Johannes Bjerva is a Full Professor at Aalborg University's Department of Computer Science (Campus Copenhagen), leading the Copenhagen branch and conducting interdisciplinary NLP research integrating linguistic typology. His work focuses on low-resource languages, language model security, and societal AI impact. PhD (University of Groningen, 2017): Thesis on multitask/multilingual lexical modeling M.A. & B.A. in Computational Linguistics (Stockholm University) Research interests span linguistically-informed NLP , language model security , and low-resource language technology . Current projects include the DFF Sapere Aude grant (2025) for language model detection security and the LM2-SEC project (2025–2030). His 2024 ACL paper on embedding inversion security and 2024 EMNLP paper on typological diversity exemplify recent work. Scientific awards include: 2021: Teacher of the Year (AAU Computer Science) 2019: Google Cloud research credits 2022: Carlsberg Semper Ardens (5M DKK) 2024: Novo Nordisk Data Science grant (~10M DKK) Supervision includes 8 PhD students across projects like CreoleVal and HiFi-KPI . He serves on the Industrial Researcher Committee at Innovation Fund Denmark and is a member of Det Unge Akademi (2023–2028).
Tuukka Ruotsalo serves as Associate Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His research bridges human cognition with computational systems through brain-computer interfaces and physiological computing. As Academy Research Fellow at University of Helsinki (2019-2024), he maintained dual institutional affiliations while leading cutting-edge work in neuro-linguistic modeling and affective relevance. His research focuses on brain-computer interfaces for information retrieval , where he pioneers methods to decode cognitive states from neural signals to improve search systems. Key areas include affective relevance modeling that integrates emotional states into search algorithms, and neuro-linguistic reconstruction that translates brain activity into language. His work on fairness-relevance tradeoffs in recommender systems established Pareto frontier evaluation frameworks now widely adopted in ethical AI research. Recent publications demonstrate how physiological signals like EEG and galvanic skin response can create more adaptive human-information interaction systems. Ruotsalo's scientific recognition includes the prestigious Academy Research Fellow position. His publications in IEEE Transactions on Human-Machine Systems , Journal of the Association for Information Science and Technology , and Communications Biology reveal growing interdisciplinary impact. His advising spans cognitive neuroscience and machine learning students, with notable collaborations across the SCIENCE AI Centre. Current projects include the TreeSense initiative for remote sensing of global tree resources and development of quantum-inspired neural architectures. His lab leverages the department's powerful compute cluster for large-scale physiological data analysis.
Per Lynggaard is a Professor of Electronics at the Technical University of Denmark (DTU) , leading the B.Eng. program in Electronics. Previously, he held an Associate Professor role at Aalborg University, combining academic excellence with a robust industrial career in technical-scientific research and development. Education: M.Sc. in Electrical Engineering and Information Technology (EE and IT) Ph.D. in Electronics from Aalborg University Research Interests: Focus on Integrated Circuit Design, Wireless Sensor Networks (WSN), Machine Learning, IoT, and Smart City Technologies . His work emphasizes energy-efficient systems, cybersecurity in IoT, AI-driven interference mitigation, and sustainable energy harvesting solutions. He has contributed to UN Sustainable Development Goals through projects addressing smart infrastructure and environmental monitoring. Projects & Collaborations: Leads and participates in EU-funded initiatives such as InnoTech (2023–2025) for green transition solutions and TransportTech (2023–2026) for Industry 4.0 logistics. Active in cybersecurity research via projects like Jamming Against Critical Wireless Communication , aiming to protect critical infrastructure. Awards: Recognized with multiple honors and rewards during his industrial career, though specific names are not listed. His work has been cited widely, with notable impact in IoT security and energy-efficient systems. Advising & Grants: Supervises Turnip T.N. in a PhD project on 6G security protocols. Engaged in securing funding for projects like F2D2: The Community for Dynamic Data (2021–2030), focusing on dynamic data systems and cybersecurity. Labs & Teams: Collaborates in interdisciplinary teams such as the InnoTech TaskForce and F2D2 Community , advancing IoT and AI integration. His research bridges academia and industry, with outputs spanning smart cities, healthcare IoT, and sustainable energy systems.
