جست‌وجوی استاد و پژوهشگر

Nick Vannieuwenhovenمشاهده پروفایل

استادیار

• Tensor decompositions
• Numerical analysis
• Riemannian optimization methods
• +۲ مورد دیگر

Nick Vannieuwenhoven is an Assistant Professor at KU Leuven, affiliated with the Department of Computer Science and the NUMA Division. He serves as the Exchange Coordinator for the Master in Mathematical Engineering and is an Associate Editor for The Electronic Journal of Linear Algebra and SIAM Journal on Applied Algebra and Geometry . His research focuses on tensor decompositions, numerical analysis, Riemannian optimization, and applications in data science. He obtained his PhD in 2015 under Professors Karl Meerbergen and Raf Vandebril, funded by the FWO (Research Foundation Flanders). His postdoctoral research (2015–2021) was also supported by FWO fellowships. His research group investigates tensor decompositions, multilinear algebra, and numerical techniques for data science, with a focus on condition number analysis and Riemannian optimization. Collaborators include experts like Carlos Beltrán, Paul Breiding, and Simon Telen. Current students include Jana Jovcheva, Bram Leys, and David Thorsteinsson, working on manifold-valued function approximation, group-invariant networks, and data-based engineering. Key awards include FWO fellowships for his PhD and postdoctoral studies. Grants include support for postdoctoral researchers via MSCA and FWO schemes. Notable projects involve Tucker compression libraries (ATC) and geometric analysis of tensor networks. His work bridges algebraic geometry, numerical analysis, and machine learning, emphasizing stability and computational efficiency.

Christophe Geuzaineمشاهده پروفایل

استاد

• Computational Electromagnetism
• Scientific Computing
• Finite Element Method
• +۵ مورد دیگر

Prof. Christophe Geuzaine is a Full Professor in the Department of Electrical Engineering and Computer Science at the University of Liège , Belgium. He previously held academic positions at Case Western Reserve University (Assistant Professor of Mathematics) and California Institute of Technology (Postdoctoral Scholar in Applied and Computational Mathematics). Research Focus: Computational electromagnetism, biomedical/geophysical modeling, and open-source software development (Gmsh, GetDP) Teaching: Courses in electromagnetic energy conversion, scientific computing, and multiphysics projects Location: Montefiore Institute B28, Quartier Polytech 1, Liège, Belgium His research employs ONELAB tools for high-temperature superconductivity ( Life-HTS ), photonics ( ONELAB-Photonics ), and domain decomposition ( GetDDM ). Current work emphasizes large-scale time-harmonic wave simulations and quantum computing applications.

Bart Kuykenمشاهده پروفایل

استاد

• Photonics
• Silicon Photonics
• Nonlinear Optics
• +۷ مورد دیگر

Bart Kuyken is a Professor at Ghent University (Photonics Group, INTEC Department) and affiliated with imec. His research focuses on advanced photonics technologies, including heterogeneous integration of materials like lithium niobate, gallium arsenide, and graphene onto silicon and silicon nitride platforms. Key areas include micro-transfer printing techniques, nonlinear optics, quantum photonics, and optoelectronic device integration for applications in telecommunications, sensing, and quantum computing. He leads projects on scalable fabrication methods for integrated photonic platforms, emphasizing high-speed modulators, mode-locked lasers, and entangled photon sources. His work bridges fundamental materials science with applied engineering, targeting commercial foundry-compatible processes. Recent innovations include ultra-low-loss waveguides, high-performance III-V lasers on silicon nitride, and cryogenic quantum electro-optic devices. Collaborations with imec highlight industry-relevant solutions for next-generation optical transceivers and AI/ML-enabled photonic systems. His research publications span 2021–2025, with a strong focus on advancing silicon photonics and overcoming integration challenges through novel printing and epitaxial techniques.

