جستجوی استاد راهنمای دانشگاهی

• Antimicrobial Development
• Microbial Community Behavior
• Biofilm Research
• +۵ مورد دیگر

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.

• Numerical Analysis
• Applied Mathematics
• Computational Fluid Dynamics
• +۵ مورد دیگر

Stefan Vandewalle is a full professor at the Department of Computer Science, Faculty of Engineering Sciences, KU Leuven. His research focuses on numerical analysis, applied mathematics, and computational methods for stochastic differential equations, wind energy modeling, and uncertainty quantification. Department Chair, KU Leuven Member, Subdivision Numerical Analysis and Applied Mathematics Member, iSi Health Institute Observer, Faculty Council of Sciences Chair, Department Council for Computer Science His recent work explores multiscale modeling, Monte Carlo methods, and data assimilation techniques. Projects include micro-macro Parareal algorithms, wind turbine aeroelasticity, and turbulent flow reconstruction for wind farms. He supervises PhD candidates and collaborates on interdisciplinary studies involving structural mechanics and renewable energy systems. Publications highlight advancements in parallel-in-time methods, stochastic optimization for tokamak reactors, and DNS-based control of turbulent flows. Key keywords: Multiscale numerical methods Uncertainty quantification Wind energy simulation Monte Carlo algorithms PDE-constrained optimization Stochastic differential equations He contributes to academic governance as a member of extended faculty boards and evaluation committees.

• Mechanobiology
• Biomechanics
• Microvascular mechanics
• +۵ مورد دیگر

Hans Van Oosterwyck serves as a full Professor in the Department of Mechanical Engineering at KU Leuven's Faculty of Engineering Sciences. He leads the Prometheus-Mechanobiology subdivision and actively contributes to the iSi Health and LIMNI research institutes, driving interdisciplinary work at the engineering-biology interface. His research centers on cellular mechanobiology in vascular and musculoskeletal pathologies, with pioneering work in traction force microscopy and organ-on-chip systems . Key focus areas include cerebral cavernous malformations (CCM) and osteoarthritis, where he investigates how cellular forces and mechanosensitive channels drive disease progression through microfluidic models and computational biomechanics . Analysis of his 2023-2025 publications reveals a dominant trend toward 3D force measurement techniques in disease modeling, particularly using degradable hydrogels for chondrocyte studies and vessel-on-chip platforms for CCM. Over 60% of recent work targets CCM pathomechanics, emphasizing Piezo/TRPV channels and cellular force dynamics. Prof. Van Oosterwyck directs multiple FWO-funded projects including "Cerebrale caverneuze misvormingen op een chip" (2023-2026) and "De relatie tussen osteoarthritis en krachten" (2023-2027). His team develops advanced tools like the Confocal BioAFM nano-opto-mechanical platform for multiscale biological analysis. He heads the Prometheus-Mechanobiology subdivision within KU Leuven's Biomechanics unit, leveraging collaborations through iSi Health for physics-based in silico health modeling and LIMNI for micro-nano technology integration. This ecosystem enables translational research from cellular mechanics to clinical applications.

Daniele Marinazzoمشاهده پروفایل

استاد

• Computational Neuroscience
• Complex Systems
• Neurophysics
• +۴ مورد دیگر

Daniele Marinazzo is a Full Professor in the Department of Data Analysis at Ghent University (Belgium), with a background in statistical physics and a focus on computational neuroscience and complex systems. He serves as Deputy Editor at PLOS Computational Biology , Co-Editor-in-Chief at Neurons, Behavior, Data Analysis, and Theory , and academic editor at Network Neuroscience and Imaging Neuroscience. His work spans theoretical physics, neuroscience methodology, and experimental neurophysiology. Academic Affiliation: Ghent University (Belgium) Editorial Roles: 3+ journals Research Initiatives: EBRAINS representative Research Interests combine computational neuroscience, complexity science, and network analysis. He investigates higher-order interactions in brain networks, synergistic information processing, and methodological advancements in neuroimaging. Recent work includes MEG/EEG analysis, gene expression modeling, and developing open-source tools like SPM-Python. Scientific Contributions include 15+ recent publications on topics ranging from individual brain fingerprinting to multisensory integration models. His work appears in venues like Nature Communications , Physics of Life Reviews , and Entropy , with methodological innovations in hidden factor localization and network synchronization analysis. Current projects include PhD/postdoc recruitment for fast-sampled fMRI analysis and organizing the Erice workshop Higher-Order Interactions: Mechanisms, Behaviors, and Networks (August 2025).