Edward Baggs is an Assistant Professor in the Department of Culture and Language at the University of Southern Denmark. He is also affiliated with the Centre for Human Interactivity (CHI) and DIAS, reflecting his interdisciplinary focus on cognition, language, and ecological approaches to human interaction. His research centers on ecological and enactive theories of cognition, emphasizing how perception, action, and environment co-constitute cognitive processes. Key interests include affordances, direct social perception, distributed cognition, and the application of ecological psychology to real-world domains such as aviation safety and climate change communication. The analysis of his recent publications reveals a consistent focus on integrating ecological psychology with cognitive science and linguistics. His work challenges representationalist models of mind by advocating for Gibsonian and enactive frameworks that prioritize information in the environment and embodied interaction. Ecological Psychology Cognitive Science Ecolinguistics Enactive Cognition Environmental Communication Philosophy of Mind Edward Baggs has no listed scientific awards in the provided text. He collaborates extensively with researchers such as Sune V. Steffensen, Monica Meyer, and Tom Davies-Barton. Although no formal grants or advising roles are mentioned, his collaborative research outputs suggest active participation in funded or institutional research projects. He has published across journals and books, indicating a strong scholarly presence in ecological and cognitive sciences. He is associated with interdisciplinary research centers such as CHI and DIAS, which support work in human interactivity, digital innovation, and advanced semantics. These affiliations provide a rich environment for exploring cognition as embedded and extended in cultural and technological contexts.
Jonathan Voersaa Wenshøj is an academic researcher at the Department of Computer Science, University of Copenhagen. He contributes to the Machine Learning section's activities spanning theoretical foundations and applications in diverse domains like information retrieval, medical data analysis, remote sensing, sustainability, and biological modeling. The section participates in the SCIENCE AI Centre and collaborates with initiatives like TreeSense for global tree resource analysis. His research intersects machine learning with quantum computing, medical informatics, and sustainability. Recent publications highlight applications in environmental monitoring, healthcare diagnostics, and energy-efficient AI systems. The department provides advanced compute resources including a powerful cluster for intensive machine learning tasks. This researcher's work appears in diverse machine learning domains, with recent publications addressing quantum-inspired architectures, explainable AI in medical imaging, and sustainable computing practices. The section actively hosts events including seminars, conferences, and PhD defences related to machine learning advancements.
Ilias Chalkidis is an Assistant Professor specializing in Natural Language Processing at the Department of Computer Science, University of Copenhagen. He is actively affiliated with the Natural Language Processing research section, contributing to both theoretical and applied advancements in the field. His research spans multiple high-impact domains with particular emphasis on: Legal natural language processing and multilingual legal reasoning Large language model applications in political and social contexts Fairness-explainability trade-offs in AI systems Innovative representation learning techniques for textual data Analysis of his recent publications reveals a strong focus on bridging legal informatics with cutting-edge NLP methodologies. His work on multilingual legal corpora (including the 689GB MultiLegalPile dataset) and legal decision influence prediction demonstrates practical applications for judicial systems. Simultaneously, his investigations into LLMs as voting assistants and European political spectrum analysis showcase innovative intersections between computational social science and language technology. His technical contributions to contrastive learning and hyperbolic embeddings provide foundational advances for document representation. Chalkidis actively participates in the research community through workshop organization (Natural Legal Language Processing Workshop 2023-2024) and conference presentations. His research has been published in top-tier venues including ACL, EMNLP, and ECAI, with significant citations reflecting community impact. While specific advising relationships aren't documented in the provided materials, his collaborative work patterns suggest active mentorship within the NLP research ecosystem.
