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.
Alexey Solodovnikov is an Associate Professor and Curator at the Natural History Museum Denmark, University of Copenhagen. Since 2022, he has led the museum's Zoology research section. His academic work focuses on systematic entomology with special emphasis on rove beetles (Insecta: Coleoptera: Staphylinidae), the largest family of living organisms. Dr. Solodovnikov's educational background includes graduating from university in Krasnodar in 1993, followed by obtaining his PhD from St. Petersburg State University in 1997. He conducted post-doctoral work at the Field Museum of Natural History in Chicago under renowned experts Alfred Newton and Margaret Thayer. His primary research interests encompass systematic entomology, phylogenetics, taxonomy, and biodiversity patterns of rove beetles. As a systematic entomologist, he discovers new species, develops phylogeny-based classifications, and studies evolutionary, biogeographic and macroecological patterns of biodiversity. His work involves extensive study of institutional entomological collections and leading insect collecting expeditions globally. Dr. Solodovnikov has published 137 research outputs, including 129 journal articles. His recent publications demonstrate strong trends in phylogenomics, integrative taxonomy combining morphological and molecular data, citizen science applications in entomology, and studies of specialized ecological relationships like beetle-mammal mutualisms. His work appears in prestigious journals including Systematic Entomology, Systematic Biology, and Journal of Natural History. His scientific contributions are significant in advancing our understanding of insect biodiversity, particularly through methodological innovations that bridge traditional taxonomy with modern computational approaches. Dr. Solodovnikov is actively involved in academic instruction and mentorship. At UCPH, he teaches Entomology and Terrestrial Zoology courses, previously taught in the Basal Arctic Biology course, and currently instructs the Communicating Science module in the UCPH-SCIENCE "Fundamentals" PhD course. He trains the next generation of zoological taxonomists through Master's, PhD, and post-doctoral level mentorship, focusing on developing sustainable expertise to identify, study and protect insect species, many of which remain undiscovered. His research laboratory operates within the Natural History Museum Denmark, with international collaborations spanning multiple continents. The team combines traditional taxonomic approaches with cutting-edge techniques including phylogenomics, deep learning for morphological analysis, and citizen science initiatives to advance systematic entomology and biodiversity research.
Gabriel Brammer is an Associate Professor at the Niels Bohr Institute , The Cosmic Dawn Center (DAWN) , University of Copenhagen. His research focuses on the formation and evolution of galaxies across cosmic time, utilizing data from the Hubble Space Telescope and contributing to the James Webb Space Telescope (JWST) Guaranteed Time Observer and Early Release Science programs.
Jonas Vinther is a Research Fellow at the Department of Computer Science , University of Copenhagen, specializing in Machine Learning and its intersections with quantum computing, medical data analysis, and sustainability. He is also an external PhD student in the Quantum Information Science & Technology program at the Niels Bohr Institute. Email: jonas.vinther@nbi.ku.dk , jonas.vinther@di.ku.dk Location: Universitetsparken 1, 2100 København Ø His research spans quantum machine learning , AI ethics , medical imaging , and environmentally sustainable AI , with recent publications on topics ranging from quantum neural networks to fairness in recommender systems . He contributes to the SCIENCE AI Centre and collaborates on initiatives like TreeSense for global tree resource monitoring.
Ivan Adriyanov Nikolov is an Assistant Professor at the Department of Architecture, Design and Media Technology within Aalborg University's Technical Faculty of IT and Design. He specializes in Computer Graphics, Computer Vision, and Augmented Reality, with a focus on 3D reconstruction techniques like Structure-from-Motion (SfM). His work bridges academic research and industrial applications, particularly in wind turbine blade inspection and educational technology. His educational background includes contributions to computer science education through innovative teaching methods. He has led projects like 'Drone Application for Pioneering Reporting in Wind Turbine Blade Inspection' (2017–2019) and 'Leading Edge Roughness - Wind Turbine Blades' (2015–2019), advancing drone-based inspection and 3D modeling for wind energy sectors. Research interests include synthetic data generation, environmental monitoring datasets (e.g., BrackishMOT, DigiWeather), and improving VR/AR user experiences. He has developed tools for dynamic lighting in pixel art games and multimodal guardian systems in VR. His datasets, such as Sewer Defect Point Clouds and Wind Turbine Blade SfM Reconstructions, are publicly available for academic use. He actively contributes to educational innovation, such as flipped classroom strategies to boost programming class engagement. His interdisciplinary approach spans computer graphics, AI-driven NPC interactions, and collaborative mixed-reality games for trust-building. Labs/Teams: Member of the Computer Graphics Group and Visual Analysis and Perception team at Aalborg University. Collaborates with industry partners on drone technology and environmental surveillance systems.
