Aisha Ameen is a Researcher in the Department of Veterinary and Animal Sciences (Pathobiological Sciences) at the University of Copenhagen's Faculty of Health and Medical Sciences, holding dual appointments as Research Assistant and Guest Researcher. Her research centers on Alzheimer's disease mechanisms with emphasis on astrocyte metabolism, glucose/glutamate dynamics, and short/medium-chain fatty acid roles. She employs functional metabolic mapping, dMRI, immunohistochemistry, and hiPSC models to investigate neurodegenerative processes at cellular and systemic levels. Analysis of her 2022-2025 publications reveals consistent focus on metabolic dysregulation in Alzheimer's pathology, particularly astrocyte energy substrate competition and fatty acid interventions. Her work bridges neuroscience, metabolism, and translational disease modeling with significant citation impact and media attention.
Christian Rønn Hansen is an Associate Professor at the Department of Clinical Research, University of Southern Denmark , specializing in radiation therapy and oncology. His work spans head and neck cancer, prostate cancer, and glioma treatment planning, with a focus on advanced radiation techniques like VMAT, IMRT, and hypofractionation. Academic Affiliation : Department of Clinical Research, University of Southern Denmark Research Collaborations : KI (Karolinska Institute), OUH (Odense University Hospital), Danish Head and Neck Cancer Group (DAHANCA) Research Interests : Christian's research integrates artificial intelligence with magnetic resonance imaging for treatment adaptation, clinical trial quality assurance for radiation therapy, and pattern of failure analysis in head and neck cancer. His work also addresses thromboembolic risk in glioma patients and proton therapy applications for grade 1–3 gliomas. Scientific Contributions : His recent publications include systematic reviews on loco-regional failure patterns in head and neck cancer (2025), national data solutions for radiation oncology (2025), and AI-driven prostate volume analysis in hypo-fractionated radiotherapy (2025). He contributed to the 2023 ACTA ONCOLOGICA AWARD-winning work and leads discussions on international radiotherapy quality assurance standards. Scientific Awards : ACTA ONCOLOGICA AWARD (2023)
Faisal Mahmood is a Professor at the Department of Clinical Research, University of Southern Denmark (SDU), with dual affiliations at Odense University Hospital (OUH). He is a key member of the Research Unit of Oncology and the AgeCare - Academy of Geriatric Cancer Research in Odense, where he leads advanced research in imaging biomarkers for radiotherapy response. His work bridges clinical oncology and medical physics, with a focus on improving cancer treatment through innovative imaging techniques. Research Interests: Dr. Mahmood's research centers on imaging biomarkers of response to radiotherapy , with expertise in radiation therapy , medical image processing , and diffusion MRI . His work explores tumor microstructure using time-dependent diffusion imaging and MRI-Linac systems, with applications in glioblastoma and pancreatic cancer. He is actively involved in developing low-dose, adaptive radiotherapy protocols to enhance treatment precision. The recent trend in his publications shows a strong focus on adaptive radiotherapy , quantitative MRI , and biologically guided treatment . His work integrates engineering principles with clinical oncology, emphasizing reproducibility and feasibility in clinical settings. Topics such as automatic beam gating, diffusion coefficient discrepancies across scanners, and histological validation of imaging biomarkers reflect his translational research approach. Scientific Awards and Recognition: Research supported by Knæk Cancer foundation Advising and Grants: Dr. Mahmood has supervised at least 3 academic works, including PhD-level research. His projects are supported by institutional and external funding, notably from cancer research foundations. He actively collaborates with multidisciplinary teams across Denmark and internationally, contributing to both national and global oncology research initiatives. Labs and Research Teams: He is affiliated with the Research Unit of Oncology and the AgeCare - Academy of Geriatric Cancer Research at OUH, where he contributes to cutting-edge research in geriatric oncology and advanced radiotherapy. His team integrates clinical data, imaging physics, and machine learning to develop personalized treatment strategies for cancer patients.
Kars van der Weijden is an academic researcher affiliated with the Faculty of Medical Sciences at the University of Groningen , working within the Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE) department. Their primary research focuses on neuroimaging methodologies, particularly PET and MRI techniques, applied to neurological disorders such as multiple sclerosis and brain tumors. Key areas include myelin imaging, diffusion-weighted imaging validation, and artifact reduction in clinical MRI. They contribute to the UN Sustainable Development Goals, specifically targeting SDGs related to good health and well-being. Research highlights include developing non-invasive imaging tools like [11C]MeDAS PET for myelin loss assessment and exploring the future of PET imaging in characterizing white matter lesions. Their work bridges translational research between animal models and clinical applications. Recent activities include reviewing cognitive impairments post-radiotherapy and advancing open science initiatives through memberships in Open Science Initiative for Perfusion Imaging (OSIPI) and GliMR . Awards include the 2024 MS Research Stichting and Research School of Behavioural and Cognitive Neurosciences recognition.
