Zain Muhammad Mujahid is a PhD Fellow at the Department of Computer Science , University of Copenhagen (UCPH). His research focuses on Natural Language Processing with emphasis on Large Language Models (LLMs), bias detection, and fact-checking methodologies. Research Interests Factuality and bias prediction in news media LLM evaluation and error analysis Cross-lingual fact-checking systems Arabic-centric language modeling Evidence attribution in summarization AI safety in multilingual contexts Publications Zain's recent work addresses critical challenges in trustworthy AI, including automating error detection in NLG systems, developing cross-lingual bias detection frameworks (SAFARI), and creating benchmarks like Factcheck-Bench for evaluating automatic fact-checkers. His research also explores bilingual safety evaluation in Kazakh-Russian contexts and cultural adaptation of LLMs for Arabic language processing.
Asbjørn Marco Sinius Munk is a Research Fellow at the Department of Computer Science, University of Copenhagen , affiliated with the Pioneer AI (P1AI) research group. His work focuses on medical image analysis and domain adaptation in deep learning. Research Interests: Domain adaptation for medical imaging 3D MRI segmentation Foundation models in biomedical applications Self-supervised learning for brain imaging Deep learning frameworks for clinical data Recent research highlights include theoretical guarantees in domain adaptation (MDD-UNet) and alignment of 3D MRI with tabular data using CLIP-inspired models. His publications demonstrate strong applications of AI in healthcare imaging domains. Contact: asmu@di.ku.dk
Boel Nelson is a Tenure Track Assistant Professor at the Programming Languages and Theory of Computation section of the Faculty of Science , University of Copenhagen. Her research focuses on privacy, particularly differential privacy and metadata privacy, with applications in distributed computing, instant messaging, and automotive data systems.
Felix Björklund Osmark is an Lecturer at the Department of Computer Science , University of Copenhagen. His work is affiliated with the Machine Learning section and the SCIENCE AI Centre, focusing on interdisciplinary applications of artificial intelligence. Current research interests include quantum computing , natural language processing , and sustainable AI . Recent publications highlight hybrid quantum-classical systems, biomedical applications of machine learning, and ethical considerations in AI development. His collaborative efforts span domains like structural biology , climate science , and medical diagnostics , leveraging the department's compute cluster and TreeSense research center resources.
Thomas Risom Pedersen is an Instructor at the Department of Computer Science, University of Copenhagen. His work aligns with the Human-Centred Computing section, focusing on enhancing the relationship between computational technology and people, supporting well-being, innovating interaction methods, and exploring how technology influences human capabilities. The Department of Computer Science (DIKU) at the University of Copenhagen is organized into research sections such as Human-Centred Computing, Machine Learning, and Software, Data, People & Society. DIKU emphasizes collaborative, interdisciplinary research to address real-world challenges. Research in Human-Centred Computing at DIKU spans topics like: Designing technology to support human activities and well-being Inventing novel interaction paradigms Investigating the impact of computational systems on human capabilities The section maintains modern labs with advanced equipment, fostering a welcoming environment for diverse researchers. While no specific publications or awards are listed, his role involves contributing to teaching, research, and collaboration within the department.
Valkyrie Savage is an Assistant Professor (Tenure Track) in the Human-Centred Computing research section at the Department of Computer Science, University of Copenhagen (Faculty of Science). She is based at Sigurdsgade 41, 2200 København N. Her research focuses on the intersection of physical input devices, digital fabrication, and sensing technologies, with a particular emphasis on creating interfaces that adapt to specific user needs, contexts, and tasks. Savage's research interests center around physical input devices (such as mice, game controllers, and surgical tools) as bridges between humans and computers. She explores how sensing (digitizing physical information) and fabrication (physicalizing digital information) interact, with substantial work conducted in fabrication labs equipped with 3D printers, laser cutters, electronics tools, and CNC mills. Her methodology emphasizes systems research where projects produce functional, novel systems that users can interact with directly. Her work often involves creative fabrication projects, including 3D printing combined with crochet, underwater 3D printing applications, and laser-cut slot-together circuits. Analysis of her recent publications reveals a strong focus on advancing digital fabrication techniques, particularly in integrating electronics with physical structures, developing novel sensing approaches, and creating interactive systems. Her work spans from fundamental material science (wood filament pyrography, multilayer laser-cuttable materials) to applied human-computer interaction (tactile interfaces for maritime automation, adaptive sensing systems). A recurring theme is the development of techniques that allow for more integrated, functional, and context-aware physical-digital interfaces. Savage's research output demonstrates significant contributions to the fields of human-computer interaction, digital fabrication, and physical computing, with publications appearing in top-tier conferences including CHI, UIST, TEI, and DIS. Her work bridges theoretical advances with practical implementations, often resulting in novel tools, techniques, and systems that push the boundaries of what's possible in human-centered computing.