Henning Tangen Søgaard is an Associate Professor at the Department of Mechanical and Production Engineering, part of AU Engineering at Aarhus University. He teaches mathematics, numerical methods, and mathematical statistics to BEng students. His research focuses on robotics in agriculture , dynamic modeling , and precision agriculture . Primary Affiliation: Department of Mechanical and Production Engineering, AU Engineering, Aarhus University Research Expertise: Computer vision, control systems for agricultural robotics, environmental modeling (ammonia emissions, spray drift), and wireless sensor networks. His work includes developing autonomous systems for weed control, GPS-based geo-referencing of crops, and mathematical models for fertilizer-related emissions. Publications span peer-reviewed journals and reports in agricultural engineering , robotics , and environmental science . Scientific awards are not mentioned in the provided text. He has no listed PhD students but has collaborated on multiple projects. For direct contact, his email is hts@mpe.au.dk .
Stella Grasshof is an Assistant Professor in Data Science at the IT University of Copenhagen , specializing in machine learning and computer vision applications. Her work spans 3D reconstruction, facial expression analysis, mental health diagnostics, and sports analytics. Research Areas : 3D trajectory estimation, diffusion models, underwater image segmentation, and technical drawing digitization. Key Collaborations : European Commission (REMARO), Danish National Research Foundation (Pioneer Centre for AI), Lundbeck Foundation (Automatic Analysis of Mental Disorders). Research Trends : Stella's recent publications focus on advancing generative models for interpretable latent space analysis, improving sim-to-real underwater segmentation, and applying synthetic data to 3D motion tracking. Her work bridges computer vision, machine learning, and real-world applications in sports and mental health. Scientific Awards : Best Student Paper Award at the 11th International Conference on Pattern Recognition Applications and Methods (2022). Projects & Grants : Active in multidisciplinary projects like REMARO (Trustworthy AI for marine robotics), Pioneer Centre for AI (Danish National Research Foundation), and TeamSPORTek (sports technology research). She has also developed datasets like MarinaPipe for marine robotics.
Celia Kjærby is an Associate Professor at the Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, where she also leads the Division of Sleep-Arousal State Transitions at the Center for Translational Neuromedicine. Her research focuses on understanding sleep micro-structures and their role in cognitive performance and brain health. Education: PhD, Graduate School of Health and Medical Sciences, University of Copenhagen (2012) M.Sc. (human biology), Faculty of Health and Medical Sciences, University of Copenhagen (2007) Bachelor of Science (biology), Faculty of Sciences, University of Copenhagen (2004) Kjærby's research investigates how sleep-arousal transitions impact restorative sleep processes related to memory consolidation and waste clearance. Her work is particularly relevant for understanding neurodegenerative and neuropsychiatric disorders where sleep disturbances play a significant role. She examines the complex micro-structures of sleep and how frequent short arousals contribute to normal sleep function. Her recent publications (2024-2025) reveal a strong focus on the glymphatic system, cerebral blood flow regulation during sleep, and the relationship between sleep disturbances and neurodegenerative conditions like Alzheimer's disease. Her research integrates advanced techniques including CRISPR/Cas9, fluorescent imaging, and machine learning approaches to analyze sleep patterns. Scientific Recognition: Member of Lundbeck Foundation Investigator Network (LFIN) (2022) Cover feature in Nature Neuroscience (August 2022) Kjærby has secured significant research funding including the Lundbeck Foundation Fellow award (2023), Lundbeck Foundation Seed Grant (2023), and an Inge Lehmann independent grant from the Independent Research Fund Denmark (2022). She serves on the editorial board of Frontiers in Neural Circuits and reviews for prestigious journals including Nature and Neuron. She is also active in scientific outreach, regularly participating in public lectures and media interviews about sleep science. She leads the research group focused on Sleep-Arousal State Transitions and has been instrumental in organizing neuroscience events including the monthly 'DIM the Brain' forum for students and postdocs at the University of Copenhagen since 2016.
