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 .
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.
Herman Tournaye is a Physician Scientist at the Center for Reproductive Medicine of the Vrije Universiteit Brussel (VUB). With over 760 research outputs and an h-index of 86 , his work spans Reproductive Medicine , Andrology , and Stem Cell Research , focusing on fertility preservation and pregnancy complications . Education : Limited details provided, but inferred MD/PhD in Clinical Sciences. Research Trends : Recent articles emphasize AI in reproductive clinics , testicular stem cell transplantation , and pre-eclampsia biomarkers . His work bridges basic science (spermatogenesis, stem cells) with clinical applications (IVF, embryo transfer, surgical interventions). Scientific Awards : 2008 Fellowship from BSRM Central Office - Orga-med Advisory Role : Supervised 10+ theses, including studies on genetic infertility , IVF outcomes , and testicular fibrosis models . Grants & Projects : Led initiatives like SRP89 (spermatogonial stem cells) and FWOAL1141 (testicular tissue cryopreservation), funded by VUB and FWO. Media Engagement : Frequent expert commentator on fertility topics, appearing in De Morgen , Radio 1 , and Le VIF .
Prof. Jan De Beenhouwer is a faculty member at the University of Antwerp, affiliated with the Department of Physics and the imec Vision Lab. His research focuses on advanced computational imaging techniques, particularly in X-ray tomography, phase contrast imaging, and reconstruction algorithms for medical and industrial applications. His primary research interests include: Development of novel X-ray imaging methodologies like edge illumination phase contrast Advanced CT reconstruction algorithms for sparse-view and dynamic systems Integration of deep learning with tomographic reconstruction Industrial applications including defect detection and material characterization Biomedical imaging such as bone structure analysis and tissue modeling Analysis of recent publications (2024-2025) reveals strong emphasis on: Innovations in phase contrast imaging hardware and simulation tools Advanced reconstruction techniques for motion compensation and sparse data AI-powered approaches for industrial inspection and biomedical research Development of open-source tools (CAD-ASTRA) for the tomography community He leads research at imec Vision Lab, focusing on both fundamental imaging physics and practical applications. The lab collaborates extensively with industrial partners on non-destructive testing solutions.
Jan Sijbers is a Full Professor at the University of Antwerp , affiliated with the Department of Physics . He serves as Spokesperson of the imec-Vision Lab and is a co-founder of spin-offs IcoMetrix and Deltaray . His academic role includes a 10% position as Research Director at imec. Research Interests: Quantitative Magnetic Resonance Imaging (MRI), Tomographic Image Reconstruction, Medical Imaging Algorithms Editorial Roles: Senior Area Editor (IEEE Transactions on Image Processing), Associated Editor (IEEE Transactions on Computational Imaging) Teaching: Courses in Physics, Mathematics, Signal/Image Processing, and X-ray Microtomography Research Trends: His 2025 publications focus on X-ray phase contrast imaging, zebrafish models for bone disease, mesh-based CT reconstruction, and AI-driven biomedical imaging. Earlier works emphasize statistical signal processing in MRI and discrete tomography algorithms. PhD Advisees: He has supervised 68 PhD theses since 2004, with recent topics spanning edge illumination X-ray imaging, 3D knee morphology, and advanced MRI relaxometry. Laboratory Leadership: As head of imec-Vision Lab, he leads research in computational imaging, with applications in medical diagnostics and industrial X-ray systems.
