جستجوی استاد راهنمای دانشگاهی

Jef Vandemeulebrouckeمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Jef Vandemeulebroucke is a researcher at the Department of Electronics and Informatics , Vrije Universiteit Brussel (VUB) , specializing in medical imaging, computer vision, and augmented reality applications in healthcare. His work bridges artificial intelligence with radiology and biomechanics , focusing on automated segmentation, predictive modeling, and real-time surgical navigation systems. Research interests include: Medical image analysis for disease prognosis (e.g., COVID-19 severity , neurosurgical drains ) Development of MedShapeNet , a 3D medical shape dataset for computer vision Augmented reality systems in orthopedic and neurosurgical interventions AI-driven fluorescence endoscopy and dynamic CT for joint kinematics Key trends in his 140+ publications emphasize deep learning , image registration , and 4D-CT applications . Supervised theses include brain age prediction and chest radiography automation. Active in 38 projects (e.g., AI-NIMO , TumorScope ), he collaborates with institutions like the Universitair Ziekenhuis Brussel (UZB) and FWO (Fund for Scientific Research-Flanders).

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).

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +۴ مورد دیگر

Nikolaos Tsiogkas is an Assistant Professor in the Declarative Languages and Artificial Intelligence (DTAI) group at KU Leuven's Faculty of Engineering Technology, Department of Computer Science. His research focuses on robotics, artificial intelligence, and autonomous systems, with particular emphasis on cognitive reasoning, knowledge representation, and sensor fusion for robotic navigation. Projects: Promotor of initiatives like 'Harnessing Robotics for Safe Agriculture' (2024-2028) and 'ROSANA: Robust Semantic Navigation in Orchards' (2022-2027); co-promotor in demining robotics and multi-arm manipulation research. Research: Combines symbolic AI with robotics, exploring knowledge graphs for explainable navigation, reinforcement learning frameworks, and computationally efficient free-space detection algorithms.

• Scan-to-BIM
• Geomatics
• Building Information Modeling
• +۷ مورد دیگر

Maarten Bassier is an Assistant Professor (tenure track) at KU Leuven, affiliated with the Department of Civil Engineering within the Faculty of Engineering Technology. He is based at the Geomatics unit operating at the Ghent and Aalst Campuses. His academic profile combines research, teaching, and institutional service, with significant contributions to the field of digital construction technologies. As senior academic staff, he serves on both the Council of the Faculty of Engineering Technology and the Civil Engineering Department Council, actively participating in institutional governance while maintaining a robust research program focused on Scan-to-BIM methodologies and geospatial applications in construction. Dr. Bassier's research centers on Scan-to-BIM methodologies, which involve converting 3D scans of existing buildings into Building Information Models. His work bridges geomatics, computer vision, and civil engineering, with applications in construction progress monitoring, infrastructure inspection, and heritage documentation. He applies machine learning techniques to automate aspects of the modeling process, particularly semantic segmentation of point clouds and integration of UAV (drone) data. His research increasingly incorporates deep learning approaches for object detection, segmentation, and completion in complex built environments, with practical applications spanning road construction, bridge inspections, and electrical substation modeling. His interdisciplinary approach connects civil engineering with computer science to solve practical construction challenges through digital innovation. Bassier's recent publication record demonstrates a strong focus on automating the Scan-to-BIM process through advanced computational techniques. His work spans multiple application domains while maintaining a consistent methodological thread of integrating sensing technologies with semantic understanding of construction environments. The trajectory of his research shows increasing sophistication in machine learning applications, moving from basic point cloud processing to complex semantic understanding and automated model generation. His publications appear in high-impact journals across civil engineering, remote sensing, and computer vision domains, reflecting the interdisciplinary nature of his work. SESAME - Semantic Segmentation of Electrical Substations and Derived Models for Engineering (2024-2026) - Promotor UAV-assisted bridge inspections (2022-2027) - Co-promotor XR-empowered dynamic reality modeling for AECO applications (2021-2026) - Co-promotor Digitization in road construction: automating as-built models (2020-2026) - Co-promotor SCAN-to-BIM Automation of as-built BIM production through digitization and machine learning (2020-2025) - Co-promotor As a member of the Division Digital and Sustainable Civil Engineering and the Subdivision Geomatics Ghent, Dr. Bassier contributes to KU Leuven's research ecosystem focused on digital transformation in civil engineering. His teaching portfolio includes courses on BIM, industrial measurements, Scan-to-BIM, 3D modeling, and geomatics, preparing the next generation of civil engineers for the digital construction landscape. His work represents the cutting edge of digital construction technologies, with practical applications that address real-world challenges in infrastructure development and maintenance.

