Viktor Holm-Janas is a Research Fellow at the Department of Computer Science (DIKU), University of Copenhagen, affiliated with the Human-Centred Computing section. His work bridges computational technology with human activities and well-being, focusing on educational settings and user interaction. Research Interests: Viktor investigates multimodal learning analytics, quantitative ethnography, and didactic theory applications in technology-enhanced education. He explores how human observations, data visualization, and interface design can support collaborative learning and physics education. Publications: His recent articles address topics like holographic analysis of classroom sound, active learning observation networks, and physics education tools. These contributions span journals such as Postdigital Science and Education and eLife , with a focus on educational technology and data-driven insights. Labs and Collaborations: Viktor collaborates within the Human-Centred Computing section, which emphasizes inclusive and innovative research environments. He contributes to projects like SAStutorials.org, advancing scientific data analysis tools.
Zaibei Li is a PhD Fellow at the Department of Computer Science (DIKU) of the University of Copenhagen , affiliated with the Human-Centred Computing section. Their research intersects Educational Technology , Multimodal Learning Analytics (MMLA) , and Human-Computer Interaction . Key Research Areas: Multimodal Learning Analytics for spoken language acquisition Collaboration analytics in hackathons and educational settings Design of smart, inclusive, and equitable learning systems Recent Work: 2024 contributions to EC-TEL , ICALT , and LAK24 conferences Development of open MMLA platforms and frameworks for human-centric analytics Contact: Email: zali@di.ku.dk Address: Sigurdsgade 41, 2200 København N.
Ekkart Kindler is an Associate Professor in the Department of Applied Mathematics and Computer Science at DTU Compute, Technical University of Denmark. His research focuses on model-based software engineering, process mining, and road condition assessment using vehicle sensor data. He leads the Competence Centre for Model-Based Software Engineering, supporting industry adoption of advanced software development methodologies. Education: M.Sc. (1990), Ph.D. (1995) from Technische Universität München; Habilitation in Computer Science (2001) from Humboldt-Universität zu Berlin. He held visiting professorships at German universities (2000–2007) and has extensive experience in formal methods, business process modeling, and Petri nets. Research interests include declarative process modeling, complexity metrics for cognitive load assessment, and the integration of formal methods into industrial software development. His work contributes to UN Sustainable Development Goals related to sustainable infrastructure (SDG 9) and innovation (SDG 9). Notable collaborations include road condition assessment projects using vehicle sensor data (LiRA-CD dataset) and contributions to Petri net standards (PNML). He has supervised PhD students such as K. I. Simonsen (protocol software) and A. Skar (road assessment). Grants and projects: Live Road Assessment with Vehicle Sensors (2019–2022), Model Transformation Tools (2013–2016), and waste management modeling (2012–2016). Active in open-source datasets and tool development for indoor climate control (climify.org).
Christoph Seidl is an Associate Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on software visualization, software archaeology, and the application of virtual reality in software engineering tasks. He leads the Immersive Software Archaeology project, exploring collaborative systems and legacy system analysis in virtual environments. Key research areas include software product lines, feature modeling, and model-driven development. Seidl has received awards such as the SoSyM Best Reviewer Award (2018) and SPLC'19 Distinguished Reviewer Award (2019). His work emphasizes innovative tools for software exploration, including immersive 3D visualization and collaborative note-taking systems in VR. He has published extensively on topics like variability management, configuration testing, and domain-specific languages. Research trends in his articles highlight advancements in using VR for software archaeology, collaborative software exploration, and methodologies for managing software evolution. His projects address challenges in legacy system understanding, feature model synthesis, and automated testing for configurable systems. Seidl collaborates internationally, with projects funded by the Independent Research Fund Denmark. His contributions span academic publications, datasets (e.g., VaMoS 2022 artifacts), and tool development for software product line engineering.
Jussi Parikka is a Professor in Digital Aesthetics and Culture at Aarhus University, leading the Digital Aesthetics Research Centre (DARC) and co-directing the Environmental Media and Aesthetics program. He holds a prominent role in media studies, with expertise spanning environmental media, media archaeology, and technological culture. His work bridges academia and art through curatorial projects like the Helsinki Biennial and Weather Engines exhibition. Parikka’s research focuses on the intersections of media, environment, and technology. Key themes include elemental media (e.g., wind), plant-based aesthetics, and critical engagements with AI and data visualization. He has authored influential books such as Insect Media (2010), A Geology of Media (2015), and Living Surfaces (2024), translated into 11 languages. His recent articles explore environmental data narratives, climatic media practices, and the socio-political dimensions of elemental forces. Awards include membership in Academia Europaea (2021). Parikka teaches courses in media theory, environmental humanities, and transdisciplinary methods, with over 20 years of international teaching experience. He collaborates with museums, artists, and designers to advance public engagement with environmental and technological issues.