• Bioinformatics
• DNA Sequencing
• Genomics
• +۳ مورد دیگر

Dries Decap is a postdoctoral researcher at the Faculty of Engineering and Architecture, Ghent University, within the Department of Information Technology (INTEC). His work focuses on bioinformatics, DNA sequencing, and computational biology with applications in genomics and high-performance computing. Research Interests: Dr. Decap specializes in developing scalable bioinformatics frameworks for DNA and RNA sequencing analysis, including tools like elPrep and Halvade . His research spans variant calling, motif discovery, and parallel computing implementations. Projects: He led his doctoral project (2011-2017) on "Doctoral project Dries Decap" under supervisors Bart Dhoedt and Jan Fostier. He also contributed to projects like IAMBEE for adaptive pathway analysis and BLSSpeller for regulatory motif discovery. Collaborations: Collaborators include Kathleen Marchal, Charlotte Herzeel, and Pascal Costanza. He has worked with institutions like IMEC and Ghent University on scalable genomic data processing solutions.

• Bioinformatics
• High Performance Computing
• Genomics
• +۴ مورد دیگر

Giles Miclotte is a postdoctoral researcher at Ghent University with dual appointments: Postdoctoral Assistant in the Faculty of Sciences (Department of Plant Biotechnology and Bioinformatics) and Postdoctoral Researcher in the Faculty of Engineering and Architecture (Department of Information Technology). He is affiliated with IMEC research institute. His research focuses on: Bioinformatics and computational genomics High-performance computing for biological data Algorithm development for error correction in sequencing technologies Genome assembly methods using de Bruijn graphs Network analysis in cancer genomics and plant systems biology Proteomics and protein sequencing methodologies His recent publications (2015-2022) demonstrate a consistent focus on improving sequencing technologies and genomic analysis methods. Key themes include: advanced error correction algorithms for Illumina and third-generation sequencing, genome assembly optimization, computational approaches for cancer driver gene identification, and novel applications of graph-based algorithms in bioinformatics. Awards: Outstanding Presentation Award at ISMB 2015 He has supervised PhD students including Razgar Seyed Rahmani (2022) and collaborates extensively with research teams across bioinformatics and computational biology domains.

• Urban Climate
• Climate Modeling
• Atmospheric Physics
• +۷ مورد دیگر

Steven Caluwaerts is an Associate Professor at Ghent University's Faculty of Sciences, Department of Physics and Astronomy (WE05). His research focuses on urban climate science, climate modeling, and meteorology, with particular expertise in urban climate modeling, weather modeling, observational networks, and citizen science applications. He is deeply involved in European climate research initiatives, particularly those related to urban environments and climate change impacts. Dr. Caluwaerts' research interests span urban climate systems, high-resolution climate modeling, and the impacts of climate change on urban environments and cultural heritage. His work integrates advanced computational techniques with field observations to address critical questions about urban heat islands, climate adaptation strategies, and building heritage preservation. He has developed innovative approaches for downscaling climate data to urban scales and has made significant contributions to understanding how climate change affects building materials and urban infrastructure. His publication record reveals a strong focus on urban climate modeling and climate change impacts, with particular emphasis on creating high-resolution climate data for urban areas, validating climate models with observational networks, and assessing climate risks to building heritage. Recent work shows increasing attention to practical applications of climate science, including heat stress monitoring for public health and sports events, climate adaptation strategies for European cities, and the development of tools for processing crowdsourced meteorological data. Dr. Caluwaerts collaborates extensively with researchers across Europe, particularly within the CORDEX framework, and has supervised numerous PhD students whose work focuses on urban climate modeling, climate change impacts on buildings, and urban heat island effects. His research is supported by various European and Belgian climate initiatives, with applications in urban planning, heritage conservation, and public health. He is actively involved in citizen science initiatives that engage schools and the public in urban climate monitoring, demonstrating his commitment to making climate science accessible and relevant to broader society. His work with the MetObs toolkit exemplifies this approach, providing user-friendly tools for processing non-traditional meteorological observations.

Tom Braeckeveltمشاهده پروفایل

پژوهشگر ارشد

• Materials Science
• Perovskite Solar Cells
• Computational Chemistry
• +۳ مورد دیگر

