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.
Francois Lauze is an Associate Professor at the Department of Computer Science , University of Copenhagen, affiliated with the Image Analysis, Computational Modelling and Geometry research group. His work bridges mathematical rigor and practical applications in image processing and shape analysis. Research Focus: Mathematical Image Analysis (variational/PDE methods) Differential and Riemannian geometry for shape statistics Applications: image inpainting, motion estimation, segmentation, medical imaging Contact: Email: francois@di.ku.dk Phone: +4535335671, +4521553933 Location: Universitetsparken 1, 2100 Copenhagen Ø Recent publications highlight advancements in SE(3) group CNNs for diffusion imaging, locally orderless networks for efficient processing, and refractive multi-view stereo techniques. His work integrates geometric modeling with computational implementations, emphasizing medical and video applications.
Silvia Tolu is an Associate Professor at the Technical University of Denmark's Department of Electrical and Photonics Engineering, specializing in Neurorobotics. She leads the NeuroRobotics Technology Lab (NRT-LAB), focusing on bio-mimetic control architectures for compliant robotic systems. Her research integrates neuroscience, computer science, and biology to develop solutions for assistive robotics and neurodegenerative disease diagnosis. Her research interests span: Neuro-robotics and neuromorphic engineering Bio-inspired control systems and adaptive motor control Machine learning for robotic applications Human-robot compliant interaction Cerebellar control models Publications primarily focus on neurorobotics, bio-inspired control, and human-robot interaction, with recent advances in learning-based control systems for soft robots and aerial manipulation. Awards include the AEG Elektrofonden Research Grant and funding for human-robot interaction safety research. Current projects include LOCOPD (Lundbeck Foundation), AEROTRAIN (EU Marie Curie ITN), and compliant human-robot interaction systems. She supervises multiple PhD students in neurorobotics and maintains international collaborations across Europe and Asia. Laboratory resources include advanced robotic platforms for musculoskeletal and soft robot control.
Anders Bjorholm Dahl is a Professor at the Department of Applied Mathematics and Computer Science , DTU Compute , Technical University of Denmark (DTU). His research focuses on medical imaging, computer vision, and biomedical engineering. He leads projects in ultrasound imaging, AI-driven medical diagnostics, and advanced imaging technologies for healthcare applications. Education: Ph.D. in Computer Science (Image Analysis and Computer Vision), DTU (2005–2009) Forestry, Royal Veterinary and Agricultural University (1997–2004) Research Interests: Combines machine learning and advanced imaging techniques to address challenges in medical diagnostics, including ultrasound super-resolution, stenosis detection in coronary angiographies, and material anisotropy analysis. His work bridges anatomy and histology using X-ray tomography and explores AI applications in healthcare. Key Projects: Crowd Counting through Remote Sensing (2025–2027) AI for Extreme Super-Resolution CT (2024–2026) Fighting Cancer with Generative AI (2024–2027) Labs/Teams: Leads the UltraSound and Biomechanics Visual Computing Center for Fast Ultrasound Imaging , focusing on real-time medical imaging solutions.
Dimitris Chrysostomou is an Associate Professor in the Department of Materials and Production at Aalborg University, Denmark. He leads the Robotics & Automation Group and directs the AI:Cybernetics Lab. His work focuses on developing safe, intuitive robotic systems for industrial and social contexts, emphasizing human-robot interaction (HRI), AI ethics, and collaborative robotics. Chrysostomou has over 15 years of research experience, funded by EU frameworks and national grants, with over 70 peer-reviewed publications. Education: PhD in Robot Vision (2013) and Diploma in Production Engineering (2006) from Democritus University of Thrace. He coordinates courses in robotics and manufacturing technology, emphasizing problem-based learning models. Administrative roles include heading the Robotics and Automation Group and the Aalborg Robotics Challenge steering committee. Research interests span AI-driven robotics, ethical implications of robot behavior, and HRI evaluation methodologies. Key projects include SAPIENT (2025-2027) for robotic intelligence and RIACT (2024-2025) on collaborative robot technology. Editor-in-Chief of *Industrial Robot* journal, IEEE Senior Member, and leader in euRobotics standardization initiatives. Notable contributions include virtual assistants for industrial robots, trust evaluation frameworks in HRI, and energy-based approaches for collaborative robotics. Active in conference organization, editorial roles, and industry collaborations, including co-founding AI startups.
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.
