Find Academic Supervisors

Maurice van Keulen is an Associate Professor affiliated with the University of Twente's research institutes including Datamanagement & Biometrics, Digital Society Institute, and TechMed Centre. His multidisciplinary work bridges computer science, healthcare, and social systems. Research Focus: Van Keulen specializes in artificial intelligence applications with emphasis on: Data management (quality, integration, probabilistic databases) Explainable AI and interpretable machine learning models Healthcare informatics (cancer prediction, medical imaging, outcome analysis) Natural language processing and social media analytics His recent work explores dynamic sparse training, meta-learning for data imputation, and ethical AI frameworks. Publication Trends: Recent articles (2023-2025) show strong focus on: Interpretable AI methods in healthcare diagnostics Robust machine learning under data corruption Meta-learning approaches for data preprocessing 3D medical imaging and reconstruction techniques Awards: Beste paper award (2018) for work on probabilistic data conditioning Supervision & Activities: Has supervised 14 research projects and serves on executive boards including EDBT (Extending DataBase Technology) and IFIP WG 2.6. Leads research on ethical dimensions of AI systems.

• Artificial Intelligence
• Data Mining
• Process Mining
• +7 more

Dr. Sanne Frequin is an Assistant Professor in Art History at Utrecht University within the Faculty of Humanities. Her work bridges traditional art historical research with digital methodologies. Academic coordinator of the Master’s program in Art History Board member of the Utrecht University Teaching Academy (T@UU) Coordinator of the Digital ArtLab Her research focuses on digital and 3D reconstruction of medieval and early modern art , particularly lost or damaged artefacts. Key projects include: The 3D reconstruction of Guy of Avesnes’ tomb Digital analysis of the Lindau Master’s panel painting Development of the #MedievalMe serious game She actively engages in science communication through: Radio appearances (NPO Radio 1’s De Wild in de Middag , OVT ) Collaborations with heritage institutions (Museum Catharijneconvent, KB National Library) Public projects like the Medieval Meme Machine

• Digital Art History
• 3D Reconstruction
• Technical Art History
• +5 more

Ruisheng Su is a Researcher at Erasmus MC's Department of Radiology & Nuclear Medicine . His work focuses on Medical Imaging , Artificial Intelligence , and Vascular Neurology , with a strong emphasis on Stroke Treatment and Cerebral Infarction research. Research Trends: His recent publications highlight the integration of Deep Learning and Neural Networks in endovascular therapy prediction and scoring systems. He explores Image Registration , Perfusion Imaging , and Vessel Segmentation to advance Cerebral Vascular Imaging and Stroke Intervention techniques. Key Contributions: Su has developed tools like CVFSNet for automated mTICI scoring, perfDSA for perfusion imaging in angiography, and segmentation-assisted methods for vessel centerline extraction, addressing critical gaps in Cerebral Infarction and Blood Clot Lysis treatment.

• Neuroscience
• Medical Imaging
• Artificial Intelligence
• +4 more

Alvaro Ivan Lau Sarmiento is a Lecturer at the Geosciences school of Utrecht University , affiliated with the Human Geography and Spatial Planning department. He actively contributes to the Laboratory of Geo-Information Science and Remote Sensing at Wageningen University & Research through collaborative projects. Education : Master in Geo-Information Science and Remote Sensing from Wageningen University Expertise : Terrestrial Laser Scanning (TLS), 3D Forest Modeling, Tropical Forest Monitoring His research focuses on Remote Sensing applications in Forest Ecology , particularly using Terrestrial LiDAR to analyze Tree Biomass Estimation and Crown Shyness phenomena. He pioneered 3D surface complementarity metrics adapted from molecular biology to quantify crown interactions in tropical forests. Recent work trends show strong emphasis on 3D Point Clouds for ecological analysis and Architecture-Based Modeling of tropical trees. His studies bridge Remote Sensing with Forest Dynamics through innovative computational methods. Alvaro coordinates and teaches courses like GRS10306 while supervising MSc Theses and Internships . He actively collaborates with Wageningen University researchers, startups, and companies in 3D modeling domains. As contact person for Terrestrial Laser Scanning Research at Wageningen University & Research, he has collected field data in tropical regions and Europe, focusing on Greenhouse Gas Emissions Monitoring in forests through his 3DForMod project.