Tom Braeckevelt is a Research Fellow at Ghent University, Belgium, working within the computational materials science group led by Prof. Veronique Van Speybroeck. Based at Tech Lane Ghent Science Park (Technologiepark 46, Zwijnaarde), he collaborates extensively with experimental teams including Prof. Johan Hofkens (photophysics) and Prof. Sara Bals (electron microscopy), bridging theoretical modeling with advanced characterization techniques to solve stability challenges in next-generation photovoltaics. Education: PhD in Materials Science, Ghent University (2018). Dissertation: Designing 2D hybrid organic-inorganic perovskites for game-changing photovoltaics , supervised by Prof. Veronique Van Speybroeck and Dr. Kurt Lejaeghere. His research centers on perovskite stability mechanisms through multiscale computational modeling (DFT, machine learning potentials, molecular dynamics) integrated with experimental validation (TEM, GIWAXS, spectroscopy). Key focus areas include phase transition kinetics, strain engineering, doping strategies, and interfacial design for cesium lead halide perovskites. This work addresses critical barriers to commercial solar cell deployment, particularly ambient-condition stability and efficiency retention. From 2019-2025, Dr. Braeckevelt co-authored 13 high-impact publications including Science (2019), Nature Communications (2022), and ACS Nano (2025), demonstrating progression from fundamental phase transition studies to machine learning-enhanced stability solutions. Recent work expands into covalent organic frameworks and rare-event sampling algorithms, reflecting methodological diversification while maintaining photovoltaic applications as the core driver. No scientific awards or fellowships were documented in the source materials. Supported by institutional research grants at Ghent University, Dr. Braeckevelt has presented findings at 8+ international conferences including PSCO19 (Lausanne), ICAMM (Rennes), and DFT2022 (Brussels). His invited talk at the 2025 Eindhoven Psiflow workshop highlights growing recognition in machine learning for perovskites. No student supervision roles were indicated in current position. He operates within Ghent's integrated materials research ecosystem, contributing to cross-disciplinary projects that combine computational prediction with nanoscale characterization to accelerate renewable energy technology development.

Fabio Jose Ayresمشاهده پروفایل

استاد مدعو

• computer vision
• machine learning
• image processing
• +۲ مورد دیگر

Fabio Jose Ayres serves as an Adjunct Professor at Insper, contributing to the development of engineering programs in Computer Science and Computer Engineering. He holds a PhD in Electrical and Computer Engineering from the University of Calgary and bachelor's/master's degrees in Electrical Engineering from the Polytechnic School of the University of São Paulo (Poli-USP). His professional background includes a Postdoctoral Fellowship in Biomedical Engineering at the University of Calgary, research associate roles at the National Research Council of Canada, and software engineering positions at Opal-RT Technologies and Google. His educational qualifications: Bachelor's and Master's in Electrical Engineering, Polytechnic School of the University of São Paulo (Poli-USP) PhD in Electrical Engineering, University of Calgary, Canada Dr. Ayres' research integrates computer vision, machine learning, and high-performance computing to address challenges in image processing and information retrieval systems. His interdisciplinary work bridges electrical engineering fundamentals with modern computational techniques, particularly relevant to biomedical applications and large-scale software solutions developed during his industry tenure.

Tom Barbetteمشاهده پروفایل

استادیار

• High-Speed Networking
• Network Function Virtualization (NFV)
• Load-Balancing
• +۳ مورد دیگر

Tom Barbette is an Assistant Professor in the Computer Engineering Center (INGI) department at the Louvain Polytechnic School (EPL) of Université catholique de Louvain (UCLouvain), Belgium. He leads the Efficiency of Networked Systems Group , focusing on programmable networks, SmartNICs, NFV, data-centers, and high-speed packet processing. PhD (2018) from Université de Liège (advisor: Laurent Mathy) Post-doctoral research at KTH, Sweden (2018-2021) and UCLouvain (2021-2022) His research explores redefining internet communication paradigms through programmable infrastructure like SmartNICs and P4. Key themes include: High-speed networking and load-balancing Sub-atomic communication models for disaggregated systems KERNEL bypass techniques for performance optimization He has contributed to major conferences like SIGCOMM, NSDI, and CoNEXT, with patents on network interface optimization. His group collaborates on projects such as: ASNI (SmartNICs programming interface) HIRT (High-speed Forward Erasure Correction) Reframer (Network stream optimization)