Hugues Bersini is a Professor at Université Libre de Bruxelles (ULB) and Co-Director of the IRIDIA laboratory, the Artificial Intelligence research laboratory of ULB. His academic career spans over three decades, with significant contributions to the fields of artificial intelligence, complex systems, and biological networks. Bersini earned his MS degree in 1983 and his Ph.D. in engineering in 1989, both from Université Libre de Bruxelles. After working as a researcher with an EEC grant from the JRC-CEE in Ispra (1984-1987), he joined the IRIDIA laboratory at ULB, where he has remained throughout his career, eventually becoming a full professor. His research spans a diverse range of topics within artificial intelligence and complex systems. Bersini is particularly known for his work on modeling and control of complex systems, neural networks, fuzzy control, data mining, autonomous agents, and biological networks. He pioneered the exploitation of biological metaphors, especially from the immune system, for engineering and cognitive sciences applications. His research has evolved to include computational chemistry, immune engineering, cognitive sciences, bioinformatics, and object-oriented technology. In recent years, he has focused on business intelligence applications and public goods through the Brussels Institute FARI. Throughout his career, Bersini has published approximately 300 papers, demonstrating consistent productivity and evolving research interests. His early work focused on optimization algorithms and immune-inspired computing, which gradually expanded to include fuzzy and neuro control systems, biological networks, and more recently, applications to real-world problems through spin-off companies and the FARI institute. His publications show a clear trajectory from theoretical foundations to practical applications, with growing emphasis on interdisciplinary approaches that bridge computer science with biology, chemistry, and cognitive sciences. Bersini has been actively involved in the academic community, having co-organized major conferences including the Parallel Problem Solving from Nature (PPSN), European Conference on Artificial Life (ECAL), European Workshops on Reinforcement Learning (EWRL), and International Competitions on Evolutionary Optimization (ICEO). He also organized tributes to Francisco Varela and the International Conference on Artificial Immune Systems (ICARIS). As an educator, Bersini teaches artificial intelligence, object-oriented programming (C++, Java, .Net, Kotlin, UML, Django/Python), and design patterns to both university students at Solvay and Polytechnic Schools and for industry professionals. He has authored fourteen French books covering computer science fundamentals, complex systems, and the intersection of computer science with other fields. His books range from technical manuals to philosophical explorations of complex systems and emergence. Bersini has coordinated significant research projects including the FAMIMO LTR European Project on fuzzy control for multi-input multi-output processes and participated in ESPIRIT projects NEMORETS and METHODS. His work has led to practical applications through spin-off companies such as Cluepoints, Tevizz, and In Silico DB, and more recently through the Brussels Institute FARI which addresses public goods like mobility, epidemics, access to jobs and schools, and energy transition.
Andrea Sarkozy is a physician scientist at the Heart Rhythm Research unit of Brussels Clinical Sciences, affiliated with the Vrije Universiteit Brussel Faculty of Medicine and Pharmacy. Specializing in cardiovascular diseases and electrophysiology, their work focuses on advanced ablation techniques for cardiac arrhythmias, including hybrid procedures and pulsed field energy applications. Research Highlights : Brugada Syndrome diagnostics, atrial fibrillation burden analysis, speckle-tracking echocardiography, and conduction system pacing algorithms. Collaborations : Active in multicenter studies with experts like Pedro Brugada and Carlo De Asmundis. Awards : Recipient of the Paul Dudley White International Scholar Award (2023, Belgium). Recent publications (2024-2025) explore 2D imaging for hybrid ablation outcomes, novel catheter designs for arrhythmia treatment, and intraventricular synchrony algorithms. Their work bridges clinical practice with technological innovation in cardiac electrophysiology.
Prof. Alexandre Mayer is a faculty member at the University of Namur, affiliated with the Department of Physics. His research focuses on interdisciplinary topics such as genetic algorithms, quantum mechanics, and optical engineering. He leads major projects like PHOENIX (2024–2029) and Bessel-CNNs (2023–2024), advancing machine learning and materials science. He has been recognized with the Quantum Project Stipend (2000) and Fenia Berz Award (2003). His work contributes to UN Sustainable Development Goals via photovoltaic innovations and materials optimization. Education: Doctor of Sciences (1998), DEA in Physics and Material Chemistry (1996), Master in Physics (1995). Research Interests: Mayer’s expertise spans computational intelligence, high-performance computing, and nanotechnology. Recent efforts include optimizing nanopyramidal absorbers and developing 2D quaternion convolutions for 3D image processing. His work intersects physics, computer science, and engineering, with applications in cosmology and historical document analysis. Grants & Activities: Principal Investigator of €5M+ projects, including PNV+ (2016–2020) and LED (2015–2019), focusing on photovoltaics and nanostructured devices. Active in conferences like SPIE Photonics Europe (2024) and workshops on quantum technologies. Labs & Affiliations: Namur Institute of Structured Matter (NISM) and Namur Institute for Complex Systems (naXys), fostering interdisciplinary research in materials science and computational physics.
