جستجوی استاد راهنمای دانشگاهی

• Human Health Engineering
• Wearable Technology
• Precision Livestock Farming
• +۳ مورد دیگر

Jean-Marie Aerts is a full professor and department chair at the Department of Biosystems within the Faculty of Bioscience Engineering at KU Leuven . He serves as chairman of the Leuven Center for Medical Technology and division head of Bio-Environmental Control and BioAsyst Division . Active member of multiple institutes including DigiSoc – KU Leuven Institute for Digital Society , iSi Health , and Leuven One Health . Head of M3-BIORES research group Chair of Departmental Council for Biosystems Researcher at Animal and Human Health Engineering division His research focuses on Human Health Engineering , with recent projects like WeCARE (wearable technology for childhood cancer care), StressTRACS (stress tracking with wearables), and Precision Biomanufacturing of Joint Implants . Publications span biomedical engineering, movement disorders, and sports performance optimization. Recent article trends show emphasis on machine learning for movement analysis , wearable sensor validation , and cross-sector health technology applications in Parkinson's disease, cerebral palsy, and athlete monitoring.

• Biological Shape Analysis
• Genetics of the Human Face
• Genetics of the Brain
• +۵ مورد دیگر

Peter Claes is a Professor at KU Leuven with dual appointments in the Faculty of Engineering Sciences and Faculty of Medicine. He serves as head of the Laboratory for Image Processing in Genetics and is affiliated with both the Department of Electrical Engineering (ESAT) and Department of Human Genetics. His institutional roles include membership in the ESAT Division - Processing of Speech and Images, iSi Health - KU Leuven Institute for Physics-based Modeling for In Silico Health, and Leuven.AI - KU Leuven Institute for Artificial Intelligence. His research focuses on: Biological shape analysis Genetics of the human face Genetics of the brain Medical image analysis 3D facial morphometry Imaging genetics Prof. Claes leads multiple major research projects funded through KU Leuven, including studies on craniofacial morphology, genetics of facial features, and AI applications in healthcare. His work integrates advanced imaging techniques with genetic analysis to understand genotype-phenotype relationships, particularly in craniofacial development. His publication record demonstrates a strong trend toward integrating multi-omics data with geometric deep learning approaches. His research spans genetics, computer vision, bioinformatics, and clinical medicine, with applications in syndrome diagnosis, forensic science, and personalized medicine. As Program Director of the POC Artificial Intelligence for the Faculty of Engineering Sciences, he plays a key role in shaping AI education at KU Leuven. His teaching portfolio includes courses on biometrics, AI in healthcare, and medical imaging analysis. He leads the Laboratory for Image Processing in Genetics, which develops and applies advanced image processing techniques to genetic research, particularly in craniofacial morphology. His work has significant implications for clinical genetics, orthodontics, and forensic identification.

• Genomic Medicine
• Quantitative Genetics
• Inflammatory Bowel Disease (IBD) Research
• +۳ مورد دیگر

Isabelle Cleynen is a Senior Lecturer at the Faculty of Medicine, KU Leuven, and leads the Laboratory for Complex Genetics within the Department of Human Genetics. She is also a member of the LBI - KU Leuven Brain Institute and participates in institutional councils. Senior Lecturer, Faculty of Medicine, KU Leuven Head, Laboratory for Complex Genetics Member, KU Leuven Brain Institute Her research focuses on polygenic risk scores (PRS) for disease prediction, genetic architecture of complex diseases, and multi-omics integration. Key projects include PRS implementation for breast cancer and Alzheimer's, AI-driven detection of bone necrosis risk in IBD, and genetic analysis of intestinal transplantation outcomes. Recent publications highlight her work at the intersection of genomics, artificial intelligence, and translational medicine, particularly for inflammatory bowel disease and neuroinflammatory disorders. Collaborative studies span European multicenter cohorts and cross-omics methodologies. She contributes to teaching courses on Molecular Genetics, Development and Reproduction, Genomic Medicine, and Biomedical Research Skills at KU Leuven.

