Tobias Nordholm-Højskov is an Instructor at the Department of Computer Science , University of Copenhagen (DIKU). His research intersects machine learning with healthcare, sustainability, and quantum computing, focusing on theoretical foundations and applications in medical data analysis, climate-aware AI, and quantum systems. He is affiliated with the SCIENCE AI Centre and contributes to projects like QDarts (quantum dot array simulation) and TreeSense (remote sensing for environmental monitoring). His work spans diverse subfields, including Explainable AI for healthcare records Federated Learning in rare disease research Quantum-inspired neural networks Retrieval-Augmented Generation frameworks Environmental impact mitigation in AI
Dr. Rasmus Pallisgaard is a Lecturer at the Department of Computer Science ( DIKU ), University of Copenhagen. His work focuses on software systems, data management, and human-centric computing, with an emphasis on creating societal value through interdisciplinary collaboration and industry partnerships. Research interests include: Design and development of software systems Data management solutions Human-computer interaction Societal impact of computational technologies
Morten Risum Pedersen is a Lecturer at the Department of Computer Science, University of Copenhagen, where he contributes to academic and research initiatives. He is affiliated with the Human-Centred Computing section, which focuses on improving the relationship between computational technology and people through interdisciplinary research. The Human-Centred Computing section investigates how technology can enhance human well-being, innovate interaction methods, and study the impact of computational systems on human capabilities. The group emphasizes a collaborative and inclusive environment for research and teaching. Contact details: Email: mope@di.ku.dk
Aske Valdemar Petersen is a Lecturer at the University of Copenhagen , affiliated with the Department of Computer Science and the Department of Mathematical Sciences . He contributes to the Human-Centred Computing section, focusing on improving the relationship between computational technology and human well-being through innovative interaction methods. The Human-Centred Computing section emphasizes collaborative research and a supportive environment for understanding how technology influences human capabilities and activities.
Mads Presfeldt is a Lecturer at the Department of Computer Science (DIKU), University of Copenhagen. His work aligns with the Human-Centred Computing section, which focuses on enhancing the relationship between computational technology and people through research on well-being, interaction design, and human capabilities. University: University of Copenhagen Department: Department of Computer Science Position: Lecturer Email: mpre@di.ku.dk
Karl van Eeden Risager is an Instructor at the Department of Computer Science, University of Copenhagen, affiliated with the Human-Centred Computing section. His research intersects computational technology with human well-being, focusing on medical imaging and machine learning applications. University: University of Copenhagen Department: Department of Computer Science Role: Lecturer His work addresses non-reference quality assessment in synthetic brain MRIs, contributing to the field of human-computer interaction through medical AI innovations. Key research themes include computational modeling, image analysis, and human-centric machine learning systems. Recent publications, such as "Non-reference Quality Assessment for Medical Imaging: Application to Synthetic Brain MRIs" (2024), highlight his expertise in medical imaging evaluation and AI-driven healthcare solutions. This aligns with broader interests in technology-enhanced diagnostics and computational well-being.
Sofia Dahl is an Associate Professor in the Department of Architecture and Media Technology at Aalborg University's Technical Faculty of IT and Design. She leads research within the Media Cognition and Interactive Systems (MeCIS) group, specializing in Sound and Music Computing. Her work bridges computer science, psychology, and rehabilitation science to develop innovative auditory feedback systems for movement rehabilitation. Dr. Dahl earned her Doctor of Technology in Speech and Music Communication from KTH Royal Institute of Technology, completing her degree in 2006. She previously served as Visiting Associate Professor in Embodied Music Cognition at the University of Oslo from 2013 to 2018. Her research focuses on the intersection of music, technology, and human movement, particularly how auditory feedback can enhance motor learning and rehabilitation. She investigates embodied interaction, movement sonification, and the cognitive processes underlying musical performance and perception. Her work has significant applications in neurorehabilitation, particularly for stroke recovery, cerebral palsy treatment, and gait training. Analysis of her recent publications reveals a strong trend toward applying sound and music computing to clinical rehabilitation settings. Her research increasingly integrates artificial intelligence with movement analysis to create adaptive biofeedback systems that respond to patients' specific needs and progress. The work spans from fundamental research on movement fluency in musical performance to applied clinical studies with measurable patient outcomes. Best Student Paper Award (2024) Nomination - Best Posters (2024) 4th Prize in RehabWeek 2023 Best Poster Competition Best Use of Sound - Academic (2023) Dr. Dahl actively supervises PhD students and leads multiple significant research grants, including the HearWalk project (2023-2027) focused on sound-facilitated rehabilitation and MusAIc-move (2022-present) which uses AI-generated music to promote engagement in movement rehabilitation. She collaborates extensively with clinicians and researchers across Europe through the Nordic Sound and Music Computing Network. Her laboratory work combines motion capture technology, real-time audio processing, and user-centered design to create effective rehabilitation tools that have been validated in clinical settings with measurable improvements in patient outcomes.