Pierre Beaujeanمشاهده پروفایل

پژوهشگر ارشد

• Quantum Chemistry
• Nonlinear Optics
• Computational Chemistry
• +۴ مورد دیگر

Pierre Beaujean is a postdoctoral researcher at the University of Namur , Belgium, affiliated with the ECOBAT (EOS) project and the laboratory of Professor Benoît Champagne. His work bridges quantum chemistry and computational chemistry , focusing on nonlinear optical materials and electrochemical interfaces for battery research. His research spans theoretical methods like Density Functional Theory and Coupled Cluster to evaluate hyperpolarizabilities, solvation effects, and molecular switches. Recent projects explore calcium anodes, 3D metal-organic frameworks, and multi-state optical systems, contributing to sustainable energy solutions. Beaujean’s publications analyze two-photon absorption , XPS spectra , and proton-electron conductivity . He is also a science communicator at Zeste de Savoir and manages the university’s chemistry department social media.

Charlotte BOUQUIAUXمشاهده پروفایل

پژوهشگر

• Theoretical Chemistry
• Nonlinear Optics
• Biophysics
• +۴ مورد دیگر

Charlotte BOUQUIAUX is an active researcher specializing in theoretical chemistry and biophysics, with expertise in nonlinear optical properties of lipid membranes and chromophores. She recently completed her Doctor of Sciences degree in October 2023 under the supervision of B. Champagne, having previously earned a Master in Chemistry Research in 2019. Her research focuses on the intersection of theoretical chemistry, biophysics, and computational science, particularly investigating how molecular structures affect optical properties in complex biological environments. She employs multiscale theoretical approaches combining quantum mechanics and molecular dynamics to study lipid membranes, chromophores, and their nonlinear optical responses. Bouquiaux's publication record shows consistent productivity with six peer-reviewed articles between 2020-2024, demonstrating evolving sophistication from foundational studies to increasingly complex membrane systems. Her work bridges chemistry, physics, and biology, with applications in membrane biophysics and optical probe development. She has been actively engaged in the academic community through conference presentations, including invited talks at the NISM Annual Meeting 2022 and other specialized symposia. Notably, she co-organized the 'Women and Girls in Science' event in April 2022, demonstrating commitment to diversity in STEM fields. Bouquiaux served as Principal Investigator for the research project 'Development and application of a multiscale theoretical chemistry method for investigating the second harmonic generation of lipid membranes' from October 2019 to December 2021, indicating early recognition of her research capabilities while still completing her doctoral studies.

Joris Degrooteمشاهده پروفایل

استاد

• Fluid-Structure Interaction
• Computational Fluid Dynamics
• Nonlinear Dynamical Systems
• +۵ مورد دیگر

Joris Degroote is a Full Professor at Ghent University's Faculty of Engineering and Architecture, where he leads research in computational mechanics and multiphysics simulation. He obtained his MSc (2006) and PhD (2010) in Electromechanical Engineering from Ghent University, with research stays at Massachusetts Institute of Technology (2007–2008) and Technische Universität München (2011). His research focuses on fluid-structure interaction (FSI) , computational fluid dynamics, surrogate modeling, and machine learning applications in engineering systems. Key areas include optimization under uncertainty, reduced-order modeling, and development of efficient numerical coupling techniques for complex multiphysics problems such as renewable energy systems, biomedical flows, and industrial processes. Recent publications demonstrate strong emphasis on high-fidelity simulations for aerospace applications (airborne wind energy, drone aerodynamics), biomedical engineering (aortic hemodynamics, cerebrospinal fluid dynamics), and advanced manufacturing (textile mechanics, tribology). Awards & Recognition: Post-doctoral Fellowship, Research Foundation Flanders (FWO) Affiliations: Core lab member of Flanders Make; serves on scientific and editorial boards of multiple journals and conferences. Leads the Sustainable Thermo-Fluid Energy Systems (STFES) and EEDT-MP research units.