Jan De Beenhouwerمشاهده پروفایل

استاد

• X-ray Imaging
• Computed Tomography
• Image Processing
• +۳ مورد دیگر

Prof. Jan De Beenhouwer is a faculty member at the University of Antwerp, affiliated with the Department of Physics and the imec Vision Lab. His research focuses on advanced computational imaging techniques, particularly in X-ray tomography, phase contrast imaging, and reconstruction algorithms for medical and industrial applications. His primary research interests include: Development of novel X-ray imaging methodologies like edge illumination phase contrast Advanced CT reconstruction algorithms for sparse-view and dynamic systems Integration of deep learning with tomographic reconstruction Industrial applications including defect detection and material characterization Biomedical imaging such as bone structure analysis and tissue modeling Analysis of recent publications (2024-2025) reveals strong emphasis on: Innovations in phase contrast imaging hardware and simulation tools Advanced reconstruction techniques for motion compensation and sparse data AI-powered approaches for industrial inspection and biomedical research Development of open-source tools (CAD-ASTRA) for the tomography community He leads research at imec Vision Lab, focusing on both fundamental imaging physics and practical applications. The lab collaborates extensively with industrial partners on non-destructive testing solutions.

• Machine Learning
• Data Mining
• Big Data
• +۴ مورد دیگر

Jesse Davis is a Professor at the Department of Computer Science , KU Leuven , actively contributing to the Machine Learning group and the Sports Analytics Lab . He is part of the Faculty of Engineering Science and the Leuven.AI Institute . Ph.D. in Computer Sciences from University of Wisconsin-Madison (2007) M.S. in Computer Sciences from University of Wisconsin-Madison (2005) B.A. in Computer Science from Williams College (2002) His research focuses on machine learning, data mining, big data analytics, and sports analytics, with significant work in: Transfer learning and Markov logic networks Anomaly detection and semi-supervised learning Medical NLP and biomechanical data analysis Soccer performance metrics and tactical analysis His recent work explores spatio-temporal data analysis in sports and explainable AI for medical applications, with collaborations spanning finance, healthcare, and semiconductor manufacturing. Notable scientific awards include: Best Paper Award (Applied Data Science Track) at KDD 2019 Best Technical Paper Award at Intelligence Analysis Workshop He advises numerous PhD and Master's students in areas like: Football analytics Tree ensemble compression Medical question-answering systems Biomechanical load prediction His lab develops tools such as: GSSL for Markov network structure learning TODTLER for transfer learning Alchemy system for Markov logic networks

Herman Bruyninckxمشاهده پروفایل

استاد

• Robotics
• Mechatronics
• Bayesian Sensor Processing
• +۱۰ مورد دیگر

Herman Bruyninckx is a Professor at the Faculty of Engineering Sciences , KU Leuven , where he also serves as Vice-Chair of the Department of Mechanical Engineering and head of the Robotics, Automation and Mechatronics (RAM) subdivision. His research focuses on integrating formally represented domain knowledge into robotic systems for real-time, self-explanatory, and certifiable control. He advocates for open standards and software engineering practices in robotics, with a career-long emphasis on knowledge-driven robotic systems over data-driven approaches.

Chris Develderمشاهده پروفایل

دانشیار

• Natural language processing
• Information extraction
• Smart grid
• +۲ مورد دیگر

Chris Develder is an Associate Professor with the research group IDLab in the Department of Information Technology (INTEC) at Ghent University - imec, Ghent, Belgium. He received his MSc degree in computer science engineering and PhD in electrical engineering from Ghent University in Jul. 1999 and Dec. 2003 respectively (as a fellow of FWO). He has held research visitor positions at UC Davis, CA, USA (Jul.-Oct. 2007) and at Columbia University, NY, USA (Jan. 2013 - Jun. 2015). Prof. Develder leads two research teams within the Internet Technology and Data Science Lab (IDLab): one focused on converting text to knowledge (NLP, primarily information extraction using machine learning), and another on data analytics and machine learning for smart grids. His Text-to-Knowledge (T2K) research group has a strong track record in information extraction across various domains including news, human resources, and biomedical applications, as well as text classification tasks such as sentiment analysis. More recently, the group has expanded into conversational agents and generative models for educational applications. With his team, Prof. Develder has published over 200 papers in international journals and conferences including EMNLP, CoNLL, EACL, ACL, ECIR, CIKM, WSDM, WWW, and NIPS. His recent publications demonstrate a growing focus on practical applications of NLP in healthcare (personality style recognition from speech, biomedical adverse drug event extraction), education (question generation, gap-filling exercises), and labor market analysis (career path prediction, skill extraction). His work bridges theoretical advances in machine learning with real-world applications across multiple domains. Prof. Develder actively supervises PhD students and has co-supervised numerous successful doctorates, including Maarten De Raedt (2024), Semere Kiros Bitew (2024), Yiwei Jiang (2024), Amir Hadifar (2023), and Klim Zaporojets (2022). His former students have gone on to work at organizations including EarlyTracks, Zoom, Nokia Bell Labs, Clarivate, and various academic institutions.