Sara Paasch Knudsen is a Teaching Associate Professor at Aalborg University's Department of Culture and Learning, within the Faculty of Social Sciences and Humanities. She is affiliated with the IT and Learning Design Research Center (L-ILD) and the ILD-LAB research lab focusing on video in education and learning organization (MASSHINE and VIDEO projects). Her work bridges technology and education, particularly in immersive technologies like XR within higher education and organizational learning contexts. Key research interests include hybrid teaching formats, flexible learning spaces, and the integration of emerging technologies such as AR/XR into pedagogical practices. She has contributed to projects like 'Fremtidens Undervisningslokale' exploring future classroom designs and the 'VAAU HyFlex' initiative on hybrid teaching models. Knudsen has also collaborated on music education digitalization and SME data literacy initiatives. Recent publications (2023-2025) focus on organizational learning space design, AI in creative education processes, and teacher-student dynamics in hybrid learning environments. She has organized workshops on innovative learning spaces and contributed to public debates on educational inclusion. Knudsen holds an ORCID identifier (0000-0001-6866-2770) and maintains active research collaborations across Denmark and internationally.
Florian Echtler is an Associate Professor at Aalborg University's Department of Computer Science within The Technical Faculty of IT and Design. He holds a PhD in Computer Science from the Technical University of Munich (2009). His research focuses on ubiquitous computing, peer-to-peer networking, and security/privacy, aiming to reduce dependency on centralized infrastructure in mobile and cloud ecosystems. He has held roles including Junior Professor at Bauhaus-Universität Weimar (2014–2020) and Visiting Professor at University of Regensburg (2012–2014). Current affiliations: Human-Centered Computing Centre and Centre for Sustainable and Digital Transformation. Editorial roles: Journal of Visualization and Interaction, i-com. Research interests include interactive surfaces, mixed reality, mobile devices, and IoT. Notable projects: DeUCoE : Decentralized Ubiquitous Computing in Everyday Environments (DFG-funded, 2021–2024). VIGITIA : Smart interactive table environments (BMBF-funded, 2019–2022). Awards include DIS 2024 Honourable Mention, TEI 2022 Best Paper Award, and CHI 2020 Best Paper Award (top 1%). Active in media engagement, e.g., discussing mobile collision warnings (2022).
Erik Kjems is a Part-time Lecturer in the Department of the Built Environment at Aalborg University’s Faculty of Engineering and Science. His work bridges civil engineering and digital innovation, focusing on the integration of advanced technologies into infrastructure planning and management. University: Aalborg University School: Faculty of Engineering and Science Department: Department of the Built Environment Position: Part-time Lecturer Email: kjems@build.aau.dk ORCID: 0000-0002-4519-6583 His research interests are centered around digital transformation in civil infrastructure, including augmented and virtual reality (AR/VR), 3D city modeling, BIM, reality capture, data fusion, blockchain applications, and intelligent transport systems. He explores how digital tools can improve decision-making, safety, and efficiency in road and utility projects. The most recent publications (2021–2024) reflect a strong trend toward practical applications of AR/VR in subsurface utility visualization, digital twins, permeable pavement materials, and data integration for infrastructure. These works emphasize field deployment, user interaction, and reconciliation of heterogeneous data sources. His research combines technical innovation with real-world validation through collaboration with utility companies and public agencies. Erik Kjems has participated in multiple research projects, including BLING: Blockchain in Government and Integrated Project Development for Road Infrastructure Education , demonstrating sustained engagement in funded research. He has also contributed to public discourse through media appearances on road pricing and digitalization in transportation. He has supervised at least one PhD student and is actively involved in academic and professional networks. His activities include participation in workshops, conferences (e.g., buildingSMART International Standards Summit), and seminars focused on digital infrastructure and BIM. Notable labs or collaborative environments include involvement in the 3D Visual Data Mining (3DVDM) project and the Videncenter for 3D GeoInformation , indicating long-standing expertise in geospatial visualization and digital modeling.