• Hydrodynamic Modeling
• Oceanography
• Fluid Mechanics
• +۳ مورد دیگر

Eric Deleersnijder is a Lecturer at the Université catholique de Louvain, affiliated with the Louvain Polytechnic School (EPL) and the Institute of Mechanics, Materials and Civil Engineering (iMMC). He conducts research within the Applied Mechanics and Mathematics (MEMA) unit of iMMC and collaborates with the Earth and Life Institute (ELI). His teaching responsibilities include courses such as General Mechanics, Marine Hydrodynamics, Fundamentals of Geographic and Environmental Modelling, Mathematical Ecology, Fluid Mechanics II, and Physics of Fluids. Deleersnijder's research focuses on hydrodynamic modeling , coastal and estuarine dynamics , and numerical methods for environmental systems. Key areas include: multi-scale ocean modeling, water renewal timescales, sediment transport, and contaminant dispersion in aquatic systems. His work emphasizes practical applications in ecosystems like the Scheldt Estuary, Nador Lagoon (Morocco), and Meuse River, alongside theoretical advances in finite volume/discontinuous Galerkin methods. Analysis of his recent publications reveals a strong emphasis on: Development of advanced numerical schemes (IMEX Runge-Kutta, DG-FEM) for 3D hydrodynamic systems Environmental risk modeling of radionuclide dispersion in river networks Hydrodynamic diagnostics (water age, residence time) for coastal management Transdisciplinary applications from Titan's subsurface oceans to North African lagoons He actively collaborates on continental-scale hydrological projects (e.g., Scheldt and Meuse river systems) and leads developments in the SLIM (Second-generation Louvain-la-Neuve Ice-ocean Model) platform. His team addresses climate impacts on water renewal and sediment dynamics through high-performance computing approaches.

• Aerospace Engineering
• Mechanical Engineering
• Thermal Engineering
• +۳ مورد دیگر

Patrick Hendrick is an Associate Professor at the Department of Mechanical Engineering, Faculty of Engineering Science, KU Leuven. His work spans aerospace engineering, thermal systems, and sustainable energy technologies. Research Focus : Hendrick's research investigates propulsion systems (hybrid rocket motors, fuel additives), energy conversion (pump-as-turbine micro-storage), and thermal engineering challenges (gas turbine vanes, heat exchangers). He also explores wastewater thermal recovery for sustainable residential heating. Teaching : He teaches aircraft engines and turbomachinery courses at KU Leuven, translating complex fluid dynamics concepts into practical applications. Publications : His recent work (2017-2019) focuses on aerospace propulsion, thermal systems optimization, and sustainable energy integration, with contributions to Aerospace Science and Technology and Applied Energy .

• Fluid Mechanics
• Turbomachinery
• Computational Fluid Dynamics
• +۴ مورد دیگر

Koen Hillewaert is a Lecturer at the University of Liège (ULiège), working within the Faculty of Applied Sciences, specifically in the Department of Aerospace and Mechanics. He is affiliated with the Design of Turbomachines and Propulsors (DoTP) research group, located in Building B52/3 at Quartier Polytech 1. His work focuses on advanced computational methods for fluid dynamics and turbomachinery applications. His educational background includes: Doctor of Engineering Sciences from Catholic University of Louvain (2013) Electromechanical Engineer from Ghent University (1995) Hillewaert's research spans multiple areas of fluid dynamics and turbomachinery, with particular expertise in computational fluid dynamics using high-order methods. His work focuses on turbomachinery design and analysis, including gas turbines, hydraulic turbines, pumps, and compressors. He has developed expertise in discontinuous Galerkin methods for fluid flow simulations, with applications ranging from aerospace propulsion to wind energy systems. His research integrates numerical analysis, machine learning techniques for flow modeling, and advanced computational techniques for plasma physics applications. His recent publications demonstrate a strong focus on high-fidelity simulation methods for turbomachinery flows, with particular attention to wall-resolved simulations, turbulence modeling, and geometric variability effects. There's a clear trend toward integrating machine learning techniques with traditional computational fluid dynamics approaches, particularly for wall modeling in separated flows. His work spans both fundamental numerical method development and practical engineering applications in aerospace and energy systems. Hillewaert holds significant institutional roles including Vice-president of KNC in the European Research Community on Flow Turbulence and Combustion (ERCOFTAC) and membership on the steering committee of the CFD General Notation System (CGNS), indicating his standing in the international CFD community. He teaches several advanced courses including Aerospace Propulsion, Aerothermodynamics of High-Speed Flows, Wind Energy, Flow in Turbomachines, Practical Fluid Mechanics for the Process Industry, and Turbomachines, demonstrating his broad expertise across fluid dynamics and turbomachinery applications.