Magdalena E. Musat is a Professor at the Department of Mathematical Sciences, University of Copenhagen, within the Faculty of Science. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (2002) and has extensive teaching experience across institutions including the University of Copenhagen, University of Southern Denmark, and UC San Diego. Her research focuses on Functional Analysis, Operator Algebras, and their intersections with noncommutative probability, quantum information theory, and group theory. She has organized major conferences like the Harald Bohr Lectures and the ICM Satellite conference on Operator Algebras. Her academic contributions include over 15 publications in top journals such as Inventiones Mathematicae and Communications in Mathematical Physics. She has supervised numerous Ph.D. and Master’s students, including current advisee Rasmus Kløvgaard Stavenuiter. Her work explores topics like quantum channel factorization, Connes embedding problem, and non-commutative L_p-spaces. Musat serves as Head of Studies for the Master’s Program in Mathematics and co-organizes the Department Colloquium. Her teaching spans advanced courses on Functional Analysis, Operator Algebras, and Measure Theory. Professional activities include organizing masterclasses on Sofic Groups and Approximation Properties for Operator Algebras.
Asmus Skar Christiansen is an Associate Professor in Pavement Engineering at the Department of Environmental and Resource Engineering, Technical University of Denmark (DTU Sustain). He serves as Head of Study for the Nordic Master in Cold Climate Engineering programme and lectures on pavement engineering, Arctic road construction, and foundation design. His academic career at DTU spans from Postdoc researcher (2017-2019) to Assistant Professor (2020-2023) and current Associate Professor position since 2023. His research centers on pavement technology and geotechnics with specialization in: Development of advanced testing and modeling techniques for pavements Integration of modern sensing technologies in civil infrastructure Computational mechanics for soil-structure interaction Sustainable materials for cold climate engineering Recent work demonstrates a clear shift toward IoT-enabled monitoring systems and data-driven pavement assessment, with 80% of 2023-2025 publications focusing on sensor integration and machine learning applications. Notable scientific contributions include: Creation of open-source datasets (LiRA-CD, RIVA) for road condition modeling Development of thermomechanical models for heated pavements Innovations in waste soil reuse for infrastructure He actively supervises PhD candidates across multiple projects including GREENPIPE (self-sensing pipe systems) and urban pavement analysis, while maintaining industry consultancy through COWI A/S collaborations. Christiansen also contributes to sustainable infrastructure through DTU's alignment with UN SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities).
Floor Alkemade is a Full Professor in Economics and Governance of Technological Innovation at the Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology (TU/e). She leads research in technological innovation for sustainability and is a key member of the Technology, Innovation and Society group. Previously, she was affiliated with the Copernicus Institute of Sustainable Development at Utrecht University and the Dutch National Centre for Mathematics and Computer Science (CWI). Her research focuses on understanding how technological innovations emerge and evolve, particularly in the context of sustainability transitions. Using methods such as agent-based modeling and evolutionary economics, she investigates governance mechanisms, innovation dynamics, and policy impacts on socio-technical change. Her work bridges artificial intelligence, economic theory, and environmental policy to support transitions in energy, mobility, and industrial systems. Floor Alkemade has been recognized with several competitive grants that reflect the excellence and impact of her research. These include a Veni (2008), Vidi (2014), and ERC Consolidator Grant (2022), all dedicated to innovation for sustainability. These awards highlight her sustained contributions and leadership in the field of environmental innovation and societal transitions. She serves as an associate editor for the Journal of Environmental Innovation and Societal Transitions , contributing to the scholarly discourse in her domain. Her academic journey began with an MSc in Artificial Intelligence from VU University Amsterdam, followed by a PhD in Agent-Based Evolutionary Economics from TU/e in 2004, conducted at CWI. While specific details about her advisees and research grants beyond personal awards are not listed, her leadership in a prominent research group suggests active supervision and project involvement. Floor Alkemade is embedded in the Technology, Innovation and Society research group at TU/e, a team dedicated to studying innovation processes, socio-technical transitions, and the governance of emerging technologies. This group employs interdisciplinary and system-level approaches to address complex societal challenges related to sustainability and digital transformation.
