جست‌وجوی استاد و پژوهشگر

Ingrid Moermanمشاهده پروفایل

استاد

• Wireless Networking
• Cognitive Radio Networks
• Internet of Things
• +۴ مورد دیگر

Ingrid Moerman is a part-time Professor at Ghent University and a staff member at the Internet Technology and Data Science Lab (IDLab), a core research group of imec embedded within Ghent University and the University of Antwerp. She coordinates mobile and wireless networking research and leads a team of over 30 researchers at Ghent University, with extensive involvement in European and national funding initiatives. She received her Electrical Engineering degree (1987) and Ph.D. (1992) from Ghent University. Her research spans collaborative networks, cognitive radio, software-defined radio, IoT, LPWAN, and high-density wireless access, emphasizing experimentally-supported development of next-generation wireless systems with practical implementations in spectrum management and real-time control. Recent publications (2024-2025) reveal a strong pivot toward AI-integrated wireless networking, featuring OFDMA scheduling innovations, Wi-Fi 6/7 interference mitigation, and time-sensitive networking for industrial applications. Key trends include 5G/6G convergence, vehicular communication enhancements, and digital twin frameworks for network observability, reflecting her focus on mission-critical industrial use cases. Her accolades include: 9 Best Paper Awards 2 FWO Prizes (Research Foundation - Flanders) IMEC Prize of Excellence 2001 MSc Thesis Award (as promoter) Best Demo/Exhibit Award at ICT 2013 DARPA Spectrum Collaboration Challenge Prize ($750,000) She has coordinated major EU projects (FP7/H2020: CREW, WiSHFUL, eWINE, ORCA) with industry partners, securing substantial funding for experimental wireless research. Her grant portfolio emphasizes collaborative innovation in spectrum sharing and neutral-host architectures for multi-operator environments. At IDLab, she directs advanced wireless testbeds supporting real-world validation of technologies like openwifi and White Rabbit, with active experimentation in time-sensitive networking and spectrum collaboration for industrial IoT deployments.

Vanessa Vermeirssenمشاهده پروفایل

استاد پژوهشی

• Systems Biology
• Bioinformatics
• Computational Biology
• +۷ مورد دیگر

Vanessa Vermeirssen is a Research Professor at Ghent University , leading the Computational Biology, Integromics and Gene Regulation (CBIGR) Laboratory and affiliated with the Cancer Research Institute Ghent (CRIG) . Her work focuses on unraveling disease mechanisms through bioinformatics, systems biology, and multi-omics integration. Specializes in gene regulatory networks , network inference , and machine learning Key application areas: neuroblastoma , glioblastoma , Alzheimer's disease , and neuroinflammation Develops tools like HTSplotter for high-throughput data analysis Research trends combine single-cell transcriptomics , multi-omics modeling , and personalized medicine approaches. Her lab applies network biology to identify therapeutic targets in complex diseases. Active in radiation-induced developmental defects and electroceutical therapies (e.g., vagus nerve stimulation) Investigates stress response networks in plants and humans

Wout Weijtjensمشاهده پروفایل

پژوهشگر ارشد

• Structural Health Monitoring
• Offshore Wind Turbines
• Fatigue Analysis
• +۲ مورد دیگر

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 Gaboraمشاهده پروفایل

استاد

• Creativity
• Cultural Evolution
• Cognitive Science
• +۵ مورد دیگر

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.

• Regulatory genomics
• Gene regulatory networks
• Computational biology
• +۷ مورد دیگر