Jens Mammen is an Adjunct Professor at the Department of Communication and Psychology , Faculty of Social Sciences and Humanities at Aalborg University . His work bridges Cultural Psychology , Mathematical Logic , and Epistemology , focusing on axiomatic foundations for cognitive categories and critiques of mechanistic psychology. Research Pillars : Cultural Psychology, Mathematical Modeling, Cognitive Theory, Epistemology Key Contributions : Development of a set-theoretic model of mind, integration of topological concepts in psychology, interdisciplinary dialogue with biology and mathematics Recent Publications (2017-2023) emphasize: Foundational challenges in psychological theory Mathematical frameworks for human-object relations Critiques of reductionism and computational models Exploration of 'soul' and consciousness in scientific contexts Media Engagement includes debates on academic integrity and public discourse, particularly around the 2013-2014 Helmuth Nyborg controversy. Methodological Envoi (2018) outlines guidelines for interdisciplinary empirical research in Scientia Danica . He actively presents at conferences on topics like axiomatics of category formation and the tension between theory-derived and ad-hoc models.
Liesanth Yde Nirmalarajan is a social work researcher at Aalborg University's Department of Sociology and Social Work, Faculty of Humanities and Social Sciences. They also hold an external appointment as Assistant Professor at VIA University College since 2018. Focus on digital technologies in child/family welfare Expertise in predictive risk modeling and algorithmic decision support Contributions to UN Sustainable Development Goals (SDG 1, 10, 16) Research spans: Interdisciplinary studies of digital welfare states Citizen involvement in algorithmic governance Ethical implications of AI in social work Co-production methodologies Public administration reform through digitization Recent publications (2023-2025) explore: Algorithmic decision-making in child welfare Participatory future workshops Digital exclusion in marginalized families Risk modeling ethics Power dynamics in digital social work
Jonathan Frederik Carlsen serves as a Clinical Associate Professor at the Department of Clinical Medicine within the Faculty of Health and Medical Sciences at the University of Copenhagen. His academic work is centered in the Radiology section, with research conducted at facilities located at Blegdamsvej 9 in Copenhagen Ø and Blegdamsvej 3 in Copenhagen N. With 37 documented research outputs, Carlsen maintains an active research profile with significant contributions to medical imaging and radiology. Dr. Carlsen's research interests span multiple critical areas in modern medical imaging, with particular emphasis on the integration of artificial intelligence into clinical radiology practice. His work explores innovative applications of imaging technology across various medical specialties including oncology, neurology, and women's health. He investigates both technical aspects of imaging modalities and practical implementation challenges in diverse healthcare settings worldwide. His research demonstrates a strong commitment to improving diagnostic accuracy, treatment planning, and clinical decision-making through advanced imaging techniques. Analysis of Carlsen's recent publications reveals a clear trajectory toward AI-assisted medical imaging with particular focus on tumor delineation, stroke assessment, and diagnostic workflows. His work bridges technical innovation with clinical applicability, examining how AI tools can be adapted to different healthcare contexts globally. The publications show consistent collaboration with interdisciplinary teams, suggesting an integrative approach to medical imaging research that connects technical development with practical clinical implementation. With numerous publications appearing in high-impact journals including Diagnostics, Neuro-Oncology Advances, and Journal of Medical Screening, Carlsen's research has garnered significant attention in the medical imaging community. His work on AI applications in radiology has accumulated multiple citations and substantial readership across academic platforms, indicating growing influence in his field. While specific details about his mentorship activities aren't explicitly provided in the available information, Carlsen's extensive collaborative research network suggests active engagement with students and junior researchers. His work appears to be conducted within the radiology research environment at the University of Copenhagen, involving interdisciplinary teams comprising clinicians, researchers, and technologists working at the intersection of medical imaging and artificial intelligence.