• Surgical Robotics
• Medical Device Design
• Haptics
• +۵ مورد دیگر

Emmanuel Vander Poorten is an Associate Professor at the Faculty of Engineering Technology, KU Leuven, specializing in surgical robotics and medical device design. He leads the Robotics, Automation and Mechatronics (RAM) research group and serves as head of the RAS subdivision. Research Interests: Surgical Robotics, Medical Device Design, Haptics, Teleoperation, Virtual Reality Training Key Projects: MIRACLE, RIVUS, AR-Spine, ARTISTE, SafeRPlan Institute Memberships: Leuven Centre for Affordable Health Technology, DigiSoc – KU Leuven Digital Society Institute, iSi Health, Leuven.AM, Leuven.IRD His work focuses on integrating robotic systems with advanced sensing technologies for minimally invasive procedures in spine surgery, vascular interventions, and fetal operations. Current research emphasizes autonomous systems, augmented reality guidance, and reinforcement learning for surgical safety. Emmanuel contributes to teaching in robotics and drive systems at KU Leuven, including courses on autonomous vehicles, machine design, and mechatronics.

Peter Schelkensمشاهده پروفایل

استاد

• Holography
• Image and Video Coding
• Digital Signal Processing
• +۶ مورد دیگر

Peter Schelkens is a Professor at the Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB). He holds additional roles including Department Chair and Head of Research Group, focusing on technology transfer and innovation in electronics and informatics. His research spans fundamental signal processing, holography, medical imaging, and standardized multimedia coding frameworks like JPEG Pleno. Education and Academic Background: Postdoctoral Fellowship (2002–2011) funded by the Research Foundation – Flanders (FWO). His work bridges theoretical advancements with applied domains such as eHealth, bio-informatics, and cultural heritage preservation. Research Interests: Holography and digital signal processing dominate his focus, including holographic compression, Fourier-based techniques, and light field imaging. Strategic projects involve error-resilient coding, computer architectures (e.g., GPU/GPGPU), and quality assessment metrics. His applied research addresses medical imaging, 3D media broadcasting, and immersive technologies. Article Trends: Recent work emphasizes holographic video codecs (e.g., INTERFERE), high-throughput hologram generation, and JPEG Pleno standardization. He explores computational methods for 3D metrology and deep learning applications in hologram optimization. Scientific Awards: Gauss Award (2000), ERC Consolidator Grant (2014), Best Associate Editor Award (2014), and multiple industry accolades. Grants/Projects: Leads major initiatives like the SRP-Onderzoekszwaartepunt LSDS (2022–2027) and GEAR (2021–2025), focusing on health tech and learning-based systems. Labs/Teams: Active in ETRO, the interdisciplinary research group at VUB, collaborating globally on holography, multimedia standards, and biomedical imaging systems.

Joaquim Sanctorumمشاهده پروفایل

پژوهشگر ارشد

• Medical Imaging
• Computational Imaging
• Biomedical Engineering
• +۳ مورد دیگر

Dr. Joaquim Sanctorum is a Postdoctoral Researcher at the University of Antwerp specializing in advanced X-ray computed tomography (CT) and image reconstruction methodologies. His work bridges medical imaging, computational engineering, and biomedical applications with a focus on high-speed, high-resolution systems and practical implementation using the ASTRA toolbox. His research expertise spans Medical Imaging , Computational Tomography , and Biomedical Engineering , with emphasis on cone-beam CT reconstruction, motion correction, distortion compensation, and system calibration. Key contributions include neural network-based deformation prediction for additive manufacturing, phase-contrast imaging techniques, and universal motion models for continuous acquisition scenarios. Analysis of his 2019-2025 publications reveals three dominant trends: (1) Algorithmic innovations for real-time CT processing in industrial contexts (e.g., selective laser melting), (2) Hardware-aware solutions for geometric calibration and distortion correction in modular X-ray systems, and (3) Expansion of imaging capabilities through tiled acquisition and extended volume reconstruction. His work consistently addresses practical challenges in biomechanics, materials science, and clinical radiology.