Simon Dellicour is a prominent researcher in molecular and spatial epidemiology, holding dual academic positions as an F.R.S.-FNRS Research Associate at Université libre de Bruxelles (ULB) and Visiting Professor at KU Leuven. He directs the Spatial Epidemiology Lab, where he leads research at the intersection of epidemiology, phylogenetics, and spatial analysis. His work bridges theoretical methodological developments with practical applications in disease surveillance and control. Dr. Dellicour completed his bioengineering degree at UCLouvain in 2009, followed by a PhD at ULB (2009-2013) under Patrick Mardulyn. His postdoctoral journey included positions at Oxford with Oliver Pybus (2013-2015), KU Leuven with Philippe Lemey (2015-2018), and the Spatial Epidemiology Lab with Marius Gilbert (2018-2020). In 2020, he secured the prestigious FNRS Research Associate position, a permanent academic appointment from the Belgian national research foundation. His research focuses on landscape phylogeography , developing and applying innovative methods to understand pathogen spread across geographical landscapes. His work integrates molecular epidemiology with spatial analysis to track disease transmission patterns for zoonotic and vector-borne diseases. He has made significant contributions to viral evolution research, including studies on SARS-CoV-2 variants, avian influenza, and West Nile virus. His methodological innovations include software packages like GCALIGNER, SPADS, PHYLOGEOSIM, SERAPHIM, KoT, NOSOI, PHYCOVA, SPREAD4, and Spread.gl, which have become valuable tools in molecular epidemiology. His publication record demonstrates consistent application of phylogeographic methods to understand pathogen spread. Recent work examines avian influenza dynamics across Europe, SARS-CoV-2 origins in bats, West Nile virus expansion related to climate change, and methodological improvements in viral landscape phylogeography. His research bridges computational methods with practical public health applications through interdisciplinary collaborations. Dr. Dellicour teaches Introduction to spatial and molecular epidemiology (BING-F432), Experimental design and data analysis (BING-F4002), and Seminars of data analysis (BING-F535). His role as research director involves mentorship of graduate students and postdoctoral researchers, though specific advisees aren't listed in the provided information. As director of the Spatial Epidemiology Lab, Dr. Dellicour leads a research team focused on developing spatial and molecular epidemiological methods. The lab maintains extensive international collaborations across Europe and globally, as evidenced by the multinational authorship on his publications. His work consistently integrates virology, ecology, statistics, and public health expertise to address complex questions about disease emergence and spread.
Olivier Deparis is a Researcher at the University of Namur , affiliated with the Namur Institute of Structured Matter and Namur Institute for Complex Systems . He holds a Doctor of Science degree from Université de Mons (awarded on 30 Jun 1997) and has been actively involved in interdisciplinary research since the early 2000s. Education Doctor of Science in Physical and Experimental Study of Optical Fiber Radiation Resistance by Visible-Infrared Spectrometry, Université de Mons (UMons), 1997 His research spans photonic crystals , spectroscopy , and machine learning applications in heritage science. Key projects include PHOENIX (Physics & Computational Intelligence in History) and PERGAMENUM21 (interdisciplinary parchment study). He applies computational methods to analyze historical materials and investigates light-matter interactions in natural nanostructures. Recent work focuses on bioinspired photonic structures (2024), genetic algorithm optimization of light absorbers (2024), and FDTD modelling for plasmonic systems (2024). His publications frequently address chirality , refractive index , and animal species in historical contexts. He collaborates with institutions across Belgium and internationally, supervising projects like MODPHOT (photocatalyst modelling). His datasets on beetle fluorescence (2016-2019) remain widely accessed in open-access repositories. Deparis frequently participates in heritage science symposia and is an organizer of events like the 2024 'Physicochimie du parchemin' workshop. His work was highlighted in 2024 press coverage by University of Namur on emerging technologies in parchment analysis.
Nicolas Debortoli is an evolutionary geneticist focused on molecular adaptation mechanisms in asexual organisms, particularly bdelloid rotifers and freshwater invertebrates. His research examines genetic mixing, desiccation resistance, and environmental DNA applications for biodiversity monitoring. He has contributed significantly to understanding horizontal gene transfer in asexual species and urban ecosystem impacts on microinvertebrates. Research Interests: Debortoli investigates: (1) Evolutionary dynamics of asexual reproduction in bdelloid rotifers, (2) Genetic hybridization in clam lineages, (3) Environmental DNA metabarcoding for ecological assessment, and (4) Urbanization impacts on microinvertebrate communities. His work integrates genomics, field ecology, and computational biology. Publication Trends: His recent articles (2016-2024) demonstrate a shift from fundamental rotifer genetics toward applied environmental genomics, including SARS-CoV-2 surveillance validation and machine learning applications in hematology. Over 50% of his output addresses sustainable development goals related to aquatic ecosystems and biodiversity conservation.