Laura Maria Alessandretti is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). Her research focuses on interdisciplinary topics such as human mobility, cryptocurrency investment networks, smartphone usage behavior, and socio-spatial segregation. She is actively involved in supervising PhD students and contributing to projects addressing sustainability science and urban dynamics. She holds an ORCID identifier (0000-0001-6003-1165) and can be reached at lauale@dtu.dk . Her work bridges computational methods with social sciences, particularly through large-scale behavioral data analysis. Key projects include studying air pollution's interplay with human mobility, computational approaches to cultural ecosystem services, and gender gaps in mobility patterns. She has contributed to datasets such as "Exposure to urban and rural contexts shapes smartphone usage behavior" (2023). Her research has been published in journals like Nature Computational Science , EPJ Data Science , and PNAS Nexus , with a focus on mobility science, cryptocurrency networks, and urban sociology.
Jakob Eyvind Bardram is a Professor and Head of the Digital Health Section at the Department of Health Technology at the Technical University of Denmark (DTU). His research focuses on mobile, wearable, and ubiquitous computing technologies applied to healthcare, including mobile sensing, human-computer interaction, and software architecture. Key application areas span clinical logistics, mental health monitoring, and digital phenotyping. He has led major initiatives such as the iHospital project (context-aware hospital systems) and MONARCA (mobile health solutions for bipolar disorder), co-founding companies like Monsenso and Cetrea. His work integrates technical innovation with clinical impact, supported by collaborations with hospitals and industry. Education: MSc and PhD in Computer Science Professional Affiliations: ACM, IEEE, Danish Academy of Technical Sciences (ATV) Editorial Roles: ACM PACM IMWUT, ACM Transactions on Computing for Healthcare Research emphasizes real-world deployment of health technologies, with contributions to cardiovascular risk assessment, behavioral activation systems, and frameworks like CARP Mobile Sensing. Awards include the 2012 Informatics Europe Curriculum Award for pervasive computing education.
Michael Mose Biskjær is an Associate Professor at Aarhus University's School of Communication and Culture, specifically within the Department of Digital Design and Information Studies. His research focuses on creativity support tools, design processes, and the role of artificial intelligence in design. He has led projects such as CIBIS (2014-2018) exploring blended interaction spaces and participated in a PhD project on avant-garde design processes (2010-2013). His research interests span AI in design, creative process analysis, and the impact of digital tools on creativity. Notable projects include studying surprise in design processes and the constraints imposed by digital tools. He has published extensively in journals like Design Studies and conference proceedings such as ECCE 2024. Biskjær has collaborated on interdisciplinary projects, combining design theory with human-computer interaction. His work often integrates longitudinal studies and technology probes to understand how ideas evolve in creative contexts.
Henning Christiansen is a Professor at Roskilde University's Department of People and Technology, affiliated with the Programming, Logic and Intelligent Systems (PLIS) research group. He is also a Knight/Chevalier of the Dannebrog (2018) and serves as Coordinator for International Student Exchanges in Computer Science, Informatics & Humanities-Technology Studies. His research spans Deep Learning for medical diagnosis, Robotics in theatrical performances, Constraint Logic Programming, Probabilistic-logic models, Natural Language Processing, Logical methods for context comprehension, Interactive art installations, Database query systems, Cultural technology projects like Viskbook. Key projects include SEAFACTS (digital maritime history platform), EXPLAIN-ME (explainable AI in medical education), NDH (cross-border health data collaboration). Publications highlight contributions to AI ethics, robot choreography, medical image analysis, constraint-based formal methods. He has supervised over 16 projects and 285+ activities, including international conferences and exhibitions. His photography has been displayed in Roskilde libraries and cultural venues.
Rob van der Goot is an Associate Professor in Data Science at the IT University of Copenhagen. His affiliations include the NLPnorth group and the Pattern Recognition Revisited lab . His research focuses on Natural Language Processing (NLP), with emphasis on language modeling, lexical normalization, and computational job market analysis. Key contributions include the development of the EEVEE annotation tool, studies on language model biases, and cross-lingual parsing techniques. He has received prestigious awards such as the Best Paper Award at W-NUT 2022 and the Outstanding Paper Award at EACL 2021 . His work spans projects like the Pioneer Centre for Artificial Intelligence (funded by the Danish National Research Foundation) and Multi-Task Sequence Labeling Under Adverse Conditions (funded by Amazon). His research also intersects with societal impacts, addressing bias in AI systems and improving NLP tools for under-resourced languages. Media engagements include discussions on AI adoption in Danish municipalities and business applications. His publications (48+) span topics from domain adaptation to large language model evaluation, emphasizing practical NLP solutions and reproducible research practices.