David Robert Shannon is an Instructor at the Department of Computer Science, University of Copenhagen. He contributes to teaching and research within the Machine Learning section, which participates in the SCIENCE AI Centre. University: University of Copenhagen Department: Department of Computer Science Section: Machine Learning His research interests span theoretical and applied machine learning, focusing on natural language processing, information retrieval, medical image analysis, computational biology, and quantum computing applications. He utilizes the department's powerful compute cluster for projects involving AI's environmental impact, quantum algorithms, and biomedical data modeling. Recent publications highlight work in quantum-inspired neural networks, sustainable AI, medical diagnostics, and cross-cultural computational frameworks. Key themes include ethical considerations in AI, hybrid quantum-classical systems, and multimodal data analysis. David collaborates with the Machine Learning section and SCIENCE AI Centre, leveraging resources like TreeSense for remote sensing and deep learning of global tree resources. The section's activities range from foundational research to applications in sustainability and biological data modeling.
Elias David Michael Theil is a PhD Fellow at the Department of Mathematical Sciences, University of Copenhagen, specializing in quantum mathematics and computational materials science. His research interests include: Quantum Algorithms Quantum Mathematics Materials Characterization Texture Analysis Metal Forming Processes Computational Mechanics Dr. Theil's work bridges theoretical mathematics with industrial applications, particularly in materials characterization and metal processing. His recent publications demonstrate strong interdisciplinary collaboration between mathematics and materials science, with papers appearing in Materials Characterization and Crystals . His research shows increasing impact, with his 2024 paper on metal forming modeling receiving 4 Scopus citations and his 2025 clustering algorithm paper gaining early attention in the field. Dr. Theil is based at Universitetsparken 5, Copenhagen Ø (DK-2100) and can be contacted at edmt@math.ku.dk.
Xenofon Fafoutis is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on the Internet of Things (IoT), wireless sensor networks, digital health, and embedded systems. He leads several projects including the DIREC Digital Community Building initiative and the eAI: Embedded AI initiative. His work emphasizes energy-efficient communication protocols, security in IoT, and the application of machine learning in edge computing. Key research interests include: IoT and Industrial IoT Wireless embedded systems and protocols Machine learning for edge devices Cybersecurity for sensor networks Wearable health monitoring systems Recent publications highlight his contributions to reinforcement learning-based scheduling, energy-efficient IoT protocols, and TinyML applications. He supervises PhD students in areas like embedded AI toolchains and predictive maintenance systems. His work aligns with UN SDG goals related to sustainable infrastructure and innovation.
Mads Brandbyge is a Professor in the Department of Physics at the Technical University of Denmark (DTU). His research focuses on electronic and thermal transport in nanosystems using quantum mechanical simulations, including molecular-scale contacts, carbon nanotubes, graphene, and nanowires. He develops computational methodologies and tools for atomistic modeling. He supervises and examines multiple PhD students, including Anaya Morales, Sørensen, Rosendal, and Zhao. His work contributes to the UN Sustainable Development Goals, particularly in advancing materials science and nanotechnology. Key research areas include quantum transport in 2D materials, electronic decoupling in graphene, and interfacial chemisorption in heterostructures. Recent publications highlight innovations in carbon nanostructures, topological materials, and nanoscale heat/charge modeling. Brandbyge organizes conferences and workshops on quantum transport, such as the 'Advanced school on Quantum Transport using SIESTA' and 'Tools for electron transport.' His research has been cited widely, with over 205 publications and collaborations across multiple countries.
Md. Tusher Mollah is a Researcher at the Technical University of Denmark (DTU), affiliated with the Department of Civil and Mechanical Engineering Digital Building Technologies. His primary research focuses on additive manufacturing, computational fluid dynamics (CFD), and material extrusion processes, particularly in construction and wind energy applications. He holds a PhD from DTU, completed in 2023, under the supervision of Prof. Jørgen Spangenberg and others. His work integrates CFD modeling to study material behavior during 3D printing, including fiber orientation in composites, layer stability in concrete printing, and resin infusion in wind turbine blades. He has contributed to projects like CFD Modelling of Material Extrusion Additive Manufacturing , exploring flow dynamics and extrusion parameters. His research also extends to optimizing composite structures for wind turbine blades and off-Earth construction frameworks. Awards: Otto Mønsteds Fond (2022), Symposium Best Papers at Solid Freeform Fabrication 2021, and Thomas B. Thriges Fond (2021 and 2022). Activities: Presented at conferences such as the European Conference on Composite Materials and the International Solid Freeform Fabrication Symposium. His lab and team collaborations emphasize interdisciplinary approaches to advancing additive manufacturing technologies for sustainable construction and renewable energy systems.