Sune Darkner is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen, specializing in the Image Analysis, Computational Modelling, and Geometry research section. His work focuses on medical image processing with particular emphasis on neuro-imaging data including MRI and PET scans. His primary research interests include Image Registration, Segmentation and Classification of Medical Image Data , with a specific focus on estimation of image similarity as his main research interest. Darkner strongly believes that the implementation of image processing algorithms should be thoroughly tested and reflect the theoretical properties as accurately as possible. His work primarily centers on neuro-imaging data such as MRI and PET. His recent publications (2024-2025) reveal a strong focus on medical image analysis, with particular emphasis on tumor volume delineation, deformable image registration with physics constraints, and applications of deep learning in medical imaging. His work spans both theoretical foundations of image processing and practical clinical applications. Darkner previously held a Post Doc position at the Technical University of Denmark from February 2009 to January 2010, demonstrating his longstanding engagement with image analysis research in the Danish academic community.
Mojtaba Zarei is a researcher at the Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, with additional affiliations at Odense University Hospital (OUH) and Karolinska Institutet (KI). His primary research unit is the Neurology Research Unit in Odense, focusing on advanced neuroimaging techniques and their applications in neurological and sleep disorders. Dr. Zarei's research spans multiple domains within neuroscience, with particular expertise in Positron Emission Tomography (PET), Diffusion Tensor Imaging (DTI), and cognitive function assessment. His work frequently addresses Alzheimer's Disease, Parkinson's Disease, and insomnia disorders, utilizing both clinical and computational approaches. His fingerprint analysis shows strong activity in neuroscience (100% for PET), diffusion tensor imaging (66%), cognitive function (45%), and Alzheimer's Disease (40%). His recent publications reveal a clear trajectory toward integrating multimodal imaging techniques with machine learning approaches for improved diagnosis and understanding of neurological conditions. The work on OPETIA (Odense-Oxford PET Image Analysis) demonstrates his contribution to developing standardized tools for neuroimaging analysis. His research increasingly bridges computational methods with clinical neuroscience, as evidenced by his work on image stitching algorithms and machine learning applications for insomnia classification. Dr. Zarei actively collaborates with researchers across multiple institutions, with notable external collaborations visible on the international network map. His work has been mentioned by peer review sites, picked up by news outlets, and shared across social media platforms, indicating growing impact in his field. Within his research unit of Neurology in Odense, Dr. Zarei appears to be part of a multidisciplinary team working at the intersection of clinical neurology, advanced imaging, and computational analysis, contributing to both methodological development and clinical applications of neuroimaging techniques.
Marco Pizzolato is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing with a focus on Magnetic Resonance Imaging (MRI), particularly diffusion MRI and biophysical modeling. He is also affiliated with the inter-departmental Microstructure & Plasticity (MAP) research group and has held visiting positions at the University of Verona, EPFL, and DRCMR. His educational background includes a PhD in Signal and Image Processing from INRIA Sophia Antipolis, a Master’s in Bioengineering from the University of Padua, and a Bachelor’s in Biomedical Engineering from the same institution. He previously served as an Assistant Professor at DTU and was a postdoctoral researcher under the Marie Curie COFUND Eurotech programme. Dr. Pizzolato's research centers on image and signal denoising, inverse problems, optimization, diffusion MRI, tractography, and Monte Carlo simulations. He actively contributes to the development of microstructural models for brain imaging, with applications in neurodegenerative diseases and brain connectivity. His work aligns with UN Sustainable Development Goals, particularly in advancing education and health through imaging technology. The recent publications reflect a strong trend in advancing diffusion MRI techniques, including ACID imaging, microscopic propagator modeling, myelin integrity mapping, and multi-scale white matter organization. These works emphasize biophysical accuracy, model validation, and integration across imaging modalities and species. Magna Cum Laude , ISMRM 2020 Magna Cum Laude , ISMRM 2022 First Place , Macaque Validation Challenge at ISBI 2018 First Place (Overall and HCP) , IronTrack Challenge 2019 (MICCAI) MICCAI Student Travel Award 2015 He has supervised PhD students such as Thøgersen, T. L. and Corral Bolaños, M. in projects related to microstructure MR imaging and myelin mapping. He has also been involved in significant grants and collaborative projects, including the Multimodal Microstructure-Informed Connectivity (MMINCARAV) initiative between Inria and EPFL, and the Sinergia consortium for Brain Communication Pathways . He co-organized multiple international events, including the MICCAI CDMRI workshops and challenges (2019–2021), and the ESMRMB Leaps in Microstructure Imaging workshop (2024). Dr. Pizzolato is an active member of the scientific community, serving as an editor for MICCAI workshop proceedings, a reviewer for major journals and conferences, and an invited speaker at ISMRM 2025. He leads and participates in several ongoing research projects at DTU focused on quantitative imaging, myelin mapping, and MRI-based connectivity, demonstrating sustained research leadership and external funding success.