Karsten Ulrik Niss is a part-time lecturer at Aalborg University's Faculty of Medicine, specifically within the Department of Health Science and Technology and the Danish Centre for Health Informatics. His work focuses on healthcare IT systems, organizational development, and telemedicine implementation. Research Interests: Telehealth systems, EHR integration, medical imaging informatics, organizational change in healthcare Key Expertise: Stakeholder analysis, clinical workflow optimization, medical IT evaluation His research explores the intersection of technology and human factors in healthcare settings, particularly through network analysis of telehomecare systems and bottom-up organizational development approaches. Recent publications examine video consultations for specialized treatments and systemic impacts of PACS/RIS implementations. Notable contributions include the MIEMIS framework for medical information system evaluation and studies on EHR implementation challenges. His work spans both theoretical modeling and practical case studies across multiple medical domains.
Daniele Dell'Aglio is an Associate Professor at the Department of Computer Science , Aalborg University , affiliated with the Technical Faculty of IT and Design . His research focuses on privacy-preserving data synthesis, knowledge graphs, and semantic data integration. Academic Rank: Associate Professor Department: Computer Science School: Technical Faculty of IT and Design University: Aalborg University Research Interests : Development of privacy metrics for synthetic data generation Heterogeneous graph representation in knowledge graphs Interactive evaluation tools for data privacy Transformer-based biomedical data extraction Integration of gut-brain axis scholarly data Scientific Awards : Best paper at the Deep Learning for Knowledge Graphs workshop (2022) Collaborative Projects include HEREDITARY (Heterogeneous semantic data integration for gut-brain interplay) as Principal Investigator, and partnerships with NASA on Mars exploration data processing. His work spans privacy-preserving technologies, knowledge graph engineering, and biomedical text mining applications.
Ulrik Pagh Schultz Lundquist is a Professor at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), where he serves as Head of both the SDU UAS Center and SDU Climate Cluster. With over 123 research outputs spanning robotics, drone technology, and programming languages, Lundquist leads significant initiatives including WildDrone (2023-2026) and Terra Salva (2024-2026), and has established himself as a leading expert in unmanned aerial systems research with extensive field applications in wildlife conservation. Lundquist's research focuses on the intersection of robotics and environmental science, with particular expertise in drone swarms for ecological monitoring. His work bridges theoretical computer science with practical conservation challenges, developing programming languages and formal models specifically for modular robotics systems. Key research thrusts include minimizing wildlife disturbance through optimized drone operations, multi-perspective data collection techniques, and scalable BVLOS (Beyond Visual Line of Sight) systems for conservation areas. His fingerprint analysis reveals strong contributions to domain-specific languages (67%), unmanned aerial vehicles (28%), and object-oriented programming (28%). Recent publications demonstrate a clear trajectory toward practical conservation applications, with increasing emphasis on ethical drone deployment, wildlife disturbance minimization, and operational safety in complex environments. Lundquist's work shows growing integration of swarm intelligence techniques with traditional conservation practices, particularly in African ecosystems as evidenced by field trials at Kenya's Ol Pejeta Conservancy. Lundquist actively leads multiple research projects including WildDrone (focusing on multi-perspective animal monitoring), Terra Salva (terahertz data transmission via drones), and a High Altitude Balloon platform for vegetation monitoring. His professional leadership includes chairing the ACM International Conference on Generative Programming Steering Committee (2019-2022) and significant roles in COST Action IC1405 (2015-2019). As a highly visible expert, he has contributed to 107 media appearances, frequently advising on drone policy including Denmark's regulatory approaches to drone safety and wildlife protection. As Head of the SDU UAS Center, Lundquist directs a multidisciplinary research team specializing in conservation drone technology. The center maintains strong international collaborations, particularly with African conservation organizations, focusing on developing drone swarm methodologies that balance data quality with minimal ecological disturbance. Current team efforts prioritize field-deployable systems that can operate effectively in remote natural habitats while providing conservationists with high-quality multi-perspective monitoring capabilities.