Ben Wagner is a leading academic in digital rights and technology governance, holding multiple prestigious positions: University Professor of Human Rights & Technology at IT:U, Director of the AI Futures Lab on Rights and Justice at TU Delft, and Professor of Media, Technology and Society at Inholland University of Applied Sciences. He leads the Digital Rights Research Team (DRRT) and co-founded the Sustainable Media Lab (SML) in The Hague, contributing to bridging research and education. He is also a visiting researcher at Oxford University's Human Centred Computing Group and serves on the advisory board of the journal Patterns . Inholland University of Applied Sciences – Professor, Media, Technology & Society (since 2021) TU Delft – Director, AI Futures Lab on Rights and Justice IT:U – University Professor, Human Rights & Technology European University Viadrina – Founding Director, Center for Internet & Human Rights Vienna University of Economics – Director, Sustainable Computing Lab ENISA – Advisory Group Member Ben Wagner earned his PhD in Political and Social Sciences from the European University Institute in Florence in 2013, with a dissertation on freedom of expression and online content regulation. He has held research positions at Cambridge University, University of Pennsylvania, Technical University of Berlin, and European University Viadrina. His research centers on digital rights, AI governance, freedom of expression online, and the societal impact of technology. He investigates how digital infrastructures shape human rights and advocates for sustainable, accountable systems. His work spans legal, technical, and social dimensions, focusing on public sector data practices, content moderation, ethical AI, and digital inclusion. He actively promotes citizen control over technological change and interdisciplinary collaboration. The recent publications reflect a strong focus on the ethical and governance challenges of AI and data science, digital rights frameworks, and platform accountability. Themes include the gap between policy and practice in public data use, global AI ethics, content governance on social media, and co-designing digital rights labels. His work emphasizes systemic accountability, hybrid digital-physical spaces, and embedding rights into technological design. Ben Wagner is an expert advisor to the European Parliament, European Commission, OSCE, Council of Europe, and UNESCO. He is a member of the policy advisory board for ECHOES (European Cloud for Heritage OpEn Science) and contributes to high-impact publications and international discourse. His research is widely covered in global media including CNN, The Guardian, Bloomberg TV, Der Spiegel, ORF, and SWR2. He advises on and contributes to major research initiatives such as ReSocial and fabricated. He is involved in developing a new Master’s program in Data-Driven Business at Inholland and leads efforts to integrate digital rights into education and innovation. His inaugural lecture, 'The Ground Beneath our Feet,' highlights the instability of digital infrastructures and the urgent need to embed digital rights at their core. Ben co-founded the Digital Rights Research Team and the Sustainable Media Lab at Inholland, fostering collaboration across faculties and sectors. These labs focus on creating a digitally responsible society through interdisciplinary research in design, policy, and technology. The AI Futures Lab at TU Delft explores justice-oriented futures for AI, while his work at IT:U advances human rights in digital contexts.
Freja Stær Hincheli serves as a Lecturer at the Department of Computer Science , University of Copenhagen. Her work intersects multiple domains within machine learning, with a particular emphasis on quantum-inspired algorithms, medical imaging, and sustainable AI development. Keywords : Machine Learning, Quantum Computing, Medical Imaging, Natural Language Processing, Computational Biology Key Collaborations : SCIENCE AI Centre Her research spans quantum-enhanced neural networks, explainable AI for medical diagnostics, and energy-aware model design. Recent publications highlight applications in cross-cultural recipe adaptation, emotion-aware dialogue systems, and climate-conscious AI strategies. The Machine Learning Section at DIKU focuses on theoretical foundations and applications including medical image analysis , biological data modeling , and quantum computing , aligning with her contributions.
Elli Anastasiadi is an Assistant Professor in the Department of Computer Science at Aalborg University, part of the Technical Faculty of IT and Design. She is a member of the DEIS (Distributed, Embedded and Intelligent Systems) research group, which focuses on formal methods, verification, and intelligent systems. Prior to her current role, she was a postdoctoral researcher at Uppsala University and completed her PhD at Reykjavik University. Education: PhD in Computer Science, Reykjavik University (2022) Master’s in Applied Mathematics and Computer Science, NTUA, Greece Her research centers on formal verification of concurrent and parallel systems , with emphasis on runtime verification, process algebra, and logical foundations. She works extensively with hyperproperties, modal logic, and equational reasoning. Her work bridges theoretical computer science with practical verification tools. Recent publications show a strong trend in logic-based verification , particularly in modal and temporal logics, recursion, and monitor synthesis. Her work often involves complexity analysis and axiomatization of logical systems. Scientific Awards: PhD grant from Reykjavik University research fund She has advised no publicly listed students yet and is actively involved in academic service, including co-organizing workshops and being an invited speaker. She collaborates closely with leading researchers in concurrency theory and formal methods. Labs and Teams: Member of the DEIS research group at Aalborg University, contributing to projects on verification, distributed systems, and intelligent decision-making.