• Computer graphics
• Virtual reality
• High performance computing
• +۵ مورد دیگر

Prof. Frank Van Reeth serves as Full Professor in the Department of Computer Sciences at Hasselt University's Faculty of Sciences, where he directs the Digital Future Lab and leads the Applied Computer Science Lab within the Expertise Centre for Digital Media (EDM) at Campus Diepenbeek. His institutional roles include Vice-Presidency of Examination Boards for Informatics and Computer Science programs. His research spans computer graphics, virtual reality, high performance computing, and human-computer interaction with strong emphasis on industrial applications. Current projects include NORM.AI for efficient AI rendering, MAXVR-INFRA for digital-physical workspaces, and MAX-R for mixed reality pipelines, demonstrating his focus on bridging theoretical computer science with practical implementations in computer vision and extended reality systems. Prof. Van Reeth has supervised 23 PhD students to completion since 1997, with recent graduates working on synthetic data training and spatial context-aware services. His active supervision of 4 doctoral candidates focuses on hardware-accelerated deep learning and industrial inspection systems. He teaches core courses in computer graphics, visual computing, and problem solving while maintaining leadership in EDM's €15M+ research portfolio. The Applied Computer Science Lab under his direction operates as EDM's primary research engine, specializing in real-time rendering, 3D modeling, and computer vision solutions. The Digital Future Lab he directs provides the infrastructure backbone for Hasselt University's mixed reality research, enabling collaborations across 15+ ongoing projects with industrial partners in manufacturing and digital media sectors.

• Distributed systems
• Networking and communications
• Communication networks
• +۶ مورد دیگر

Professor Wim LAMOTTE is a Full Professor in the Faculty of Sciences at Hasselt University, affiliated with the Computer Sciences capacity group and based at the Expertise Center for Digital Media (EDM) on Campus Diepenbeek. He leads research within the Applied Computer Science Lab and Digital Future Lab while serving as President of both the Capacity Group Board INF and the Information Security Committee. His research spans multiple critical areas of computer science: Distributed systems and parallel computing Networking and communication protocols Cryptography and privacy security High performance computing Computer graphics and virtual environments Professor Lamotte has supervised 13 PhD students since 2007, with recent completions focusing on network security and privacy. His teaching portfolio includes core computer science courses across networking, security, programming, and distributed systems for both undergraduate and graduate students. His research activities demonstrate sustained productivity with 13 projects spanning from 2009 to ongoing work through 2026, showing particular strength in securing networked applications and optimizing communication systems. Current projects address next-generation video delivery, cyber security threats, and web performance automation. As an academic leader, Professor Lamotte holds significant governance roles within the Faculty of Sciences while maintaining active research and teaching commitments across multiple computer science disciplines.

• High Performance Computing
• Scientific Computing
• Mathematical Software
• +۵ مورد دیگر

Associate Professor Jori LIESENBORGS is affiliated with Hasselt University's Faculty of Sciences, Department of Computer Sciences, and the Expertise Centre for Digital Media. They lead the Applied Computer Science Lab while contributing to the Digital Future Lab initiative. Research spans high-performance computing , scientific modeling , and data-intensive applications with discipline codes including High Performance Computing (01020702), Mathematical Software (01020703), and Numerical Computation (01020705). Key specialties involve visual analytics for high-dimensional data, AI-driven video streaming optimization, and epidemiological simulations for infectious disease control. Current supervised PhD projects include: Daniël Bot: Visual Analytics for High-Dimensional Data Hannes Keunen: AI & Video Streaming (2024-2028) Elise Kuylen: Individual-based Disease Transmission Models (2023) Jan Yperman: Machine Learning in MS Research (2021) Balazs Nemeth: Pharmacometrics Applications (2020) Active research grants focus on AI-driven video streaming infrastructure and HIV/Hepatitis C outbreak modeling using phylogenetic data. Teaching responsibilities include Algorithms, Operating Systems, Parallel Systems, and Computational Optimization across the 2024-2026 academic cycles. The Applied Computer Science Lab provides specialized computational resources at Campus Diepenbeek (EDM-2.10), supporting both theoretical algorithm development and real-world implementations in medical and media technology domains.