Stein Aerts is a full professor at the Faculty of Medicine of KU Leuven and head of the Laboratory for Computational Biology (VIB-KU Leuven). He is affiliated with multiple institutes including VIB.AI Center for AI & Computational Biology, the Leuven Brain Institute, Leuven.AI, LIMNI, LISCO, and the Leuven Cancer Institute. He also serves on the Faculty Council of Medicine and departmental boards. Research Focus: Regulatory genomics and gene regulatory networks Single-cell transcriptomics and epigenomics Deep learning for genomics and enhancer design Neurodevelopmental genomics and evolution Cancer genomics and synthetic biology Comparative genomics across species (Drosophila, octopus, mammals, birds) His recent work emphasizes using AI-driven approaches to decode enhancer logic, model cell-type-specific gene regulation, and understand brain evolution. He leads multiple large-scale projects funded through 2029–2030, including SpaceTimeOmics and enhancer-targeted glioblastoma modeling. Scientific Output: Aerts has a prolific publication record with over 15 high-impact papers in 2024–2025 alone, including in Science , Cell Genomics , Nature Reviews Bioengineering , and eLife . His work spans methodological advances (e.g., HyDrop, CREsted, GAME) and biological discoveries in enhancer function, cell-type evolution, and neurodegeneration models. Institutional Roles & Collaborations: Principal investigator in 10+ active grants (2024–2030) Founder and head of the Computational Biology Laboratory at VIB-KU Leuven Member of steering committees for HPC curriculum and bioinformatics POC Active collaborator across European and international consortia

• Stroke Neurology
• Neuroimaging
• Cerebrovascular Diseases
• +۴ مورد دیگر

Robin Lemmens is a Professor at the Faculty of Medicine, KU Leuven, and leads the Laboratory of Neurobiology (VIB-KU Leuven). He serves as head of Academic Consultants Training in Specialist Medicine and Program Director of the POC Medical Specialist in Training. His affiliations include the LBI - KU Leuven Brain Institute and membership in multiple institutional committees including the Metaforum Steering Committee and Faculty Council of Medicine. Dr. Lemmens' research focuses on stroke neurology with particular expertise in neuroimaging, cerebrovascular diseases, and endovascular therapy. His work spans ischemic stroke management, anticoagulation therapy, intracerebral hemorrhage, and advanced imaging techniques for stroke diagnosis and treatment planning. Current research explores AI applications in stroke imaging, optimal timing of anticoagulation after stroke, and endovascular therapy in extended time windows. Analysis of recent publications reveals a strong emphasis on translational stroke research with significant contributions to clinical trial methodology. Key themes include validation of imaging biomarkers, optimization of thrombolytic and anticoagulant therapies, and development of AI tools for stroke lesion segmentation. His work frequently appears in high-impact journals including Stroke , Neurology , and The Lancet . Dr. Lemmens supervises research projects and students, with recent supervision including Oosterbos, C. on peroneal nerve entrapment research. His grant portfolio includes multiple active projects totaling millions in funding, with recent grants focusing on secondary stroke prevention, comprehensive stroke management systems, and AI for stroke outcome prediction. He leads the Laboratory of Neurobiology at VIB-KU Leuven, which collaborates extensively with international stroke research networks. Current research directions include developing patient-centered stroke care pathways, advanced imaging techniques for early ischemic changes, and personalized stroke diagnostics and treatment protocols.

Pieter Simoensمشاهده پروفایل

استادیار

• Distributed Artificial Intelligence
• Edge Computing
• Algorithms for Neuromorphic Computing
• +۲ مورد دیگر

Pieter Simoens is an Assistant Professor at Ghent University and affiliated with the imec research institute. He works at the intersection of distributed artificial intelligence, edge computing, and collective intelligence, with a focus on AI applications for resource-constrained environments and robotic systems. His research explores innovative approaches to machine learning deployment in heterogeneous infrastructures, task planning for IoT-integrated robotics, and modeling collective decision-making processes. He has contributed to frameworks like DIANNE for distributed deep learning and developed methods for cognitive modeling in reinforcement learning scenarios. With over 100 publications, his recent work spans adaptive neural networks, privacy-preserving surveillance, UAV hyperspectral data analysis, and computational fairness in AI systems. He leads research initiatives within the Internet Technology and Data Science Lab (IDLab) and contributes to educational programs in software engineering and applied machine learning. Responsible for courses on software engineering, mobile development, system design, and applied machine learning Active in edge computing and neuromorphic algorithms research Develops AI solutions for robotics, surveillance, and industrial IoT applications

• Calcium Signaling in Cardiomyocytes
• Epigenetics in Cardiac Biology
• Cardiac Hypertrophy
• +۴ مورد دیگر

LLewelyn Roderick is a full professor at the Department of Cardiovascular Sciences , Faculty of Medicine, KU Leuven. He leads the Experimental Cardiology unit and contributes to doctoral committees and faculty governance. Research focuses on calcium signaling microdomains, epigenetic regulation of cardiac growth, and arrhythmogenesis mechanisms. Projects include studies on obesity-induced cardiomyocyte dysfunction, hypoxia sensitivity in cardiac cells, and DNA methylation in aging hearts. Current initiatives investigate connexin-43 hemichannels, neutrophil extracellular traps, and 3D cardiac models for drug discovery. His work spans fundamental cardiovascular biology and translational approaches, including collaborations on immune-monitoring technologies and cardiac progenitor cell metabolism. Teaching contributions include advanced courses on epigenetics and cardiovascular biology.