Samir Bhatt is a Professor of Machine Learning and Public Health at the University of Copenhagen's Faculty of Health and Medical Sciences, Department of Public Health, Section for Health Data Science and AI. He also holds a position as Professor of Statistics and Public Health at Imperial College London since 2016. His work focuses on developing mathematical, statistical, and computer science tools to address critical questions in human health. His educational background includes a DPhil in Statistical Genetics from the University of Oxford (2010), an MPhil in Computational Biology from the University of Cambridge (2006), and a BEng in Chemical and Bioprocess Engineering from the University of Bath (2005). Professor Bhatt's research spans the intersection of statistics, machine learning, and public health with particular emphasis on infectious disease modeling. His primary research areas include Bayesian inference, genomic epidemiology, and kernel methods applied to health data. His work bridges theoretical statistical approaches with practical public health applications, particularly in disease surveillance and outbreak response. The integration of AI with traditional epidemiological methods represents a key innovation in his research program. Analysis of his recent publications reveals a strong focus on applying advanced computational methods to pressing public health challenges. His work demonstrates consistent innovation in developing AI-driven approaches for infectious disease modeling, genomic surveillance, and survival analysis. Notable themes include the application of graph neural networks to epidemiological data, development of interpretable AI tools for public health decision-making, and sophisticated modeling of disease transmission dynamics across multiple pathogens including malaria, cholera, and respiratory viruses. Professor Bhatt has published extensively with over 107 research outputs to date. His work has received significant attention, with multiple publications covered by news outlets, referenced on social media platforms, and read by researchers on academic platforms like Mendeley. His research on AI for infectious disease modeling published in Nature demonstrates the high impact of his work in both academic and policy spheres. His research group at the University of Copenhagen appears to focus on developing computational tools for health data science, with particular emphasis on creating analytical frameworks that can be rapidly deployed during disease outbreaks. The development of GRAPEVNE (Graphical Analytical Pipeline Development Environment for Infectious Diseases) represents one such effort to create accessible tools for public health practitioners.
Jesper Havelund is a researcher at the Department of Biochemistry and Molecular Biology, University of Southern Denmark, specializing in metabolomics, mitochondrial biology, and metabolic pathways. His work integrates mass spectrometry and systems biology to study metabolic regulation in diseases like obesity, diabetes, and cancer. Research areas include metabolomics, mitochondrial dysfunction, and metabolic disease mechanisms Key projects: Nordic Metabolomics Society travel grant (2019-2020) Collaborations span neurology, endocrinology, and oncology research Recent publications focus on fructose metabolism in lung cancer, hepatic stellate cells in fatty liver disease, and mitochondrial adaptations in skeletal muscle. His work employs advanced metabolomic techniques to uncover novel therapeutic targets. Scientific awards include the Nordic Metabolomics Society travel grant. He utilizes liquid chromatography-mass spectrometry extensively in his research, with a focus on lipid and amino acid metabolism across multiple organ systems.
Ute Hahn is an Associate Professor at the Department of Mathematics, Aarhus University . Her research bridges Statistics, Biostatistics, and Neuroscience , with a focus on neurodegenerative diseases like ALS and advanced microscopy techniques . Research Interests: Statistical modeling in ALS and genetic research Stochastic geometry and spatio-temporal analysis Super-resolution microscopy (PALM, STED) Medical statistics and clinical epidemiology Functional data analysis and methodological innovations Selected Publications highlight her interdisciplinary work, including studies on ALS mouse models , microscopy artifacts , and spatio-temporal patterns in medical and environmental contexts . Collaborative Projects: Ute is actively involved in the MechanoGeometry research initiative, which began in 2022 and continues into 2023.
Hugo Daniel Macedo serves as an Associate Professor in the Department of Electrical and Computer Engineering at Aarhus University, where he leads research at the intersection of formal methods and cyber-physical systems. His primary institutional affiliations include the INTO-CPS initiative and the HUBCAP project, focusing on integrated toolchains for collaborative engineering design. His research spans critical domains in modern engineering: Digital Twins : Visualization frameworks, security architectures, and applications in autonomous systems (e.g., F1TENTH race cars) and sustainable infrastructure (floodwater management for Power-to-X) Formal Methods : Advancement of the Vienna Development Method (VDM), including tool integration with UML and Visual Studio Code Cyber-Physical Systems : Model-based design, co-simulation techniques, and lifecycle management for circular economy applications Analysis of his 2022-2024 publications reveals a strategic focus on operationalizing digital twins through formal verification, with significant contributions to floodwater resource systems and secure autonomous vehicle frameworks. His work consistently bridges theoretical formal methods with industrial applications, particularly in sustainable engineering contexts. Dr. Macedo actively supervises graduate students in digital twin implementation and formal verification methodologies, though specific advisee names are not publicly documented. His project leadership includes the EU-funded Digital Innovation HUBs initiative (2020-2022), which developed collaborative platforms for cyber-physical system design, securing substantial research grants for toolchain integration and security validation. He maintains active roles in the International Overture Workshop series as both contributor and proceedings editor, driving community standards for formal methods tooling. Current laboratory work centers on the INTO-CPS Application environment, where his team develops co-simulation frameworks for real-time digital twin deployment across automotive and environmental engineering domains.