Mads Høi Rasmussen is an Associate Professor at the Department of Mechanical Engineering, University of Southern Denmark. His work bridges robotics, production engineering, and sustainable energy systems. Key Research Areas: Robotics, Sustainable Energy, Production Engineering Projects: Co-Investigator in the 'Mini Picker' research project Research Focus includes robotic assembly systems, phase change materials for building temperature regulation, and hybrid ventilation technologies. His work on robot cell matrices aims to enhance agile manufacturing processes. Media Contributions highlight his family's efforts to combat fatal diseases in Bolivia, reflecting interdisciplinary engagement beyond academia. Collaborations span international partnerships in manufacturing, robotic assembly, and mechanical design.
Hans Magnus Henrik Lundell is an Associate Professor at the Department of Health Technology, Technical University of Denmark , specializing in Magnetic Resonance research. His work bridges biomedical engineering and neuroscience through advanced imaging techniques. Active in diffusion MRI and neurodegeneration research Current supervisor of two PhD students in multi-modal imaging projects Contributor to 11 publications with international collaborations Focus on tumor microstructure and cerebellar imaging applications His research on Diffusion-weighted MRS and time-dependent diffusion imaging has applications in glioblastoma diagnostics and neurodegenerative disease studies. Recent work explores clinical MRI-Linac integration for radiotherapy monitoring and extracellular diffusion dynamics in human tissue.
Markus Kiderlen is an Associate Professor at the Department of Mathematics, Aarhus University, specializing in the intersection of geometry, probability theory, and statistics. His research spans integral geometry, convex geometry, stochastic geometry, geometric tomography, and spatial statistics. Primary affiliation: Department of Mathematics, Aarhus University Academic rank: Associate Professor His work in stochastic geometry involves integral geometric relations, Minkowski tensors for quantifying random particles, and uniqueness/inference problems in geometric tomography (e.g., solving Hammer's X-ray problem). Another key focus is spatial sampling methods, including Wicksell's corpuscle problem and Cavalieri volume estimation improvements. Recent research trends include geometric reconstruction algorithms, stereological techniques for nonconvex particles, and rotational integral formulae for convex bodies. He has also explored polarizations in rearrangement processes and their applications. Markus Kiderlen has presented at international conferences such as MCQMC (2022), Stochastic Geometry Workshops (2019-2022), and the WIASABISS workshop (2018). His publications reflect collaborations with researchers like M. Stehr, R. Eriksen, and D. Hug.
Mikael Novén serves as an Assistant Professor in the Movement and Neuroscience division of the Department of Nutrition, Exercise and Sports at the University of Copenhagen. His research program bridges aging studies, motor control, and neuroimaging with a focus on how the aging brain learns fine-motor skills using advanced MRI techniques including functional imaging, diffusion-weighted data, and quantitative T1 mapping. His research interests center on aging-related changes in motor learning , brain structural networks , and language processing mechanisms . Using MRI methodologies, he investigates functional and structural reconfigurations during precision pinch tasks while also exploring brain correlates of phonological proficiency. His work spans cognitive neuroscience, gerontology, and MRI physics development with particular emphasis on sensorimotor integration across the lifespan. Analysis of his publication record reveals consistent research trajectories in age-related motor control differences (particularly 2024-2025 bimanual tracking studies), neurolinguistics (2021-2024 language processing work), and MRI methodology development (2021 physics paper). His recent work increasingly focuses on comparative analyses between younger and older adults, with three 2024-2025 publications specifically addressing aging effects on motor skill acquisition. Dr. Novén maintains active professional engagement through Twitter (@NeuroLingMi) and GitHub (MikNoven), with research outputs appearing in high-impact journals including NeuroImage, Human Brain Mapping, and Frontiers in Aging Neuroscience. His Scopus Author ID is 57199058849 and ORCID is 0000-0003-0256-0522.