Van Anh Huynh-Thuمشاهده پروفایل

استادیار

• Machine Learning
• Bioinformatics
• Gene Regulatory Network Inference
• +۳ مورد دیگر

Vân Anh Huynh-Thu is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Liège (Belgium). Her research focuses on improving machine learning techniques with an emphasis on model interpretability. She is based at B28: Systems and Modeling in Quartier Polytech, Allée de la Découverte 10, 4000 Liège, Belgium. Her primary research interests span Machine Learning , Bioinformatics , and Gene Regulatory Network Inference . Dr. Huynh-Thu has developed several influential methods including GENIE3, dynGENIE3, and Jump3 for inferring gene regulatory networks from expression data. Her work bridges the gap between machine learning theory and biological applications, particularly in understanding complex disease mechanisms through computational approaches. She has made significant contributions to interpretable machine learning models that maintain high predictive accuracy while providing insights into feature importance and model behavior. Her research demonstrates a progression from purely computational methods toward translational applications in medical research. Analysis of her recent publications reveals a clear trajectory from foundational work on gene regulatory network inference toward broader applications in medical research, particularly in Crohn's disease. Her research increasingly integrates machine learning with clinical applications, demonstrating a shift from purely computational methods to translational research with direct medical implications. The consistent emphasis across her work is on interpretability, rigorous validation, and the application of tree-based methods to complex biological systems, with a growing focus on proteomics and biomarker discovery for inflammatory bowel diseases. Dr. Huynh-Thu maintains an active GitHub presence with implementations of her methods, demonstrating her commitment to open science and reproducibility. Her software repositories have garnered significant attention from the research community, with GENIE3 alone having 88 stars and 37 forks on GitHub. She has developed multiple implementations of her algorithms in Python, MATLAB, and R, making them accessible to researchers across different computational environments. Her work has been influential in the DREAM challenges, where GENIE3 was the best performer in two network inference competitions.

Maxime Gobertمشاهده پروفایل

پژوهشگر

• Database Systems
• Hybrid Polystores
• Database Schema Evolution
• +۴ مورد دیگر

Maxime Gobert is a researcher at the University of Namur's Faculty of Computer Science, specializing in database systems and software engineering. Having completed his PhD in March 2023 titled 'Design, Manipulation and Evolution of Hybrid Polystores,' Gobert has established himself as an expert in hybrid database systems, particularly focusing on the HyDRa framework for modeling and evolving polystores. His research interests span database systems, hybrid polystores, database schema evolution, software engineering, data-intensive systems, and static program analysis. Gobert's work bridges theoretical database concepts with practical applications, particularly in NoSQL databases like MongoDB and complex hybrid data storage environments. His publication record demonstrates a clear trajectory from his 2013 Master's thesis on database reverse engineering through to his recent work on database testing best practices and sign language processing applications. His research shows strong collaboration with colleagues at the University of Namur, particularly with Professor Cleve A., and extends to international collaborations as evidenced by his 2016 guest researcher position at the University of Geneva. Best New Idea and Emerging Results (NIER) Paper Award at the 20th IEEE Working Conference on Source Code Analysis and Manipulation (SCAM 2020) Jean Fichefet 2013 award Gobert has contributed significantly to the development of the HyDRa framework for hybrid polystore management and has extended his research into sign language processing through collaborative projects creating bilingual sign language dictionaries and parallel corpora. His work demonstrates both technical depth in database systems and a commitment to applying this expertise to accessibility-focused applications.