Lasse Jakobsen is a postdoctoral researcher at Aalborg University's Department of Health Science and Technology, Faculty of Medicine, specializing in biomechanics , slip resistance testing , and occupational safety . His work spans sports technology , friction analysis , and exoskeleton implementation in logistics environments. Education : PhD in Mechanical Engineering (Elastomer Friction) from Technical University of Denmark (2020), MSc in Sports Technology from unspecified institution (2016) Research focuses on footwear-surface interactions , exoskeleton biomechanics , and preventing occupational accidents . Recent work includes slip resistance testing for cheese warehouses and exoskeleton trials in logistics. His publications (26 total) and datasets demonstrate expertise in friction modeling and workplace safety . Scientific awards include recognition in 2016 (MSc) and 2023 (unspecified). Collaborations with industry partners like Sika Footwear and academic institutions address practical safety challenges in industrial and sports contexts.
Andreas Møller Jørgensen is an Associate Professor at Aalborg University's Department of Sociology and Social Work, affiliated with the SCOPAS research unit (Shaping Concepts, Practice and Advances in Social Work) within The Faculty of Social Sciences and Humanities. His research merges philosophy of technology with theories of democracy, focusing on core concepts like time, space, care, justice, and equality in social work practices. He employs qualitative methods including ethnography, interviews, and document studies to explore how technological innovations reshape social work and how power relations evolve in digitalized welfare systems. Key projects include ROSA (Robot Technologies in Social Work), investigating AI integration; SOMESO (Social Media and Algorithms in Social Work), analyzing digital tools' impacts; and CARE (Exploring relational practices in child welfare). He co-edited the 2023 book *Plads til omsorg i socialt arbejde med børn og familier*, emphasizing care as central to social work with vulnerable families. His research highlights tensions between neoliberal welfare systems and humanistic care practices, particularly in pandemic contexts and automated decision-making. He frequently collaborates with international scholars and participates in conferences addressing digital social work and democratic innovations. Media engagements include analyses of Denmark's welfare digitalization and ethical challenges in algorithmic child protection systems.
Thomas Roger Hilberth is an Associate Professor at the Aarhus School of Architecture , where he coordinates Research Lab 3: Emerging Sustainable Architecture and Teaching Program 2. With a PhD in architecture (2007) and a diploma from ETH Zurich (1998), his career spans academic roles, architectural practice, and humanitarian projects. Academic Staff, Aarhus School of Architecture Research Focus: War architecture, security architecture, sustainability, and India-specific design Co-founded Hilberth & Jørgensen Architects (2016–present) Research interests include the intersection of architecture with security dynamics, sustainable practices, and cultural/historical contexts. His work explores territorialization theories through philosophers like Deleuze and Foucault, with applications in post-earthquake reconstruction (e.g., Gujarat, India) and climate emergency responses. Scientific contributions span 17 publications, including peer-reviewed works on transparent solar cells (2008), security architecture (PhD thesis, 2007), and a 2021 book chapter on sustainable architectural pedagogy. Recent outputs (2013–2021) address global urban challenges, cross-cultural design, and editorial projects like the Architectural Guide of Jordan (2016). Awards : SIA membership (1998), Swiss Steel Construction Prize (1996) Education : PhD (2007), Dipl. Arch. ETH (1998), Eidgenössische Matura (1993) Humanitarian Work : 2001 earthquake project with Vastu Shilpa Foundation, Ahmedabad As a supervisor , he mentored students in sustainable architecture and contextual design. His research lab integrates technological innovation with cultural habitation studies, emphasizing mutual learning in foreign contexts (e.g., Studio Mumbai, 2017).
Rentian Zhu is a PhD Fellow in Economics at the Copenhagen Business School , specializing in Labor Economics and Innovation. They hold an MSc in Advanced Economics and Finance and a BBA in Economics. Education MSc in Advanced Economics and Finance, Copenhagen Business School BBA in Economics, The Chinese University of Hong Kong Technical Skills Python Stata R Rentian's research focuses on the digitalization of the Danish economy , analyzing its impact on jobs, firms, and households through economic modeling and data science methods like text classification and deep learning. Their work bridges traditional economic analysis with modern computational techniques to address complex socioeconomic challenges. Research Experience includes positions at Copenhagen Business School and Statistics Denmark. No scientific awards, students, or lab affiliations were explicitly mentioned in the provided text.