• Biomechanics
• Sports Science
• Rehabilitation Science
• +۴ مورد دیگر

Benedicte Vanwanseele is a Professor at KU Leuven's Faculty of Movement and Rehabilitation Sciences, where she leads the Department of Human Movement Sciences. She serves as Head of the Biomechanics of Human Movement Research Group and Director of the LISS – KU Leuven Institute for Sports Sciences. Additionally, she is a member of the iSi Health Institute for Physics-based Modeling for In Silico Health. Her research focuses on human movement biomechanics with specific interests in: Achilles tendon mechanics and tendinopathy Gait analysis and movement disorders Sports biomechanics and injury prevention Rehabilitation engineering Machine learning applications in movement analysis Footwear biomechanics and human-equipment interaction Her recent publications demonstrate a strong focus on clinical biomechanics applications, particularly in Achilles tendinopathy, pediatric orthopedics (clubfoot), running mechanics, and geriatric movement assessment. Research trends show integration of computational modeling, machine learning, and advanced motion analysis techniques to address rehabilitation challenges. Professor Vanwanseele leads multiple research projects including investigations into Achilles tendon complexity, human-footwear interaction during gait, musculoskeletal modeling for ergonomics, and movement pattern analysis in osteoarthritis patients. She directs the LISS Institute and supervises doctoral research in movement sciences.

• Geographic Information Systems
• Remote Sensing
• Spatial Analysis
• +۵ مورد دیگر

Jos Van Orshoven is a full Professor at KU Leuven's Faculty of Bioscience Engineering within the Department of Earth and Environmental Sciences. He serves as Division Head of the Spatial Information Processing Division (SADL) and leads subdivisions for Ground for GIS and Earth Observation, while holding membership in Leuven One Health Institute and the Departmental Council for Earth and Environmental Sciences. His research spans Geographic Information Systems, remote sensing, and spatial analysis applied to environmental challenges. Key interests include climate-resilient land management, urban green space planning, forest dynamics under climate change, soil carbon monitoring, and socioeconomic disparities in environmental exposure. His work integrates drone and satellite technologies (Sentinel-2, VNIR/SWIR/LWIR) with spatial optimization for sustainable resource allocation. Recent publications reveal strong trends in climate adaptation (forest composition shifts, drought impacts on orchards), green infrastructure health benefits (3-30-300 rule evaluations), and precision environmental monitoring (radiocaesium transfer meta-analyses, soil carbon mapping). His team develops innovative methods like YOLOv8 tree detection for quantifying visible green space and spatial optimization for sediment loss minimization through afforestation. Radiocaesium soil-to-plant transfer meta-analysis (2025) Atlantic lowland forest climate vulnerability assessment (2025) Urban green space accessibility disparities research (2025) Agrovoltaics site suitability framework (2025) Soil carbon monitoring via Sentinel-2 (2024) He actively supervises research through multiple grants as promotor/co-promotor, including EU-funded projects on digital twins for sustainable cities (2024-2027), climate resilience networks (2023-2027), and drone remote sensing training (2022-2024). His teaching portfolio covers Geographic Information Systems, Geospatial Technologies, and Forest/Nature Landscape Planning across undergraduate and graduate bioscience engineering programs. His research group operates within KU Leuven's Spatial Information Processing Division, collaborating with international networks on the Omo-Turkana Basin management, Burundian land degradation monitoring, and Flemish urban green space initiatives. Current work focuses on scaling forest growth models for climate change predictions and optimizing spatial remediation strategies for radiologically contaminated soils.

Jef Peetersمشاهده پروفایل

استاد

• Robotic Disassembly
• Circular Economy
• Materials Recycling
• +۳ مورد دیگر

Prof. Jef Peeters is a faculty member at KU Leuven in the Institute for Sustainable Metals and Minerals , specializing in Manufacturing Processes and Systems . His research focuses on robotics, circular economy strategies, and sustainable materials recovery. Academic Rank: Professor Research Areas: Robotic disassembly, WEEE recycling, critical raw materials. Recent Publications highlight interdisciplinary work blending robotics, deep learning, and environmental engineering. Key topics include human-robot collaboration in remanufacturing, advanced sorting techniques for plastics and metals, and life cycle assessments of recycling strategies. Technical Expertise spans computational fluid dynamics (CFD) modeling, laser-induced breakdown spectroscopy (LIBS), and computer vision systems for defect detection and battery dismantling. His work addresses challenges in e-waste management and product reparability. Applications of his research include robotic grasping constraints, unsupervised learning for waste retrieval, and techno-economic assessments of sorting technologies. This reflects a strong commitment to advancing circular economy practices through automation.