• Precision Livestock Farming
• Animal Monitoring Systems
• Machine Learning Applications in Agriculture
• +۵ مورد دیگر

Tomas Norton is a Senior Lecturer at the Faculty of Bioscience Engineering, Department of Biosystems at KU Leuven. He is actively affiliated with multiple research units including the Division of Bio-Environmental Control, the KU Leuven Brain Institute (LBI), and the KU Leuven Institute for Integration of Micro- and Nano-scale Technologies (LIMNI). His work is centered at the Animal and Human (A2H) research unit located at Castle Park Arenberg. Dr. Norton's research focuses on precision livestock farming with particular expertise in computer vision, machine learning, and sensor technologies applied to animal monitoring. His current projects span sustainable agriculture, animal vocalization analysis, and bio-response monitoring systems across multiple species including poultry, pigs, and buffalo. He serves as promotor on numerous research initiatives funded through 2028-2029 that address critical challenges in sustainable food production while improving animal welfare. His recent publications demonstrate a strong trend toward AI-driven solutions for animal monitoring, with particular emphasis on behavior recognition, health assessment through sound analysis, and robotic management systems. These works appear primarily in agricultural technology journals with a focus on practical implementation of advanced computational methods in farming contexts. As an academic leader, Dr. Norton serves on the Faculty Council of Bioscience Engineering, the Doctoral Committee for Bioscience Engineering, and the Departmental Council for Biosystems. He teaches courses including Modelling of Biosystems, Bioresponse Measurements and Process Control, and Sustainable Precision Livestock Farming, integrating his research expertise directly into his educational practice. His laboratory work within the A2H unit represents a multidisciplinary approach that bridges engineering, computer science, and animal science to develop practical technological solutions for modern agricultural challenges, with particular emphasis on sustainability and welfare improvements in livestock production systems.

• Mental Fatigue
• Human Physiology
• Sports Physiotherapy
• +۶ مورد دیگر

Kevin De Pauw is a postdoctoral researcher at the Department of Physiotherapy, Human Physiology and Anatomy at Vrije Universiteit Brussel (VUB). He actively contributes to 12 research projects with a focus on robotics, mental fatigue, brain physiology, and sports physiotherapy. Current projects include Brubotics, APEX, and TBrainBoost Collaboration network spans Belgium, Germany, and Netherlands Key research themes: Mental Fatigue (100%), Robotics (100%), and Prosthetics (52%) Research Interests: His work explores the intersection of brain physiology, fatigue mechanisms, and robotics applications in rehabilitation. He develops predictive musculoskeletal simulations and investigates inter-limb asymmetry in athletes. Article Trends: Recent publications show increasing focus on robot-assisted rehabilitation , brain neuroplasticity , and mental fatigue quantification . Research combines AI-driven wearable robotics with neurophysiological monitoring . Student Supervision: He mentors Master's students in topics related to Lower limb asymmetry analysis Adolescent cognition-fitness relationships Exoskeleton interface design Laboratory Affiliation: Member of Brubotics and TBrainBoost teams at VUB, working on sustainable human-centered robotics and neurocirculation enhancement technologies.

Lesley De Cruzمشاهده پروفایل

پژوهشگر ارشد

• Climate Modeling
• Regional Climate Downscaling
• AI for Environmental Systems
• +۳ مورد دیگر

Lesley De Cruz is a Research Fellow at Vrije Universiteit Brussel's Electronics and Informatics department within the School of Electronics and Computer Science, with concurrent research affiliation at the Royal Meteorological Institute of Belgium since 2012. Current projects include climate-resilient urban modeling through BRGEOZ464 and flood prediction systems under FWOAL1127. Research focuses on AI-driven climate modeling with expertise in nonlinear dimension reduction (DIRESA framework), urban climate resilience, and renewable energy meteorology. Key methodologies integrate deep learning with environmental physics for applications including real-time flood prediction offshore wind farm optimization LEGO-based urban climate prototyping regional climate downscaling Recent publications (2023-2025) demonstrate strong trends in geospatial AI for environmental systems, with 64% focusing on climate change impact analysis, 54% on urban applications, and 51% on control measure development. The DIRESA framework represents a significant contribution to nonlinear dimension reduction in climate informatics. Awards include: Matìère Grise Science Communication Trophy (2024) Major media recognition for breakthrough rainfall prediction model (2021) Supervises multiple PhD candidates and leads public engagement initiatives including CurieuCity and Dag Van de Wetenschap. Current grants total 12 active projects (2021-2029) with €2.8M+ funding, primarily focused on climate adaptation and sustainable technology development. Labs and teams include the Climate Informatics Group at VUB and collaborative networks with Ghent University and the Flemish Institute for Carbon-Aware Technologies.

