Matteo Acclavio is an Assistant Professor in Computer Science at the School of Engineering and Informatics, University of Sussex, affiliated with the Foundations of Software Systems (FoSS) research group. A logician specializing in proof theory and its applications to computer science, his work bridges mathematical logic with concurrency theory and process calculi. Education: PhD in Mathematics, Aix-Marseille University, France Master in Discrete Mathematics and Foundations of Theoretical Computer Science, Aix-Marseille University Master in Mathematics, Roma Tre University, Italy Bachelor in Mathematics, Roma Tre University His research focuses on graphical proof systems, linear logic, modal logic, and concurrency theory. Publications highlight contributions to deep inference, sequent calculus, and the intersection of logic with distributed systems. Recent work explores logical frameworks for concurrency, such as choreographic programming, and graphical models for proof systems. He teaches courses like Operating Systems and maintains active collaborations in theoretical computer science.
Christian Bergqvist serves as Associate Professor at the University of Copenhagen's Faculty of Law, affiliated with the Center for Business Law and Public Regulation. He teaches Danish-language courses 'konkurrence- og markedsføringsret' and 'Konkurrenceret', alongside English-language 'EC Competition Law', while supervising Master's and PhD theses in competition law domains. His academic foundation includes a PhD from the University of Copenhagen (2006), complemented by professional experience as Assistant Professor at Copenhagen Business School (2008-2010) and legal practice at Bech Bruun and Plesner law firms. Bergqvist's research centers on EU Competition Law applications within network industries (telecom, energy, transport) and digital markets. He examines sector regulation-competition law interactions, abuse of dominance frameworks, and economic theory integration. Recent scholarship increasingly addresses AI-driven collusion mechanisms and Big Tech regulatory challenges, particularly concerning FAANG companies. Analysis of his 2024-2025 publications reveals converging trends: algorithmic pricing collusion dominates current output, while traditional sector-specific competition law analysis remains prominent in regulated industries. His work bridges theoretical antitrust frameworks with practical digital market enforcement challenges. As an active graduate supervisor, Bergqvist mentors students through the University of Copenhagen's law programs. His institutional contributions occur primarily through the Center for Business Law and Public Regulation, where he engages in collaborative research on evolving competition law paradigms.
Peter Sestoft is a Professor at the IT University of Copenhagen (ITU), leading the Computer Science Department since 2017. His primary roles include academic leadership, research in programming languages and software engineering, and teaching. He holds a PhD in Computer Science from the University of Copenhagen (1991) and has held academic positions at institutions like the Royal Veterinary and Agricultural University and the Technical University of Denmark before joining ITU in 1999. His research focuses on programming languages, functional and managed object-oriented languages, parallel programming, compilers, and spreadsheet implementation technologies. He has developed influential tools like the C5 Generic Collection Library for C# and Moscow ML, a Standard ML implementation. His work on Funcalc and Corecalc advanced spreadsheet technology with user-defined functions and efficient recalculation algorithms. Key contributions include over 30 publications, including books on programming language concepts and Java/C# syntax. He has led major research projects such as 'Popular Parallel Programming' (P3) and 'Probabli' for actuarial calculations. His academic service includes roles on national grant committees and international conference organizing committees. Notable advising includes PhD students like Andrzej Wasowski (ITU Professor) and David Christiansen (Director of Haskell Foundation). His work has been recognized through grants exceeding 25 million DKK and collaborations with institutions like Microsoft Research and Harvard University.
Hjalmar Alexander Bang Carlsen is an Associate Professor at the Copenhagen Center for Social Data Science (SODAS), Faculty of Social Sciences, University of Copenhagen. He specializes in mixed digital methods and is deeply engaged in research and teaching related to digital data analysis, particularly in the context of political and civic participation on social media. He is a key contributor to the Social Data Science master's degree program. University: University of Copenhagen School: Faculty of Social Sciences Department: Copenhagen Center for Social Data Science (SODAS) Position: Associate Professor in Mixed Digital Methods Email: hc@soc.ku.dk ORCID: https://orcid.org/0000-0002-2638-0932 His research centers on mixed methods strategies for digital data, with a substantive focus on civic and political engagement via social media. Key areas include informal volunteering during crises, gender inequality in online political participation, and the use of large language models (LLMs) for qualitative interviewing. He leads three major projects: SoMeVolunteer (on crisis volunteering), public participation on Facebook, and AInterviewer (an LLM-based interviewing tool). The recent publications reflect a strong trend in digital sociology, crisis response, and methodological innovation. His work combines large-scale social media data with surveys, interviews, and textual analysis, emphasizing ethical and epistemological considerations in computational social science. Topics span from refugee solidarity and pandemic volunteering to framing contests among climate NGOs and gender disparities in digital political engagement. While no formal scientific awards are listed in the provided text, Carlsen is actively funded by the Velux Foundation and UCPH Data+, and his work is widely disseminated through media and academic outlets. He collaborates closely with researchers like Jonas Toubøl and Snorre Ralund, and his projects often involve interdisciplinary teams. He has secured seed funding for innovative methodological development, indicating strong grant-writing capacity. He is involved in public engagement, with multiple media appearances discussing Danish civic response during the pandemic and refugee crises. His research outputs include journal articles, book chapters, and a co-authored textbook on mixed methods. He also participates in workshops and public lectures, contributing to both academic and public discourse on digital society. Carlsen is affiliated with SODAS and the Social Sciences Datalab, indicating active involvement in data-intensive research infrastructure. His work on AInterviewer suggests leadership in emerging AI-driven qualitative methods, positioning him at the forefront of digital social research innovation.