Aranka Steyaert is a Postdoctoral researcher at the Department of Information Technology (EA05) within the Faculty of Engineering and Architecture at Ghent University. She is affiliated with IMEC and focuses on bioinformatics and computational biology, particularly in modeling de Bruijn graphs and correcting sequencing errors using probabilistic graphical models. Her research spans genome assembly, variant calling, and metagenomics applications. Her work integrates graph theory with machine learning to address challenges in next-generation sequencing data analysis. She has published extensively on methodologies for improving node and arc multiplicity estimation in de Bruijn graphs using conditional random fields. She also contributed to the development of the UMGAP metagenomics analysis pipeline. Steyaert was supported by the Research Foundation - Flanders (FWO) as a Fellow from 2018 to 2022.
Dirk Van den Poel is a Professor of Data Analytics/Big Data at Ghent University, Belgium, specializing in statistical computing, social media analytics, and predictive modeling. He has co-founded pioneering academic programs including the first predictive analytics master’s program globally, the Master of Science in Statistical Data Analysis, and the Master of Science in Business Engineering/Data Analytics. Teaches courses: Statistical Computing, Big Data, Social Media Analytics Research focus: Analytical CRM, ensemble classification methods, big data 110+ ISI-indexed publications in journals like IEEE Transactions on Power Systems and Decision Support Systems His recent work explores topics such as rumor detection in social media, predictive maintenance using sensor data, and crisis response through service adaptation. He leverages machine learning and deep learning for applications in agriculture, healthcare, and energy sectors. Current projects involve topic modeling (BERTopic), credit scoring with interpretable models, and spatiotemporal crime prediction using mobile phone data. Dirk’s methodology integrates stream processing frameworks , reinforcement learning , and ensemble techniques .
Paul Temple is an active researcher at the Faculty of Computer Science, University of Namur, specializing in machine learning applications for software systems. His work bridges artificial intelligence, deep learning optimization, and configurable software engineering. Research focuses on energy-aware neural architecture search , variability-intensive systems , and constraint-integrated machine learning . Key contributions include developing genetic algorithms for balancing AI performance/consumption (SmartTune project) and RNN-based log analysis for software variants (VaryMinions). Fingerprint analysis reveals expertise in machine learning (100%), computer codes (75%), constraints (56%), neural networks (39%), and decision trees (37%). Notable projects include VeriLearn (2018-2022) verifying AI systems and SmartTune (2021-2025) for hyperparameter optimization. Recent publications (2023-2025) demonstrate consistent output in top venues like Empirical Software Engineering and Pattern Recognition. His h-index of 165 indicates significant scholarly impact. Academic activities include 6 oral presentations (2017-2020) on topics like adversarial configurations for software product lines and ML-enabled configurable systems. Supervised Work (2) suggests mentorship of junior researchers.
Gaetano Paparella is a Physician Scientist specializing in heart rhythm management and cardiovascular diseases at the Department of Cardiology, Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel. He maintains clinical practice at University Hospital Brussels (UZB) located at Laarbeeklaan 101, 1090 Jette, Belgium, with strong research integration into his clinical work. His primary research interests focus on cardiac electrophysiology, particularly atrial fibrillation and Brugada syndrome. His work spans diagnostic approaches, genetic testing implications, and innovative treatment strategies for cardiac arrhythmias. He has made significant contributions to understanding the relationship between genetic mutations and clinical manifestations in arrhythmia syndromes. Analysis of his 86 publications reveals consistent research focus on cardiac rhythm disorders, with particular emphasis on the application of advanced imaging techniques like speckle-tracking echocardiography and electrocardiographic imaging. His work demonstrates increasing collaboration with international research groups, particularly in genetic studies of arrhythmia syndromes. His research output shows steady productivity with 11 publications in 2021 and 2022, demonstrating ongoing active engagement in the field. The publication trend indicates growing focus on genetic aspects of arrhythmia syndromes alongside traditional electrophysiology research. Dr. Paparella maintains extensive collaborative relationships with leading European electrophysiologists including Pannone L., Sarkozy A., Brugada P., Chierchia G.B., and de Asmundis C., contributing to multicenter studies and registry-based research that has influenced clinical practice guidelines.