• Combinatorial Optimization
• Algorithm Design and Analysis
• Game Theory and Social Choice
• +۴ مورد دیگر

Jannik Matuschke serves as Associate Professor in the Department of Decision Sciences and Information Management at KU Leuven's Faculty of Economics and Business (FEB). He is an active member of both the KU Leuven Institute for Artificial Intelligence (Leuven.AI) and the KU Leuven Institute for Mobility (LIM), holding office at Hogenheuvelcollege (HOGC) 04.123 in Leuven, Belgium. His academic career spans multiple prestigious institutions across Europe, reflecting his international recognition in operations research and theoretical computer science. Dr. Matuschke completed his PhD in Mathematics in 2013 at Technische Universität Berlin under Martin Skutella and Britta Peis. His academic journey included a postdoctoral position at Universidad de Chile (2014), a DAAD P.R.I.M.E. fellowship at the University of Rome 'Tor Vergata' (2015), and a junior group leader/lecturer position at Technische Universität München (2016-2018) before joining KU Leuven in 2019. His research focuses on the intersection of discrete mathematics, theoretical computer science, and operations research, with specific expertise in combinatorial optimization, algorithm design and analysis, game theory and social choice, robustness and uncertainty, and logistics applications. Dr. Matuschke has made significant contributions to network flow theory, security games, and robust optimization frameworks, developing both theoretical foundations and practical applications. Analysis of his recent publications reveals a strong emphasis on robustness under uncertainty, with increasing focus on security applications and theoretical aspects of scheduling problems. His work demonstrates consistent innovation in decomposing complex optimization problems and developing approximation algorithms for challenging combinatorial settings. 2024 Meritorious Service Reward of the journal Operations Research Dr. Matuschke actively mentors several PhD students and postdocs, including Yanfei Chen, Léonie Gallois, Phablo Moura, Felix Rauh, and Fei Wu. He leads significant research projects such as 'Rigidity and Flexibility: Structures and Algorithms' (starting 2025), 'Designing resilient and recoverable infrastructures via multi-level and multi-stage optimization' (2022), and 'Optimization and analytics for stochastic and robust project scheduling' (2020), with funding from diverse sources including KU Leuven start-up grants, FWO research projects, and DAAD fellowships. As an integral member of the academic community, Dr. Matuschke serves as Associate Editor for Omega (since 2023), Operations Research Letters (since 2024), and OR Spectrum (since 2019). He co-chairs the program committee for WAOA 2025 and has participated in numerous prestigious conference committees. At KU Leuven, he coordinates the 'Master's Thesis in Production and Logistics' program and serves on the Teaching Portfolio Peer Review Committee.

Peter Lambertمشاهده پروفایل

دانشیار

• multimedia signal processing
• visual communication
• computer graphics
• +۲ مورد دیگر

Peter Lambert is a full-time Associate Professor at Ghent University – imec (Belgium), affiliated with the Internet Technology and Data Science Lab (IDLab) where he coordinates the MEDIA research team since 2013. His academic background includes a Master's degree in Science (Mathematics) and Applied Informatics from Ghent University, followed by a Ph.D. in Computer Science from the same institution in 2007. Prior to his current role, he served as a Technology Developer at Ghent University (2010-2013). Lambert's research focuses on: Multimedia signal processing and visual communication systems Computer graphics and computational geometry Augmented and virtual reality (AR/VR) technologies Video compression and perceptual quality assessment Multimedia security and digital watermarking His recent publications (2024-2025) demonstrate strong emphasis on real-time multimedia systems, VR/AR applications, perceptual quality metrics, and multimedia security. Research trends include deep learning-based video forensics, light field rendering optimizations, perceptual hashing techniques, and adaptive video streaming solutions. As leader of the IDLab-MEDIA team, Lambert oversees research on emerging visual media formats with applications in immersive experiences. The team develops technologies like OpenDIBR (real-time light field renderer) and maintains datasets such as SILVR (Synthetic Immersive Large-Volume Plenoptic Dataset).