Alexandre Mauroyمشاهده پروفایل

استادیار

• Dynamical Systems
• Control Theory
• Operator Theory
• +۳ مورد دیگر

Alexandre Mauroy is an Assistant Professor at the University of Namur (UNamur) in the Department of Mathematics and the naXys center. He holds a Ph.D. in Applied Mathematics (2011) and a Master's in Aerospace Engineering (2007) from the University of Liège. His research focuses on dynamical systems, control theory, operator theory, and networks, with applications to nonlinear systems and mathematical biology. Key awards include the BELSPO return grant (2013), BAEF fellowship (2011), and FNRS fellowship (2007). Mauroy's work emphasizes the Koopman operator framework for analyzing nonlinear systems, including global stability, spectral identification, and data-driven methods. He leads projects like KOMUDYS (Koopman operator techniques for multiscale systems) and KORNET (nonlinear network identification). His research spans topics such as regions of attraction estimation, switched systems, and urban traffic management through the AUTOMATic project. Education: Ph.D. in Applied Mathematics, University of Liège (2011) M.Sc. in Aerospace Engineering, University of Liège (2007) Key Projects: KOMUDYS: Koopman operator methods for multiscale systems AUTOMATic: Autonomous urban traffic management KORNET: Nonlinear network identification His contributions include advancing the Koopman operator's theoretical foundations and practical applications, with over 49 research outputs since 2008. He actively collaborates internationally and contributes to conferences, workshops, and editorial activities in systems and control theory.

Martin Diehlمشاهده پروفایل

مدرس

• Computational Materials Science
• Crystal Plasticity
• Multi-physics Modeling
• +۳ مورد دیگر

Martin Diehl is a lecturer at the Faculty of Engineering Sciences of KU Leuven , Belgium. He is affiliated with the Department of Materials Engineering and the Department of Computer Science . His research focuses on computational materials science, particularly crystal plasticity simulations and multiscale modeling of metallic microstructures.

Sven Roggeمشاهده پروفایل

دانشیار

• Strain engineering
• Computational materials science
• Metal-organic frameworks
• +۵ مورد دیگر

Sven Rogge is an Associate Professor at the Faculty of Engineering and Architecture at Ghent University, where he leads computational research on nanostructured materials. His work bridges theoretical modeling and practical applications in materials science, with particular focus on strain engineering and mechanical properties of framework materials. Rogge earned his Master of Science in Engineering Physics in 2014, followed by a Ph.D. in 2018 under supervision of Prof. Veronique Van Speybroeck and Prof. Toon Verstraelen. His doctoral research developed simulation algorithms for interrogating mechanical behavior of metal-organic frameworks under temperature and pressure. He subsequently held two postdoctoral fellowships from the Research Foundation Flanders before becoming an associate professor in 2023. Rogge's research centers on computational materials science with emphasis on strain engineering of nanostructured materials. His work spans molecular dynamics simulations, multiscale modeling, and machine learning approaches to understand and design materials with tailored mechanical properties. Key research themes include solid-state phase transformations, flexibility mechanisms in porous frameworks, and computational design of materials for energy applications. His group has pioneered techniques such as the micromechanical model (MicMec) for investigating cooperative phenomena in reticular materials. His publication record shows a strong trend toward integrating computational methods with experimental validation across diverse materials systems. Recent work demonstrates growing emphasis on machine learning applications in materials discovery, particularly for metal-organic and covalent organic frameworks. His research bridges fundamental understanding of material behavior with practical applications in energy storage, gas separation, and perovskite stability. ERC Starting Grant (2023) for establishing strain engineering as an in silico technique Member of the Young Academy of the Royal Flemish Academy of Belgium for Science and the Arts (2023) Member of the Federal Board of Research Policy (FRWB) (2023) Two postdoctoral fellowships from the Research Foundation Flanders Ph.D. fellowship from the Research Foundation Flanders Rogge co-teaches Bachelor and Master courses in Engineering Physics, including Quantum Mechanics I and Modelling and Engineering of Nanoscale Materials. His research group maintains active collaborations across European institutions and contributes to several large-scale projects focused on computational materials design. The group has developed several computational tools and databases, including MicMec for mechanical modeling and ReDD-COFFEE for covalent organic framework screening, which have gained international recognition in the computational materials community.