Rune W. Berg is an Associate Professor in the Promotion Programme at the Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen. He leads the Berg Lab with research focused on Neuronal Signalling and maintains an active research profile with 66 publications to date. Dr. Berg's educational background includes a Ph.D. in Biophysics from the University of California, San Diego (2003), an M.S. in Physics from UC San Diego (2000), and Cand. Scient. and B.Sc. degrees in Biophysics from the Niels Bohr Institute at the University of Copenhagen (2000 and 1997 respectively). His research interests span Functional Neuronal Networks, Sensory and Motor processing, and Complex physics. The Berg Lab investigates neural signaling mechanisms with a strong emphasis on developing novel technologies for neural interfacing and brain research. Recent work demonstrates an interdisciplinary approach combining neuroscience, physics, and engineering to create advanced tools for neural monitoring and modulation. Analysis of Dr. Berg's recent publications reveals a strong focus on neural engineering technologies, particularly optical and electromagnetic approaches for brain research. His work bridges fundamental neuroscience with practical engineering solutions for neural interfaces, with applications in understanding brain function and developing neural prosthetics. The research spans from molecular-level interactions to circuit-level neural dynamics. Dr. Berg has participated in specialized training workshops including 'Construction of the brain' at Kristineberg Marine research station, 'Neurophysics' at the Institute of Theoretical Physics in Santa Barbara, and 'Neuron as a nonlinear oscillator' at the Salk Institute. His professional experience includes continuous work since January 2004 as a Post Doctoral member of Jorn Hounsgaard's Lab at the University of Copenhagen, following a Visiting Post Doctoral fellowship at Taipei Veterans General Hospital and National Yang-Ming University in Taiwan (September-December 2003).
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
Jacob Nielsen is an Associate Professor at the SDU Metaverse Lab, affiliated with the Maersk Mc-Kinney Moller Institute at the University of Southern Denmark. His research spans robotics, audiometry, and educational technology, with a focus on user-centered design and accessibility. Current Role: Associate Professor, SDU Metaverse Lab Key Themes: Modular Robotics, Human-Robot Interaction, User-Operated Audiometry His recent work emphasizes democratizing audiometric testing through smartphone applications and self-administered methods, while earlier contributions include educational robotics frameworks for children and rehabilitation systems using industrial robots. Collaborations extend to clinical audiology and STEM engagement projects in Africa. 2024-2025: 5 publications in user-operated audiometry and hearing aid calibration 2017-2020: TEDx talks and youth robotics programs in Denmark Jacob actively contributes to public discourse through 51 media appearances, including discussions on social innovation, robotics in education, and Denmark’s future technologies.
Xuping Zhang is an Associate Professor at the Department of Mechanical and Production Engineering, Aarhus University, within the AU Engineering college. Their expertise spans mechatronics, robotics, and control systems, with a focus on applications in rehabilitation, manufacturing, and biological handling. Fields of Expertise: Mechatronics Design, Robotic Inspection and Maintenance, Digital Twin Technology, and Human-Robot Collaboration. Recent publications (2024) include advancements in locomotion control for quadruped robots and hand-eye calibration using 3D vision, reflecting their interest in hybrid control algorithms and robotic agility. They are involved in EU DEMO remote maintenance projects and Danish SME manufacturing initiatives. Contact: Email xuzh@mpe.au.dk or phone +45 4189 3167.
Ming Shen is an Associate Professor at the Department of Electronic Systems, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on antennas, millimeter-wave systems, and AI-driven RF sensors with applications in 5G/6G communications, biomedical engineering, and smart systems. His research interests span antenna design (including phased arrays, metamaterials, and compact structures), AI integration in electromagnetic systems, and medical sensor technologies. Recent projects include drone-based electromagnetic signature analysis, vibration energy harvesting for pacemakers, and smart healthcare systems for posture recognition and surgical site infection monitoring. Key projects include DRONES: Drone-Obtained Electromagnetic Signatures (2024–2028), Sensor Intelligence for Healthcare and Sports (2022–2027), and DeepBone (2021–2022), which explored deep learning for surgical infection detection. His work also bridges machine learning and electromagnetic design, with breakthroughs in surrogate modeling and automated antenna optimization. Ming Shen has supervised 6 PhD students and published over 160 peer-reviewed articles. Notable contributions include AI-assisted NLOS sensing, ultra-wideband antenna innovations, and medical applications such as electrical impedance-based bone healing assessment.
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.