Patrizia Paggio serves as an Associate Professor and Senior Researcher within the Department of Nordic Studies and Linguistics at the University of Copenhagen's Faculty of Humanities, concurrently holding a full professorship at the University of Malta's Institute of Linguistics and Language Technology since September 2011. Her scholarly work centers on the intricate relationship between verbal and nonverbal communication modalities, with international recognition for advancing methodologies in multimodal analysis. Academic Background: PhD in Computational Linguistics from the University of Copenhagen (1997), dissertation: "The Treatment of Information Structure in Machine Translation" Professor Paggio's research program investigates how gestures, head movements, and other nonverbal cues interact with spoken language to construct meaning in natural communication. She has pioneered methodologies for constructing and analyzing multimodal corpora, while maintaining technical expertise in machine translation systems, grammar engineering, and content-based querying frameworks. Her theoretical work spans formal syntactic structures, discourse phenomena, information packaging, and ontological representations for linguistic data, consistently bridging computational methods with linguistic theory. Analysis of her recent publications (2020-2025) reveals a sustained focus on computational approaches to nonverbal communication, particularly the automatic detection and annotation of head movements and gestures in both physical and digital environments. Key contributions include the GEHM Zoom corpus for online interaction analysis, eye-tracking studies of emoji processing, and diachronic modeling of historical language change. Her work strategically integrates eye-tracking, corpus linguistics, and machine learning techniques, establishing her at the convergence of linguistic theory, cognitive science, and artificial intelligence applications. Professional Leadership: Coordinator of the international GEHM (Gestures and Head Movements in Language) research network Organizer of MULTIMODAL CORPORA 2018, 4th European/Nordic Symposium on Multimodal Communication, and LREC2022 Workshop on People in Vision, Language and the Mind
Mohammad Naser Sabet Jahromi is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University, Denmark. He is affiliated with the Visual Analysis and Perception Centre for AI Ethics, Law and Policy. His research focuses on explainable AI (XAI), biometrics, machine learning, and ethical AI applications in legal and medical domains. He actively participates in interdisciplinary projects like REPAI: Responsible AI for Value Creation (2023-2027), which explores AI ethics, computational discourse analysis, and value-driven AI systems. His educational background is not explicitly detailed in the provided text, but his research trajectory indicates strong expertise in computer science and AI systems. Key research interests include interpretable machine learning models, privacy-preserving biometric systems, and AI applications in asylum adjudication and educational assessment. Recent work emphasizes developing XAI frameworks like SIDU-TXT for NLP, verifying machine unlearning mechanisms, and automating large-classroom assessments. His projects bridge technical AI advancements with societal implications through collaborations with legal and ethical scholars. Notable contributions include datasets evaluating XAI methods in medicine and methodologies for transparent AI decision-making. He has participated in conferences such as ICPR 2024 and JURISIN 2023, showcasing interdisciplinary research impact.
Alan O'Leary is an Associate Professor in Media Studies at Aarhus University's School of Communication and Culture, where he specializes in videographic criticism and academic filmmaking. His work bridges traditional scholarship with innovative video essay formats, exploring anti-utilitarian practices of 'minor' and 'luxury' scholarship. Dr. O'Leary's research focuses on the methods and poetics of video essays, with particular interest in constraint-based creativity. His scholarly profile includes significant contributions to understanding how digital videos can serve as critical commentary on film and screen media. He has published extensively in leading journals including [in]Transition: Journal of Videographic Film & Moving Image Studies , where he serves as co-editor. His recent publications demonstrate a consistent trajectory exploring videographic criticism as scholarly practice, with increasing focus on creative constraints, epistolary formats, and collaborative approaches. O'Leary's work has gained international recognition, with video essays winning prestigious awards and being selected for major film festivals including Marienbad Film Festival 2025. Winner of the Videographic Criticism category of the British Association of Film, Television and Screen Studies (BAFTSS) Practice Research Awards 2024 Video essay CLASSIF. & ME (LAIRD'S CONSTRAINT) selected for Marienbad Film festival 2025 Multiple video essays named among the best in Sight and Sound annual polls (2022, 2023) O'Leary actively supervises MA theses and PhD students working on topics including film festivals, collaborative songwriting, and popular celebrity, with special interest in practice-based research. He leads several research projects including Cyborgs, Constraints and Critical Intimacies: The Poetics of Videographic Criticism and Epistolary video essay , while regularly organizing workshops and conferences on videographic methods.