Nicholas Franckenمشاهده پروفایل

پژوهشگر ارشد

• X-ray Imaging
• Phase Contrast Imaging
• Computational Imaging
• +۳ مورد دیگر

Dr. Nicholas Francken serves as a Postdoctoral Researcher at the Imec-Vision Lab, University of Antwerp, Belgium, specializing in advanced x-ray imaging techniques with a focus on inline phase contrast systems using edge illumination setups. His interdisciplinary background bridges astrophysics, data science, and computational imaging. His educational foundation includes: Master of Science in Astrohysics & Astronomy (2018) from the Catholic University of Leuven Completion of the Lcie Entrepreneurship Academy (2018) Francken's research centers on developing high-performance computational frameworks for x-ray imaging, leveraging GPU-accelerated ray tracing to simulate complex optical phenomena. His work addresses critical challenges in phase contrast imaging, with applications spanning materials science and non-destructive testing. The integration of physics-based modeling with cutting-edge computing infrastructure defines his methodological approach. His 2022 publication demonstrates expertise in translating optical theory into practical simulation tools using NVIDIA's OptiX engine, revealing trends toward real-time computational imaging solutions. This work contributes to evolving subfields including GPU-accelerated physics simulations and advanced tomography techniques. Within the Imec-Vision Lab ecosystem, Francken actively participates in research collaborations while supporting academic instruction through exercise sessions for physics and field theory courses, demonstrating commitment to both research innovation and educational development.

Wilfried Philipsمشاهده پروفایل

استاد

• Computer Vision
• Real-time Computer Vision
• Video Quality Improvement
• +۴ مورد دیگر

Wilfried Philips is a senior full professor at Ghent University and scientific lead of imec's Center of Excellence on Image Processing and Sensor Fusion. He leads the Image Processing and Interpretation (IPI) research group at imec-UGent and Ghent University's valorization consortium iKnow, which has created 9 spin-off companies including Senso2Me (IoT services for elderly care). His research focuses on real-time computer vision and video quality improvement for industrial applications, with key domains spanning automotive sensing, industrial inspection, machine learning, and video surveillance. The IPI group's work has directly generated three commercial spin-offs through applied research in these areas. Dr. Philips' publication portfolio demonstrates significant impact across remote sensing, medical imaging, and biological computer vision, with multiple highly-cited papers including a 2014 Best Paper Award-winning study on hyperspectral-LiDAR fusion. His honors include: Best Paper Award, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2014) Senior Member, IEEE Fellow, Belgian-American Educational Foundation As a translational research leader, he has successfully bridged academic innovation and industrial implementation through multiple technology spin-offs and industry partnerships.

• Computer Graphics
• Computer Vision
• Virtual Reality
• +۴ مورد دیگر

Prof. Dr. Fabian DI FIORE is a Lecturer and Research Coordinator at the Department of Computer Science, Faculty of Sciences, Hasselt University. He is affiliated with the Expertise Center for Digital Media (EDM) and leads research in Computer Graphics, Virtual Reality, and Extended Reality (XR). His roles include coordinating research projects and teaching courses such as Operating Systems, Computer Animation & Simulation, and Computer Graphics & Visual Computing. His research focuses on modeling and simulation, computer vision, and digital media applications. Notable projects include XR innovations for manufacturing, digital support for industrial processes, and collaborative virtual environments for education. He coordinates 16 active research projects, emphasizing XR infrastructure and applied technologies in industry and healthcare. Prof. DI FIORE supervises PhD candidates in Extended Reality applications, such as Psychomotor Task Assistance and Training using XR. He is involved in education initiatives like the International interdisciplinary project and the International School program. His work bridges academic research and practical applications, with a focus on innovation in digital media and educational technology. His teaching responsibilities include coordinating courses on operating systems, computer animation, and project management. He is a co-owner of key training components such as Computer Architecture and International interdisciplinary projects, reflecting his dual role in education and research leadership.

Gilles Perrouinمشاهده پروفایل

استاد پژوهش

• Software Engineering
• Testing
• Artificial Intelligence
• +۳ مورد دیگر

Gilles Perrouin is a Research Professor in the Faculty of Computer Science at the University of Namur, affiliated with the Research Center on Information Systems Engineering and the Namur Digital Institute. His expertise spans Software Engineering, Testing, Artificial Intelligence, and Machine Learning, with a focus on software product lines, configuration management, and automated testing techniques. He leads projects such as SQUAL.AI (Software Quality through Artificial Intelligence) and SmartTune (Hyper-parameter Optimization for Deep Learning). Perrouin has received awards including the Distinguished Reviewer Award (2023 and 2019) and the VAMOS 2024 ten-year Most Influential Paper Award. He actively participates in organizing conferences like the Belgium-Netherlands Software Evolution Workshop and contributes to initiatives promoting diversity in science, such as Women and Girls in Science events. His research involves advancing testing methodologies for complex systems, exploring energy-efficient neural architectures, and addressing fairness in machine learning. Collaborations span international institutions, reflecting his global impact in software engineering and AI.