, P0X60A), psychological interventions (P0W42A, P0N41B), single-case research (P0X93A), and clinical psychology practicum (P0Y05A, P0W57A, P0Y08A), indicating his commitment to both research and clinical training.

Els GoetghebeurView profile

Professor

• Biostatistics
• Causal Inference
• Quality of Care
• +2 more

Els Goetghebeur is a Full Professor at Ghent University's Department of Applied Mathematics, Computer Science and Statistics. She chairs the UGent Expert Center for Statistics and serves as Chief-Editor of Statistics in Medicine , while leading the causal inference group within the STRATOS initiative. Her research emphasizes causal inference, survival analysis, and quality of care assessment in biomedical contexts. University: Ghent University Department: Applied Mathematics, Computer Science and Statistics Leadership Roles: Chair of UGent Expert Center for Statistics, Chief-Editor of Statistics in Medicine, Lead of STRATOS Causal Inference Group Her work spans methodological developments in causal inference and survival analysis, applied to biomedical challenges like cancer outcomes, transplant medicine, and tuberculosis diagnostics. Recent publications focus on propensity score methods, latent class analysis, and patient-reported outcome modeling across diverse clinical trials. Key trends in her research include: Improving causal inference techniques in observational studies Advancing survival analysis methods for complex clinical data Standardizing statistical practices in biomedical research through editorial leadership Developing frameworks for handling missing data in patient-reported outcomes Contributing to multicenter clinical trial designs for prostate cancer and solid tumors