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Oliver BaumannView profile

Professor

• Organization Theory
• Strategic Management
• Innovation Management
• +4 more

Oliver Baumann serves as Professor with special responsibilities at the Department of Business & Management within the Faculty of Business and Social Sciences at the University of Southern Denmark. He concurrently leads the Section Strategic Organization Design (SOD), driving research at the intersection of organizational theory, strategic management, and innovation processes. His research program investigates how organizations develop adaptive capabilities amid technological change and environmental uncertainty. Key contributions examine modular organizational designs, performance feedback systems, and collaborative search mechanisms in complex problem-solving contexts. Recent work increasingly addresses the integration of artificial intelligence and blockchain technologies into organizational structures, with empirical studies spanning platform ecosystems and news industry transformations. His scholarship bridges theoretical organization studies with practical challenges of technological adaptation across multiple sectors. Analysis of his publication trajectory reveals growing emphasis on computational approaches to organizational design, particularly regarding how algorithmic systems interact with human decision-making in dynamic environments. His 2023-2025 work shows heightened focus on AI-mediated collaboration, platform ecosystem dynamics, and adaptation mechanisms in disrupted industries like media and manufacturing. The consistent thread across his scholarship remains understanding how organizations balance exploration and exploitation under varying conditions of complexity. As head of the Strategic Organization Design section, Baumann directs research initiatives that connect with SDU's Digital Democracy Centre through investigations of technology-mediated collaboration and information ecosystem dynamics. His leadership role facilitates cross-disciplinary engagement with societal implications of digital transformation.

Daniel FürstenauView profile

Associate Professor

• IT Management
• Digital Health
• Digital Transformation
• +3 more

Dr. Daniel Fürstenau is an Associate Professor in Business IT at the IT University of Copenhagen and a part-time researcher at Charité - University Medicine Berlin . He is affiliated with the Einstein Center Digital Future and holds a PhD in Business Administration and Information Systems from Freie Universität Berlin . Prior to ITU, he served as Assistant Professor at Copenhagen Business School . Research Focus: IT Management, Digital Health, Digital Transformation, and Data Platform Governance Notable Projects: DICE (Digital Health in Circular Economy, EU-funded 2022-2026) Collaborations: Germany-based networks in Digital Health, Public Health Agencies, and Nursing Care Research Trends (2022-2023): 19 publications across digital health infrastructure, circular business models, symptom checker adoption, and data governance in healthcare. Key methodologies include scoping reviews, case studies, and maturity model development. Awards & Recognition: 2020 OCIS Best Paper Award Runner Up (Academy of Management) 2022 Best Associate Editor Track IS in Healthcare (ICIS) Leadership Roles: Foreperson of 2023 assessment committee for Information Systems Associate Professor recruitment at ITU

Jonas Valbjørn AndersenView profile

Associate Professor

• Data Science
• Machine Learning
• Big Data
• +6 more

Jonas Valbjørn Andersen is an Associate Professor at the IT University of Copenhagen within the Information Systems and Digital Innovation research group. His expertise lies in applying data science and machine learning to solve organizational challenges in healthcare systems, FinTech, and decentralized digital ecosystems. PhD in Information Systems and Management from Warwick Business School Focus areas: Algorithmic Decision Making, Blockchain Governance, and Complex Adaptive Systems His research leverages unstructured data from large registries, system logs, and open data sources, combining systems modeling with natural language processing and network analysis. Recent work emphasizes clinical decision support algorithms and decentralized platform ecosystems. Scientific contributions span blockchain dynamics, FinTech classification, and IoT data business models. Awards include the ECIS Best Research-In-Progress Paper Award (2019) , ECIS Outstanding Associate Editor Award (2022) , and the Warwick Doctoral Research Scholarship (2012) .

Peter RøgenView profile

Associate Professor

• Differential Geometry
• Structural Biology
• Protein Structure Prediction
• +3 more

Peter Røgen is an Associate Professor at the Department of Applied Mathematics and Computer Science , Technical University of Denmark (DTU). His research bridges Differential Geometry with Structural Biology , focusing on mathematical modeling of protein folding and structural descriptors. Develops low-dimensional metric maps for the protein universe Works on protein structure prediction from amino acid sequences Collaborates with companies via ESGI workshops on applied geometry problems Research Trends in his recent publications include geometric obstruction analysis , topological constraints in protein alignment, and mathematical optimization for structural refinement. His work combines knot theory, differential geometry, and computational biology to solve problems in protein structure modeling. He has supervised PhD projects on protein structure optimization and geometric knot theory, and participated in pump geometry design collaborations with engineering departments. His methodological contributions include Gauss integrals for conformational analysis and elastic curve modeling for structural comparison.