• Modelling dynamic and ultrasonic response of complex structures
• Design optimisation of multifunctional structures and metamaterials
• Structural health monitoring (SHM)
• +۲ مورد دیگر

Dimitrios Chronopoulos is an Associate Professor in the Department of Mechanical Engineering at KU Leuven , Faculty of Engineering Technology. His research focuses on structural health monitoring, design optimization of composite and metamaterial structures, and wave propagation analysis for damage prognosis. Unit: Mecha(tro)nic System Dynamics (LMSD), Ghent and Aalst Campuses Research Affiliations: Leuven Centre for Affordable Sustainable Technology, LIM - KU Leuven Institute for Mobility His work integrates physics-informed machine learning and computational modeling to address challenges in predictive maintenance of smart composite systems, including aircraft and wind turbine components. Recent projects emphasize digital twins, Bayesian frameworks, and ultrasonic sensor networks for real-time damage assessment. Publications highlight trends in deep learning for SHM , topological phononic crystals , and multi-scale damage detection using hybrid models. He actively supervises students in advanced ultrasonic monitoring and predictive analytics.

Eugen Pircalabeluمشاهده پروفایل

مدرس

• High-dimensional statistics
• Probabilistic graphical models
• Social network models
• +۶ مورد دیگر

Eugen Pircalabelu is a Lecturer at UCLouvain (Université catholique de Louvain) working at the Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) within LIDAM at the Faculty of Science. Prior to his current position, he held a Visiting Professor position at Ghent University and a Postdoctoral position at KU Leuven. Dr. Pircalabelu's research focuses on high-dimensional statistics, with particular emphasis on probabilistic graphical models, social network analysis, copula models, and information criteria. His work bridges theoretical statistics with practical applications in fields such as neuroscience (fMRI data analysis) and epidemiology (COVID-19 modeling). His recent publications reveal a strong trend toward distributed and federated learning approaches for high-dimensional graphical models, with applications spanning from financial time series to brain connectivity networks. His methodological contributions include innovations in model selection criteria, sparse estimation techniques, and time-varying network models that have advanced the field of high-dimensional statistical inference. Dr. Pircalabelu actively supervises multiple PhD students including Mengxue Li, Lise Léonard, and Lara Wautier, and has recently guided Ensiyeh Nezakati and Alexandre Jacquemain to completion of their doctoral studies. He teaches courses in nonparametric statistics, numerical methods for statistics, and statistical learning. He serves the statistical community through organizing regular Statistical/Econometrics seminars at ISBA and contributing to the RShiny@UCLouvain platform for open educational resources. Notably, during the COVID-19 pandemic, he developed a SHINY app for predicting hospitalizations and ICU admissions in Belgium.

Florian Fepponمشاهده پروفایل

استادیار

• Topology Optimization
• Optimal Design
• Homogenization
• +۶ مورد دیگر

Florian Feppon is an Assistant Professor in the NUMA division of the Department of Computer Science at KU Leuven. His research spans topology optimization, optimal design, homogenization, multiscale modeling, uncertainty quantification, data assimilation, and asymptotic analysis of partial differential equations, with applications in 3D printing, heat exchangers, photonics, and microfluidic devices. He completed his PhD in 2019 at École polytechnique under Grégoire Allaire and Charles Dapogny, funded by Safran, and a Master’s thesis in 2016 at MIT with Pierre Lermusiaux. From 2020 to 2022, he was a Hermann-Weyl postdoctoral instructor at ETH Zürich. His research interests include developing algorithms for nonlinear constrained optimization, such as the Null Space Optimizer , and analyzing subwavelength resonances in acoustic metamaterials, fluid-structure interactions, and homogenization of porous media. Scientific awards : Prix Paul Caseau 2019 (EDF, Institut de France), ECCOMAS PhD award 2019, and SMAI-GAMNI thesis award 2021. Grants : FWO Junior Research Project (2024-2028) on topology optimization of large-scale systems under uncertainty. Students : Javier Bevia-Ripoll and Dries Toebat, working on topology optimization with local and global constraints. Software : Lead developer of the open-source Null Space Optimizer for constrained optimization.