• Remote Sensing
• Geographic Information Science
• LIDAR Point Clouds and Reconstruction
• +3 more

Konstantin Klein is a Visiting Professor at the University of Amsterdam 's Faculty of Humanities, specializing in History, European Studies, and Religious Studies. His research focuses on Late Antiquity, particularly the intersection of epigraphy, religious history, and urban development in Constantinople and Jerusalem. Research interests include: Epigraphic analysis of ancient Semitic inscriptions Digital humanities applications in text restoration Urban spatial organization in religious contexts Material culture of Late Antique cities Gender roles in epigraphic patronage Recent publications demonstrate expertise in: Machine learning for damaged inscription recovery Comparative urbanism of Byzantine capitals Analysis of Palmyrene funerary art Epigraphic patterns in Christian holy sites Interpretation of Late Antique decay processes Gender-regulated epigraphic expressions

• Late Antiquity
• Epigraphy
• Religious History
• +3 more

Srirang Manohar is a Full Professor at the TechMed Centre , University of Twente, specializing in Multi-Modality Medical Imaging . His work focuses on photoacoustic imaging, ultrasound, and tomography, with clinical applications in breast cancer, prostate cancer, and thyroid disorders.

• Photoacoustic Imaging
• Ultrasound
• Tomography
• +3 more

Bert de Vries is a Professor at the Signal Processing Systems Group at Eindhoven University of Technology (TU/e), where he has been employed since January 2012. He maintains a dual career, also working at GN Hearing in the hearing aids industry since April 1999, where he holds both research and managerial roles. His academic journey began at TU/e, where he earned his MSc in Electrical Engineering in 1986, followed by a PhD from the University of Florida in 1991. Between 1992 and 1999, he worked at Sarnoff Research Center in Princeton, NJ, contributing to diverse signal and image processing projects. Professor de Vries's research centers on Bayesian Machine Learning, with particular focus on the Free Energy Principle and its applications to engineering problems. His work bridges theoretical neuroscience with practical signal processing systems, especially in biomedical applications. He directs the BIASlab research team at TU/e, which develops probabilistic programming tools including RxInfer.jl, ForneyLab.jl, GraphPPL.jl, ReactiveMP.jl, and Rocket.jl. His research spans active inference, variational message passing, probabilistic programming, and Bayesian neural networks, with applications ranging from hearing aids to multi-agent systems. Analysis of his recent publications reveals a strong trend toward practical implementations of Bayesian inference frameworks, particularly through Julia-based probabilistic programming tools. His work shows increasing focus on active inference applications, message passing algorithms, and the intersection of Riemannian geometry with probabilistic modeling. The research demonstrates consistent progression from theoretical foundations toward real-world engineering applications, particularly in biomedical signal processing and autonomous systems. Professor de Vries teaches a graduate-level course on Bayesian Machine Learning at TU/e and actively contributes to open-source software development through his GitHub profile (bertdv), with recent activity as recent as August 2025. His research team has developed several influential probabilistic programming libraries that have gained significant attention in the machine learning community. The BIASlab research group continues to advance the state of the art in Bayesian inference methods with applications in hearing technology, robotics, and signal processing.

• Bayesian Machine Learning
• Signal Processing
• Biomedical Applications
• +3 more

Paul Tiesinga is Professor of Neuroinformatics at Radboud University's Faculty of Science, where he directs the Neuroinformatics group at the Donders Centre for Neuroscience. His research focuses on understanding information processing in the brain, particularly the role of oscillations ('brain waves') in cognitive functions and disease mechanisms. He combines computational modeling with experimental approaches including optogenetics to investigate cortical dynamics. As Director of Education for the Institute for Mathematics, Physics and Astronomy, he oversees academic programs while maintaining active research in: Computational modeling of cortical circuits Oscillation mechanisms in neural coding Data sharing policies for neuroscience Information transfer between brain areas His recent publications reflect advances in neurotechnology development, thalamocortical connectivity analysis, and novel methodologies for neural data interpretation.