Tim Bjørn Dyrby is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing. His research focuses on medical imaging, particularly diffusion MRI, tractography, and biophysical modeling of the brain. His research interests lie at the intersection of neuroscience, medical imaging, and computational modeling. Key areas include Diffusion MRI , Tractography , Axonal modeling , Myelin integrity , and quantitative MRI . He applies advanced computational techniques to understand brain microstructure and connectivity in both health and disease. His recent publications highlight a strong focus on standardization and methodological advancements in preclinical diffusion MRI, particularly in vivo and ex vivo imaging protocols. The work emphasizes data processing, validation against microscopy, and the application of tractography for neural pathway mapping. There is a growing emphasis on linking MRI-derived biomarkers to neurophysiological properties such as conduction velocity. Tim Dyrby actively supervises PhD students and leads significant research projects. He is the Principal Investigator (PI) of the CoM-BraiN project, which aims to develop a non-invasive framework for mapping conduction velocity in brain networks. His collaborative network is extensive, involving international experts in MRI physics and neuroscience. He is affiliated with the Visual Computing section at DTU Compute, where he contributes to advancing computational methods for brain imaging analysis. His work is supported by active research grants and contributes to key UN Sustainable Development Goals in health and well-being.
Jeanette Krogh Petersen is a Clinical Associate Professor at the Research Unit for Pathology (Odense) under the Clinical Institute of the University of Southern Denmark. Her work focuses on epigenetics, DNA methylation, and tumor biology in central nervous system tumors, particularly glioblastoma and meningioma. She actively collaborates with multidisciplinary teams across institutions. Affiliation: Clinical Institute, University of Southern Denmark Role: Research Unit for Pathology (Odense) Research Interests: Epigenetic mechanisms in intracranial tumors Development of 3D in vitro tumor models Multiomic profiling of glioblastoma progression Genomic and molecular characterization of pituitary adenomas Recent Publication Trends: Her 2024-2025 work emphasizes advanced tumor modeling, epigenetic biomarkers, and neuroimaging integration for precision oncology. Collaboration Network: Partners in Denmark and international institutions, with focus areas in neuro-oncology, molecular pathology, and radiation biology.
Professor J. Andreas Bærentzen is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), where he has held academic positions since 2001. His research focuses on computer graphics, shape modeling, real-time rendering, and geometry processing. He holds a MSc Eng (1998) and PhD (2003) from DTU. His work emphasizes topological adaptability in shape representation and efficient geometry processing, with notable contributions to structural topology optimization, 3D reconstruction, and virtual reality applications. Education: MSc Eng, Technical University of Denmark, 1991–1998 PhD, Technical University of Denmark, 1998–2003 Research Interests: Interactive 3D modeling and real-time graphics Topology optimization and structural infill design Shape modeling using distance fields and deformable hypersurfaces Applications in biomedical imaging (e.g., white matter dynamics) and environmental engineering (e.g., tree geometry simulation) His recent publications highlight advancements in neural network-based shape representation, skeletonization for tree reconstruction, and inverse-designed structural infill for engineering. He supervises multiple PhD students and leads projects on robotic manufacturing and virtual reality visualization. Bærentzen collaborates internationally, including visits to Stony Brook University (USA) and Padova University (Italy). Advisees & Projects: PhD Students: Rui Cui, Thomas D. V. Christiansen, Elias Theil Gæde Key Projects: 'Generative Methods for Brain Tissue Phantoms', 'Neural Form Representation', 'Graph Algorithms with Geometric Applications' His work bridges theoretical geometry processing with practical applications in architecture, biomedical engineering, and environmental science, leveraging DTU's interdisciplinary research ecosystem.
Kristoffer Hougaard Madsen is a Professor at the Department of Applied Mathematics and Computer Science , Technical University of Denmark (DTU), specializing in Visual Computing and Cognitive Systems . His work focuses on brain function mapping using functional MRI (fMRI), with expertise in fMRI data analysis, study design, and noise reduction techniques. Education: Civil Engineer (Bioinformatics & Complex Systems) from DTU (2004) External Position: Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre (since 2008) His research spans neuroimaging , brain network modeling , and neuromodulation techniques like transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS). He supervises PhD projects on topics such as individual brain circuit modeling , cerebellum organization in schizophrenia , and cooperation behavior in children . Recent publications highlight his contributions to electric field optimization , time-dependent diffusion imaging for tumors, and high-resolution mapping of brain structures . His work aligns with UN Sustainable Development Goals related to health and well-being. He collaborates extensively with institutions like Copenhagen University Hospital and contributes to interdisciplinary research in neurodegenerative diseases (e.g., Parkinson’s, Multiple Sclerosis) and psychiatric disorders .