Troels AndreasenView profile

Associate Professor

• Computer Science
• IT
• Databases and knowledge bases
• +6 more

Troels Andreasen is an Associate Professor at the Department of People and Technology, Roskilde University. His research focuses on advanced query systems, artificial intelligence, and knowledge base modeling. Computer Science Databases and knowledge bases Fuzzy logic and quantities Intelligent search engines His work explores natural logic frameworks for database querying, flexible query answering systems, and intelligent information retrieval methods. Recent publications analyze computational intelligence for search systems and logic-to-database integration techniques. Notable projects include: SEAFACTS (2023-2025) - Digital platform for maritime history MemoryMechanics (2020-2023) - Memory systems research NorDigHealth (2019-2021) - Regional digital health solutions Kulturportalen (2014-2017) - Cultural heritage platform He has served on program committees at international conferences and participated in external organizations like University of Granada and Aalborg University. Media engagements highlight his expertise in search engine evolution and fuzzy logic applications since 2005.

Regina ChristiansenView profile

Research Fellow

• Qualitative Research
• Alcohol Use Disorder
• Eating Disorders
• +4 more

Regina Christiansen is a Postdoctoral Researcher at the Department of Clinical Research, University of Southern Denmark, with dual affiliations at the Research Unit of Psychiatry, Odense University Hospital, and the Center for Philosophy and Ethics of Health. Her work bridges clinical psychiatry, digital health innovation, and ethical frameworks in mental healthcare delivery. Her research program centers on: Qualitative investigations of alcohol use disorder and eating disorders using semistructured interviews Development and co-production of digital interventions including serious games (e.g., Maze Out) and blended iCBT-therapy models Ethical implications of algorithmic decision-making in healthcare systems Social dynamics of online interaction versus physical presence in therapeutic contexts Analysis of her recent publications reveals a methodological shift toward mixed-methods evaluations of digital mental health tools, with increasing emphasis on stakeholder co-creation processes. Her work on alcohol use disorder (Blend-A project) and eating disorders (Maze Out) demonstrates rigorous examination of implementation barriers while maintaining focus on patient autonomy and moral responsibility within therapeutic relationships. Scientific awards: No awards documented in the source material. Dr. Christiansen serves as Principal Investigator for the OTTiP project (Optimal Treatment Transition in Psychiatry) and Reduktion af Tvang (Reduction of Coercion), while co-leading the EAS project (Ethics and Algorithms in Health Care). Her grant portfolio demonstrates sustained funding for research at the intersection of clinical practice, digital innovation, and ethical governance. She operates within a robust collaborative network spanning University of Southern Denmark, Odense University Hospital, and international partners including Karolinska Institutet, with particular strength in multidisciplinary teams addressing complex mental health challenges through integrated clinical-ethical frameworks.

• Data Management
• Graph Algorithms
• Software Systems
• +3 more

Konstantinos Skitsas serves as an Assistant Lecturer and Visiting PhD Student at the Department of Computer Science, University of Copenhagen, affiliated with the Software, Data, People & Society (SDPS) section under Head of Section Dmitriy Traytel. His research focuses on data management systems and graph algorithms, specifically developing scalable techniques for subgraph matching and spectral filtering. This work addresses computational challenges in processing large-scale graph-structured data, with applications in social network analysis and pattern recognition. The SDPS section emphasizes interdisciplinary collaboration with industry to create software systems aligned with human and societal needs. His 2025 publication “Pilos” represents current work in graph processing efficiency, contributing to IEEE ICDE proceedings. The SDPS research environment actively explores topics like offline speech recognition and process discovery as indicated in section news. As part of the Department of Computer Science, he contributes to teaching while conducting PhD research within Copenhagen’s computational ecosystem, with office locations at Universitetsparken 1 (2100 Copenhagen Ø) and Sigurdsgade 41 (2200 Copenhagen N).

• Image Analysis
• Computational Modelling
• Geometry
• +3 more

Magnus Rahbek Dalgaard Hansen is an Instructor at the Department of Mathematical Sciences and a Visiting PhD Student at the Department of Computer Science, Algorithms and Complexity section, both at the University of Copenhagen. He works in interdisciplinary research areas including image analysis, computational modelling, geometry, and machine learning.

Marleen de BruijneView profile

Professor

• Medical Image Analysis
• Machine Learning
• AI in Radiology
• +6 more

Marleen de Bruijne is Professor of AI in Medical Image Analysis jointly appointed at the University of Copenhagen, Denmark and Erasmus MC – University Medical Center Rotterdam, The Netherlands. Within the Department of Computer Science at Copenhagen she belongs to the Image Analysis, Computational Modelling and Geometry section, where she leads research at the intersection of machine learning and medical imaging. Education MSc in Physics, Utrecht University, 1997 PhD in Medical Imaging, Utrecht University, 2003 Research Interests Her work centers on developing and validating machine-learning algorithms for quantitative analysis of medical images. Key themes include: Transfer learning and domain adaptation across imaging centers Deep learning architectures for segmentation and classification of pulmonary, cardiovascular and neuro images Probabilistic graphical models and Bayesian approaches for robust airway and vessel extraction Computer-aided diagnosis systems for emphysema, bronchiectasis, COPD and calcification Her group translates these techniques into clinical workflows to improve early diagnosis and patient management. Scientific Awards NWO-VENI (Netherlands Organisation for Scientific Research) NWO-VIDI NWO-VICI DFF-YDUN (Danish Council for Independent Research) Advising & Grants She has (co-)supervised 30 PhD students to completion and served as principal investigator on several large personal grants. Her funding record demonstrates sustained support from both Dutch and Danish national science foundations. Labs & Teams She is actively involved in the SCIENCE AI Centre at the University of Copenhagen and maintains strong collaborative links with Erasmus MC Radiology and Pulmonology departments, fostering cross-institutional datasets and multicenter clinical validation studies.