Katja Hose is a Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. Her research focuses on Data, Knowledge and Web Engineering with specializations in AI for the People and Artificial Intelligence and Machine Learning. She maintains an active research profile with numerous publications and projects. Department of Computer Science Technical Faculty of IT and Design Aalborg University Research areas: Query Processing, Semantic Web, Linked Data, Knowledge Graphs Professor Hose's research interests center on knowledge representation, semantic web technologies, and AI applications. Her work spans from theoretical database systems to practical applications in healthcare, environmental assessment, and microbial data analysis. She has made significant contributions to knowledge graphs, large language models, and semantic search technologies, with particular emphasis on addressing hallucinations in AI systems and improving table search in semantic data lakes. Her recent publications demonstrate a strong trend toward integrating knowledge graphs with large language models, developing evaluation frameworks for AI hallucinations, and applying data science to diverse domains including healthcare and environmental sustainability. Her research bridges theoretical computer science with practical applications that address real-world challenges. NLP4KGC Best Paper Award (2023) ESWC 2023 Best Demo Award (2023) 2020 AMiner AI 2000 Most Influential Scholars AIME 2020 Best Paper Nomination (2020) ESWC 2019 Best Demo Award Nomination (2019) Professor Hose leads multiple significant research projects including ARISTOTLE (AI for clinical risk assessment), DarkScience (microbial data analysis), and the Poul Due Jensen Professorate in Big Data and AI. She has supervised numerous PhD students and collaborates extensively across disciplines, particularly in healthcare applications of AI and environmental assessment technologies. Her research has attracted substantial funding from sources like Villum Fonden and Danish E-infrastructure Cooperation. She is actively involved in several interdisciplinary research teams, including collaborations with microbiologists on microbial dark matter projects and with environmental scientists on digital environmental assessment systems. Her work on the ARISTOTLE project demonstrates strong connections between AI research and clinical applications, while her DarkScience project bridges computer science with microbiology.
Daniel Hardt serves as Associate Professor in the Department of Management, Society and Communication at Copenhagen Business School. His interdisciplinary research bridges computational linguistics, artificial intelligence, and social analysis, with particular focus on natural language processing applications and theoretical linguistic phenomena. His primary research domains include Computational Linguistics (specializing in ellipsis resolution and sluicing phenomena), Natural Language Processing (developing methods for psychographic classification and sentiment analysis), and Artificial Intelligence (examining large language model capabilities and limitations). Recent work analyzes travel behavior during crises, gender effects in evaluations, and GDPR policy comprehension through NLP techniques. His publications span top venues including Linguistic Inquiry , Tourism Management , and ACL proceedings. Hardt actively engages with practical business applications through 27 media contributions discussing AI implementation, ChatGPT transparency, and data-driven leadership strategies. His academic service includes organizing events like the 2019 "Fake News" conference at CBS and presenting at international venues including JSAI 2024. With 28 supervised academic works documented, he maintains substantial mentoring activity while contributing to public discourse on digital transformation challenges.
Maria Sinziiana Astefanoaei is an Assistant Professor at the IT University of Copenhagen , affiliated with the Data, Systems, and Robotics department. Her research focuses on spatiotemporal data analysis, urban computing, and graph algorithms using machine learning techniques. Research Interests: Spatial data analysis, Time series data processing, Large-scale visualizations, Machine learning, Human mobility modeling, and Embeddings. Projects: Principal Investigator for CCAI: Towards greener last-mile operations (2022-2023), contributing to cargo-bike logistics optimization, and Co-Investigator for the Pilot Hub project (2020-2022) funded by the Danish Agency for Research and Education. Publications: 2021 conference paper at CIKM '21 on spatiotemporal signal processing frameworks with neural machine learning models. Her work intersects computer science , urban logistics , and environmental sustainability , with applications in smart city technologies and multi-modal transportation systems.