Hans Martin Kjer is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he is affiliated with the UltraSound and Biomechanics group within the Visual Computing Center and the Center for Fast Ultrasound Imaging. His research bridges engineering and medical imaging, with a strong emphasis on developing and validating advanced ultrasound techniques for biomedical applications. Research Interests: His work focuses on super-resolution ultrasound imaging, microvascular analysis, 3D reconstruction of biological structures, and image registration. He applies computational methods to improve the resolution and accuracy of ultrasound, particularly in renal and lymph node vasculature imaging. His research contributes to the UN Sustainable Development Goals in health and well-being through innovative diagnostic tools. Publication Trends: Over the past several years, Kjer has consistently published in high-impact journals and conferences in biomedical engineering and imaging. His recent work emphasizes the validation of super-resolution ultrasound against micro-CT, realistic 3D blood flow simulation, and the application of AI in enhancing imaging resolution. These studies reflect a strong trend toward quantitative, reproducible, and clinically relevant imaging solutions. Scientific Contributions: While no specific awards are listed, his leadership in major research projects and frequent collaborations with leading experts in ultrasound (e.g., Jørgen Arendt Jensen) underscore his significant role in the field. Advising and Funding: Kjer serves as a supervisor and principal investigator in several funded research initiatives, including AI for Extreme Super-Resolution CT , 3DIM: 3D Imaging Center , and QIM: Center for Quantification of Imaging Data from Max IV . He mentors PhD students and collaborates across disciplines, contributing to both biomedical and materials science imaging projects. Laboratories and Teams: He is an integral member of the Center for Fast Ultrasound Imaging and the Visual Computing Center at DTU. These teams focus on cutting-edge ultrasound technologies, image processing algorithms, and multimodal imaging integration, positioning Kjer at the forefront of computational biomedical imaging in Denmark.
Patricia Wolf is a Professor in the Department of Business & Management at the University of Southern Denmark (SDU), Faculty of Business and Social Sciences. She is affiliated with multiple interdisciplinary research centers, including the Centre for Integrative Innovation Management (C*I2M), the SDU SCC Elite Center PACA, and the SDU Climate Cluster, reflecting her broad impact across innovation, climate futures, and societal transformation. Her research focuses on innovation management, foresight methodologies, artificial intelligence in social contexts, knowledge management, and climate futures. She explores how organizations and societies can envision and enact sustainable futures, particularly through participatory and creative methods such as scenario development, flash fiction, and citizen science. The 15 most recent publications reveal a strong trend toward integrating AI, climate imagination, and participatory futures, with increasing emphasis on emotional dimensions like climate anxiety and hopeful envisioning. Her work bridges theory and practice, often involving collaborations with SMEs, educational institutions, and environmental organizations to co-create actionable strategies. Innovative Teaching Award 2024 John Bessant Best Paper Award (2023 and 2021) SCC Fast track - uddelingsrunde november 2024 Patricia Wolf has secured significant grant funding for projects such as FUSION, PACA, and CFF, where she serves as Principal Investigator or Co-PI. These projects focus on mobilizing youth, educators, and communities to engage in climate future fiction and responsible innovation. She has supervised PhD students and contributed to curriculum development in innovation and foresight education. Her teaching includes courses on innovation management, knowledge management, and organizational processes. She leads and participates in interdisciplinary teams across SDU, including collaborations with the Department of Sports Science, the Climate Cluster, and external partners in Denmark and Germany. Her labs and research groups emphasize co-creation, narrative methods, and future-oriented design, fostering a culture of integrative and socially responsible innovation.
Niels Bjørn-Andersen is an External Professor at Copenhagen Business School's Department of Digitalization within the CBS School of Business. His academic career spans five decades with significant contributions to Information Systems research, particularly in socio-technical systems and digital transformation. Recent work focuses on societal impact measurement and maritime informatics. His research interests center on Information Systems with specialization in digital ecosystems, value co-creation, and societal impact assessment. Key areas include: Maritime informatics and container supply chain optimization Open government data sustainability frameworks ERP systems evolution and implementation challenges Socio-technical traditions in Scandinavian IS research Academic impact beyond bibliometric metrics Recent publications show a strategic shift from technical ERP studies toward societal value measurement and maritime digitalization. With 150+ publications including 41 journal articles and 28 conference proceedings, his work demonstrates consistent engagement with real-world digital transformation challenges. Notable contributions include frameworks for PortCDM implementation and societal value measurement methodologies. Media engagement is substantial with 160 press appearances addressing IT failures in Danish public sector systems and e-commerce impacts on retail. Professional activities include AIS Grand Vision Project participation and lectures on Scandinavian socio-technical research origins. His supervised work encompasses 5 academic projects, though specific student names aren't disclosed in available materials. Current research trajectories emphasize sustainable value creation through digital infrastructure and redefining academic impact metrics.