• Probabilistic Machine Learning
• Deep Probabilistic Programming
• Statistical Structural Bioinformatics
• +5 more

Thomas Wim Hamelryck is a Professor at the Department of Computer Science (Programming Languages and Theory of Computation) and the Department of Biology (Computational and RNA Biology) at the University of Copenhagen . With a PhD in Protein Crystallography from the Free University of Brussels (VUB), he specializes in Bayesian modeling , probabilistic machine learning , and statistical structural bioinformatics , focusing on protein structure prediction, evolution, and non-Euclidean data representation.

• Machine Learning
• Artificial Intelligence
• Information Retrieval
• +4 more

Adrián Avelino Sousa-Poza is a Researcher at the Department of Computer Science , University of Copenhagen, specializing in Machine Learning and its applications across diverse domains including Artificial Intelligence , Medical Data Analysis , and Quantum Computing . His research intersects with the SCIENCE AI Centre , focusing on both theoretical and applied aspects of machine learning. Recent work explores environmentally sustainable AI , quantum-enhanced models , and cross-cultural adaptation systems , reflecting his interdisciplinary approach. Key themes in his publications include large language models , quantum computing applications , and healthcare informatics , with a particular emphasis on interpretability , fairness , and hardware optimization in AI systems.

Mikkel AbrahamsenView profile

Associate Professor

• Computational Geometry
• Algorithms
• Complexity Theory
• +2 more

Mikkel Abrahamsen is an Associate Professor at the Department of Computer Science, University of Copenhagen. His research focuses on computational geometry and theoretical computer science, particularly in packing, covering, and partitioning problems. Education: MSc in Datalogi, University of Copenhagen (2013). His research interests include ∃ℝ-completeness , geometric algorithms , clustering , and online algorithm design . He has contributed to understanding the complexity of problems like PSPACE-hardness in geometric reconfiguration and polynomial-time solutions for star partitions . His recent work spans computational geometry , clustering optimization , and online sorting algorithms , with acceptance at top venues like FOCS, STOC, and SODA. His 2024 publications include advancements in unit square packing and geometric reconfiguration . Scientific awards include the Carlsberg Semper Ardens grant and the Sapere Aude research leader grant , highlighting his impact in theoretical computer science. He advises PhD students such as Florestan Brunck , Jack Stade , and Hanwen Zhang . His outreach has been featured in Inside Science , Atlas Obscura , and Danish media outlets like Ingeniøren and Datatech .

• Computer Science
• Algorithms
• Artificial Intelligence
• +3 more

Magnus Raabo Andersen serves as a Lecturer in the Department of Computer Science (DIKU) at the University of Copenhagen, based at Universitetsparken 1 in Copenhagen Ø. His role is integral to the department's academic operations within Denmark's largest university. His research spans foundational computer science domains, with emphasis on computational theory and practical applications. Key areas include: Algorithm design and optimization Artificial intelligence systems development Large-scale data analysis methodologies Software architecture and engineering principles Computational complexity theory Machine learning frameworks No documented scientific awards or honors are associated with his profile in available institutional records. Current information does not indicate active student supervision or externally funded research grants. His contributions appear focused on instructional responsibilities within DIKU's academic programs.

• Image Analysis
• Computational Geometry
• Computer Vision
• +3 more

Tore Ziegler Hougaard Andersen serves as a Lecturer in the Department of Computer Science (DIKU) at the University of Copenhagen. He is affiliated with the Image Analysis, Computational Modelling, and Geometry research section, which focuses on interdisciplinary work spanning theoretical algorithms to real-world applications in science and industry. His research interests derive from the section's core themes, including medical/biological imaging, computer vision, robotics, and mathematical geometry. The section actively contributes to initiatives like the SCIENCE AI Centre and collaborates with facilities such as Max IV and the Danish Bioimaging Network. DIKU provides robust infrastructure for this work, including high-performance computing clusters and specialized labs. While specific advising or grant activities for Andersen are unreported in the source material, the department emphasizes cross-sector collaboration through networks like the Pioneer Centre for Artificial Intelligence and MADE (Manufacturing Academy of Denmark).

• Computer Science
• Machine Learning
• Image Analysis
• +2 more

Caroline Helene Erslev Due is an Instructor at the Department of Computer Science, University of Copenhagen. She is affiliated with the Image Analysis, Computational Modelling, and Geometry section, which focuses on theoretical analyses, algorithm development, and applications in computer vision, geometric statistics, and machine learning. Her work contributes to solving concrete problems for science, industry, and society through computational methods. The department is part of the SCIENCE AI Centre, with expertise in areas including numerical optimization, computer simulation, and geometric modeling. Caroline's role involves teaching and research within these domains, supported by modern labs and computational resources. Contact: cadu@di.ku.dk