• Computational Neuroscience
• Neurophysics
• Brain Oscillations
• +2 more

Marcel Rost is a Researcher at the Leiden Institute of Physics (LION) , Leiden University, focusing on fundamental surface science and electrochemical processes at atomic scales. His work bridges thin film technology , electrocatalysis , and scanning probe microscopy (SPM) innovations. Developed high-speed EC-STM for real-time electrochemical imaging Explores platinum electrode degradation mechanisms in energy applications Pioneered Subsurface-AFM for nanoscale friction-based imaging His research combines thermodynamic modeling , kinetic Monte Carlo simulations , and custom SPM systems to address unresolved questions in surface stress, island nucleation, and additive effects in copper electrodeposition . Collaborations with semiconductor industries and institutions like TU Wien and Forschungszentrum Juelich highlight his impact. Scientific awards include the Vidi Subsidy (2009) and TOP Subsidy (2018) . His lab's 15+ recent publications (2017–2024) cover topics such as platinum roughening , heterodyne force microscopy , and additive-driven deposition , with implications for catalysis , microelectronics , and material synthesis .

• Surface Science
• Electrocatalysis
• Electrochemistry
• +4 more

Pieter Kruizinga is an Assistant Professor at Erasmus MC specializing in Neurosciences . His work bridges Ultrasonography , Doppler Flowmetry , and Medical Imaging , focusing on advanced neuroimaging techniques. Current affiliations include collaborations with Erasmus MC's Neurosciences department and interdisciplinary teams in biomedical engineering. Institution: Erasmus MC Department: Neurosciences Research interests revolve around Brain Imaging , Functional Magnetic Resonance Imaging , and Tumor Vascularization . His projects aim to improve diagnostic and therapeutic approaches for neurological conditions, particularly gliomas, using Functional Ultrasound (fUS) and MRI technologies. Trends in research outputs highlight the integration of Doppler Ultrasound with MRI for vascular analysis, development of 3D modeling for blood flow dynamics, and creation of patient-specific vascular phantoms to enhance imaging accuracy. His work also explores hemodynamic monitoring in freely moving subjects via skull implants. Advising and Grants include supervision of interdisciplinary research projects and contributions to collaborative grants in neuroimaging and biomedical engineering. Specific details about individual grants are not provided in the text. Labs and Teams are not explicitly mentioned, but his network involves collaborations with institutions across the globe, focusing on neuro-oncology and biomedical imaging.

• Neurosciences
• Ultrasonography
• Doppler Flowmetry
• +5 more

Hans-Martin Schwab is an Assistant Professor at the Biomedical Engineering Department of Eindhoven University of Technology (TU/e), affiliated with the Eindhoven MedTech Innovation Center and the Photoacoustics and Ultrasound Laboratory. His research focuses on advanced ultrasound and photoacoustic imaging techniques, including multi-perspective imaging, model-based artifact reduction, and deep learning-assisted signal processing. He contributes to UN Sustainable Development Goals through innovations in medical imaging technologies. His expertise spans transducer engineering, circumferential strain imaging, and ultrasound reconstruction methods. Recent collaborations involve international teams working on applications like vascular strain analysis and tissue regeneration using ultrasound phased arrays. Over 28 publications since 2020 highlight contributions to photoacoustic imaging systems, numerical simulations, and clinical ultrasound advancements. Prof. Schwab teaches courses on ultrasound imaging, clinical measurements, and blood oxygenation imaging. He has supervised numerous projects, including DBL initiatives on light/sound integration for medical imaging. His work emphasizes translating theoretical models into practical clinical tools, with a focus on improving diagnostic accuracy and patient outcomes.