• 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.

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +۷ مورد دیگر

Dr. Lode Jorissen is a Postdoctoral Assistant at Hasselt University's Faculty of Sciences, where he is affiliated with the Capacity group Computer Sciences within the Expertisecentrum voor Digitale Media (EDM) on Campus Diepenbeek. He maintains dual laboratory affiliations with both the Applied Computer Science Lab and the Digital Future Lab. His research spans multiple specialized areas of visual computing: Computer Graphics and Visual Computing Virtual Reality and Augmented Reality systems Image Processing and Computer Vision Novel-view synthesis techniques Projection-based augmented reality View-dependent lighting effects in XR 3D Modeling and Image-Based Rendering Dr. Jorissen manages an extensive research portfolio comprising 14 active projects with timelines extending from 2013 through 2029. Current major initiatives focus on AI-generated video detection, projection-based AR enhancement, and advanced lighting effects in XR environments, with practical applications across industrial manufacturing, construction, and immersive media production sectors. His funded research projects include: Training-free and model-agnostic approaches for generalizable and explainable AI-generated video detection (2025-2029) Enhancing Projection-based Augmented Reality (2025-2029) ALARMM_SBO: Accurate large-area Localization and spatial Alignment with Robust Markerless Methods (2025-2029) Expanding Capabilities of View-Dependent Lighting Effects in XR (2023-2027) DIGIBUILD: Digital Support for Construction Industrialization through Off-site Production (2024-2026) Dr. Jorissen currently supervises three PhD students as copromotor while teaching multiple advanced courses in image processing, computer graphics, and visual computing for both the 2024-2025 and 2025-2026 academic years. His laboratory work at the Applied Computer Science Lab focuses on developing practical visual computing solutions that bridge theoretical computer vision techniques with real-world industrial applications, particularly in manufacturing and construction environments.

• Computer Graphics
• Computer Vision
• Virtual Reality
• +۲ مورد دیگر

Dr. Jeroen PUT serves as a Researcher-expert and Research Manager within the Faculty of Sciences at Hasselt University. His primary academic appointment resides in the Capacity group Computer Sciences, with significant leadership roles in the Expertise Centre for Digital Media (EDM). He actively contributes to the Applied Computer Science Lab and Digital Future Lab, driving research in computational imaging and interactive systems. His research centers on Computer Graphics , Computer Vision , and Virtual Reality with industrial applications. Key focus areas include real-time rendering, deep learning for visual inspection, and VR-based assembly validation systems. This work bridges academic innovation with manufacturing and logistics sectors through projects like FARAD2SORT for automated product sorting. Current funding includes the Expertise Centre for Digital Media initiative (2024-2028) which he manages, providing resources for advanced computational infrastructure. His teaching portfolio demonstrates commitment to graduate education in visual computing disciplines despite no explicit student supervision details being published. Dr. PUT operates within the Applied Computer Science Lab ecosystem, which fosters collaboration between computer scientists, engineers, and industry partners. The lab maintains strong ties to manufacturing and logistics sectors for rapid prototyping and deployment of vision-based solutions in real-world production environments.

• Computer Vision
• Robotics
• Machine Learning
• +۳ مورد دیگر

Junhong CHEN serves as a Research Fellow at Hasselt University within the Faculty of Engineering Technology. His primary affiliations include the Capacity group Engineering Technology, the Engineering Materials and Applications research group, and the Digital Future Lab—where he contributes specialized expertise in computer vision and robotics. His research centers on solving critical challenges in robotic perception and manipulation through Deep Learning. Key focus areas include transparent object grasping—a complex industrial automation problem requiring novel approaches to visual processing and motor control. This work directly addresses limitations in current robotic systems handling glass, plastic, or other optically challenging materials. CHEN recently led the project 'Deep Learning based methods for transparent object grasping' (June 2023-March 2024), which developed advanced neural network frameworks for robotic vision systems. While no student supervision details are publicly listed, his affiliation with active research groups indicates ongoing mentorship within technical teams. His work demonstrates practical applications in logistics automation and smart manufacturing environments. As part of Hasselt University's Engineering Materials and Applications group and Digital Future Lab, CHEN operates at the intersection of material science and AI-driven engineering solutions—contributing to the institution's strategic focus on digital transformation in industrial processes.