Naohiro Okada is an Associate Professor at the Graduate School of Medicine, Department of Psychiatry, The University of Tokyo, and concurrently serves as an Associate Professor at the International Research Center for Neurointelligence (IRCN). He is also the Core Manager of the Human fMRI Core facility. Dr. Okada has extensive experience in neuroimaging research, particularly focusing on psychiatric disorders and adolescent brain development. Dr. Okada obtained his M.D. from the University of Tokyo Faculty of Medicine in 2004. After completing his residency, he began psychiatry training at the University of Tokyo Hospital in 2006 and worked as a psychiatrist at Tokyo Metropolitan Matsuzawa Hospital from 2007 to 2012. He earned his Ph.D. from the Graduate School of Medicine, University of Tokyo in 2017, and joined IRCN in 2019 where he manages the human fMRI scanner facility. His research primarily focuses on using functional magnetic resonance imaging (fMRI) to understand brain structure and function in healthy adolescents and patients with psychiatric disorders. Dr. Okada's work aims to elucidate the neurobiological substrates of psychiatric disorders and develop biomarkers for clinical applications. He has published extensively on topics including schizophrenia, autism spectrum disorder, depression, and adolescent brain development, with a particular emphasis on multi-site collaborative studies and data-driven approaches to psychiatric classification. Dr. Okada's recent publications demonstrate a strong focus on developing novel diagnostic classifications based on neuroimaging data, investigating resting-state neural signatures across psychiatric disorders, and establishing robust infrastructure for multi-center MRI research. His work bridges human and animal research while incorporating machine learning and AI techniques to advance the field of psychiatric neuroimaging. Dr. Okada is actively involved in several research projects funded by the Japan Society for the Promotion of Science, including the Advanced Bioimaging Support Platform (2022-2028), MRS analysis of basal ganglia GABA dysfunction in schizophrenia (2021-2025), and studies on dose reduction and brain function changes in schizophrenia patients (2018-2022). He is a member of the Society for Neuroscience and the Japanese Society of Biological Psychiatry, reflecting his commitment to advancing neuroscience research and its applications in understanding and treating psychiatric disorders.
Adam Scharpf is a Tenure Track Assistant Professor in Comparative Politics at the Department of Political Science , University of Copenhagen . His research focuses on political regimes, autocracy dynamics, and security apparatus behavior, with a special emphasis on loyalty production and repression mechanisms. Research Interests: Political regime structures and transition Authoritarian security sector dynamics International relations of dictatorships Sportswashing and reputation management Elite selection in repressive institutions Military training and political militarization Publication Trends: Recent work examines soft power targeting through Kissinger's seminars, sportswashing effectiveness analysis, military training impacts on political systems, and authoritarian security apparatus career dynamics. His 2023-2025 publications show increasing focus on event-driven repression patterns and elite ideological influence. Awards: APSA Best Article Award (Democracy & Autocracy Section) NEPS Stuart A. Bremer Award ISA Dina Zinnes Award Young Scholar Award (University of Mannheim) Contact: adam.scharpf@ifs.ku.dk | Office Hours: Wednesdays 16.00-17.00
Jon Sporring is a Professor at the Department of Computer Science, University of Copenhagen, specializing in theoretical and applied image processing, stochastic geometry, and biomedical imaging. He leads research in mathematical and medical image analysis, computer graphics, and pattern recognition. Education: Ph.D. in Computer Science (1998), Master in Computer Science (1995), both from University of Copenhagen Affiliations: Pioneer AI section, Applied Geometry Lab, and Faculty of Science External Roles: Visiting professor at McGill University (2012-13), co-founder of DigiCorpus Aps (2012-16) His research integrates scale-space theory, statistical shape analysis, and advanced imaging techniques for applications in medical diagnostics, materials science, and neuroscience. Recent work focuses on 3D reconstruction, persistent homology for bias correction, and AI-driven biomedical analysis. Jon teaches computer science at all academic levels, currently offering courses in bioimaging, signal processing, and deep learning. He emphasizes collaborative projects with external partners and has held administrative roles including Vice-Chair for Research at DIKU. His 15 most recent publications reflect expertise in medical imaging, 3D modeling, and AI applications, with subfields spanning neurodegenerative disease analysis, mitochondrial ultrastructure, and multi-scale image processing. Articles demonstrate interdisciplinary impact across medicine, biology, and materials science.