• Biomedical Engineering
• Ultrasound Imaging
• Photoacoustics
• +3 more

Akshay Kumar Burusa is a Researcher in the Department of Agricultural Biosystems Engineering at Wageningen University & Research . His work focuses on integrating robotics, computer vision, and deep learning for agricultural automation, particularly in greenhouse environments. Research Interests : Robotics and machine learning for agro-food systems 3D pose estimation and keypoint detection in plants Real-time object tracking in cluttered environments Next-best-view algorithms for plant reconstruction Biomechanical modeling for robotic grasping Recent Publications highlight advancements in agricultural robotics, including multi-view active vision for plant node detection, deep learning-based grasping of deformable objects, and self-supervised 3D reconstruction algorithms. His work emphasizes practical applications in tomato greenhouses and poultry processing automation. Collaborations : Collaborates with experts like Eldert van Henten and Gert Kootstra on projects involving robotic perception and tracking. His research contributes to improving efficiency in agro-food robotics through advanced vision systems and algorithm design.

• Robotics
• Computer Vision
• Deep Learning
• +7 more

Brend Jonker is a researcher at Erasmus MC specializing in Oral and Maxillofacial Surgery. His work bridges clinical practice with biomedical research, focusing on improving outcomes for oral cancer patients and advancing prosthetic solutions for craniofacial reconstruction. Primary Affiliation: Erasmus MC, Oral and Maxillofacial Surgery Research Interests span oral cancer survivorship, radiation therapy optimization, and innovative biomaterial applications. His work includes: Evaluating long-term quality of life post-microvascular tongue reconstruction Comparing bone graft materials for maxillary sinus augmentation Developing predictive assays for oral mucosal radiation toxicity Creating 3D-printed temporomandibular joint prostheses with graded material properties Scientific Contributions include clinical trials and translational research in: Postoperative radiotherapy for high-risk oral cavity cancer Biomechanical modeling of joint replacements Retrospective cohort analyses of tumor control

• Oral Cancer
• Implant Placement
• Radiation Therapy
• +3 more

Dr. Francisco Martinez Garcia is a veterinarian and researcher specializing in Laboratory Animal Science at the University of Groningen. His research focuses on hydrogel mechanics , extracellular matrix (ECM) engineering , and cell-matrix interactions for tissue regeneration applications. Key Research Themes : Biomechanics of biomaterials, decellularization techniques, 3D cell culture systems, and regenerative medicine. Technical Expertise : Hydrogel characterization, viscoelastic properties analysis, vascular scaffold design, and proteomic profiling. Publications highlight his work on: Organ-derived ECM hydrogels for disease modeling Mechanical regulation of stromal cell behavior Decellularized vascular scaffolds for tissue engineering Immunoisolation constructs for cell therapy Collaborations include researchers like Dr. J.K. Burgess and Prof. M.C. Harmsen, with interdisciplinary applications in skin regeneration, cardiovascular repair, and cancer biology. No scientific awards or student advising information were explicitly mentioned in the provided texts.

• Veterinary Sciences
• Tissue Engineering
• Biomechanics
• +5 more

Ihor Smal is an Assistant Professor at the Department of Biology, Faculty of Science, Utrecht University. He has held previous positions at Erasmus MC (2009-2018) and TU Delft (2019-2020). His research bridges statistical image processing, smart microscopy, and explainable AI for biological motion analysis, with applications in automated real-time imaging systems. Education: M.Sc. in Physics and Electrical Engineering, Ivan Franko National University of Lviv (1999, cum laude) Professional Doctorate in Engineering (PDEng), Eindhoven University of Technology (2005) PhD in Biomedical Imaging, Erasmus University/MC (2009) His work focuses on developing AI-driven solutions for motion registration, particle tracking, and image understanding in biological systems. He leads the NWO IMAGINE! program's Tech Work Package 2, aiming to automate imaging experiments using explainable AI. The 15 most recent publications highlight his contributions to deep learning for CT segmentation, particle tracking, diffusive state modeling, and real-time imaging optimization. Key subfields include neural networks, biomedical signal processing, and automated microscopy. Scientific Awards: VENI grant Erasmus MC Fellowship NWO BBoL grant Students: Vincent Hellebrekers Daan te Rietmole His lab at Utrecht University, accessible via www.smal.ws, collaborates with institutions like Erasmus MC and TU Delft, leveraging facilities such as the Utrecht Biology Imaging Center.

• Image Analysis
• Smart Microscopy
• Artificial Intelligence
• +7 more