• Solid-State Batteries
• Electrochemistry
• Materials Science
• +۵ مورد دیگر

Mohamed El Marini is an active Assistant Professor in the Department of Materials and Chemistry at the Faculty of Engineering, Vrije Universiteit Brussel (VUB). His research focuses on advanced electrochemical systems and energy storage materials, particularly solid-state batteries and electrochemical interfaces. His primary research interests include: Solid electrolytes and electrode interfaces for all-solid-state batteries In situ electrochemical characterization using TEM (EC-TEM) Multiscale modeling of electrochemical processes Electrochemical nucleation and growth mechanisms Energy storage materials development His recent publications demonstrate a strong emphasis on combining experimental techniques like electron microscopy with computational modeling to understand fundamental processes in battery materials. Key trends include the investigation of solid-electrolyte interfaces, electrochemical-radiolysis coupling, and high-throughput electrochemical characterization methods. No scientific awards were explicitly mentioned in the source materials. El Marini actively participates in doctoral scholarship programs and collaborates extensively within VUB's research ecosystem. His work involves significant interdisciplinary collaboration across materials science, chemistry, and engineering disciplines, particularly through VUB's research groups focused on sustainable materials engineering. While specific grant details aren't provided, his research output suggests involvement in projects related to next-generation battery technologies and electrochemical characterization methods. His research appears to be conducted within VUB's advanced materials characterization facilities, with particular emphasis on in situ electrochemical transmission electron microscopy (EC-TEM) capabilities and multiscale modeling infrastructure for studying solid-state battery interfaces.

• Applied Mathematics
• Computational Science
• Plasma Physics
• +۷ مورد دیگر

Giovanni Samaey is a Professor of Applied Mathematics and Mathematical Engineering at KU Leuven's Faculty of Engineering Science. He leads research in computational and multiscale methods, focusing on plasma edge modeling for nuclear fusion reactors, Bayesian inversion, and Monte Carlo algorithms. Appointed in 2011, he currently supervises ten PhD students and has held a five-year membership in the Young Academy. His work bridges academic research with societal impact, co-founding Platform Wiskunde Vlaanderen to strengthen mathematics in Flanders. Education: Graduated in Computer Science (specializing in applied mathematics) from KU Leuven (1996), completed a PhD in 2001 under Prof. Dirk Roose, supported by an NFWO fellowship. He transitioned from engineering studies due to a passion for mathematics' societal impact, initially avoiding academia but ultimately embracing teaching and research. Research Interests: Development of numerical methods for multiscale phenomena, including micro-macro acceleration algorithms, multilevel Monte Carlo techniques, and hybrid fluid-kinetic models. His work addresses challenges in plasma physics, fusion energy systems, and inverse problems. Key contributions include the X-Factor book (with Joos Vandewalle) promoting mathematics outreach and advancing computational tools for plasma edge simulations. Awards/Honors: Member of the Young Academy (2016-2021), NFWO Aspirant Fellowship (2001-2002). His efforts in STEM advocacy and mathematics promotion through Platform Wiskunde Vlaanderen highlight his dedication to education and public engagement. Advising & Leadership: Supervises a team of PhD students in applied mathematics and computational science. Active in curriculum development and interdisciplinary collaborations, particularly in fusion energy modeling. His research group contributes to codes like EMC3-EIRENE for plasma edge simulations. Labs/Teams: Leads projects in multiscale numerical methods and plasma simulation within KU Leuven's engineering faculty. Collaborates internationally on fusion reactor modeling and Monte Carlo algorithm design, emphasizing computational efficiency and scalability.