Line Katrine Harder Clemmensen is a Professor at the Department of Mathematical Sciences, University of Copenhagen. She specializes in statistical modeling, machine learning, and AI, with emphasis on low resource domains, explainability, and fairness in health/life science applications. She co-founded Interhuman AI as Chief Scientific Officer and maintains an active research program across multiple disciplines. Statistical Modeling Machine Learning Explainable AI Fairness in AI Health/Life Science Applications Her recent publications (2024-2025) span computational biology, neuroscience, environmental science, and emotion recognition. Notable collaborations include interdisciplinary work in pediatric OCD analysis, fungal microbiome prediction, and facial emotion recognition systems. She actively explores fairness and scalability in AI models. Dr. Clemmensen holds 60 publications with significant impact across computational biology (40+ citations), neuroscience (68+ readers), and machine learning (20+ Scopus citations). She has been referenced in news outlets, blogged, and discussed across multiple social platforms.
Irena Vodenska is Professor of Finance and Director of Finance Programs at Boston University’s Metropolitan College, Department of Administrative Sciences. She holds a PhD in statistical finance and an MA in economics from Boston University, an MBA from Vanderbilt University, and a BS in computer information systems from the University of Belgrade. She is also a Chartered Financial Analyst (CFA) charter holder. Her research is at the intersection of finance, complexity science, and artificial intelligence, focusing on systemic risk modeling, ESG investments, and financial network dynamics. She has led major interdisciplinary research projects funded by the National Science Foundation, the European Commission, and the U.S. Army Research Office. PhD, Statistical Finance – Boston University MA, Economics – Boston University MBA – Owen Graduate School of Management, Vanderbilt University BS, Computer Information Systems – University of Belgrade Dr. Vodenska’s research interests include network theory in finance, systemic risk propagation, AI-powered ESG analysis, cryptocurrency price forecasting, and financial regulation. She employs big data, machine learning, and natural language processing to analyze financial news, market dynamics, and corporate sustainability. Her work investigates how climate disinformation spreads via social networks and influences public policy and governance. The recent articles highlight a consistent focus on modeling financial and economic systems using network science and AI. Trends include systemic stress testing, sentiment analysis in financial markets, cascading failures, and the interplay between macroeconomic indicators and financial networks. Her work spans econophysics, behavioral finance, public health economics, and ethical AI in fintech. National Science Foundation (NSF) research grant (2023) NSF EAGER Award (2014–2015) European Commission FET Open Grant (2012–2014) U.S. Army Research Office (ARO) Grant (2020–2021) MEXT Post-K Computer Grant, Japan (2016–2019) Alexander Hamilton Fulbright Fellowship (1994) Owen Graduate School Fellowship (1995–1996) Dr. Vodenska teaches core finance courses such as Investment Analysis and Portfolio Management, Derivatives Securities, and Financial Regulation and Ethics. She co-developed the MET AD 678 course with Professor Tamar Frankel from BU Law, emphasizing real-world case studies and ethical decision-making. Her research grants have supported innovative work in systemic risk modeling, AI for ESG, and financial network stability. She is actively involved in mentoring, conference organization, and editorial roles in leading journals. She is a key organizer of the International School and Conference on Network Science (NetSci) and the Big Data in Economics, Science, and Technology (BEST) Conference. Her lab and research team focus on complexity in financial systems, bringing together economists, physicists, computer scientists, and data analysts to study global financial stability and sustainability.
Professor Daniel S. Hain is an Associate Professor at Aalborg University Business School, part of Aalborg University's Faculty of Social Sciences and Humanities. He is affiliated with the IKE Research Group (AI for the People) and the MASSHINE Cluster for Research on Innovation and Development. His research focuses on innovation dynamics, artificial intelligence, network analysis, and technology forecasting. Hain has been actively involved in strategic initiatives such as the Danish Industry Foundation's AI Denmark program and the Generative Ethnographic AI (GE-AI) seed project, demonstrating his commitment to advancing AI applications in societal contexts. His work bridges academic research with practical industry challenges, particularly in areas like patent analytics (e.g., Patentsberta model), renewable energy innovation, and global venture capital patterns in developing economies. Hain has received the OECD IPSDM “Big Data Analytics” Challenge award (2018) for collaborative research on inventive activity visualization. He contributes to policy discussions on AI governance, the privatization of research talent, and regional green technology development. Key projects include the Danish Research Unit for Industrial Dynamics (DRUID) since 1995, exploring innovation systems, and the EIS project on energy innovation competitiveness. Hain’s recent focus on generative AI ethics and SME predictive analytics reflects his dual expertise in technical methodologies and socio-economic impacts.
Per Grau Møller is an Associate Professor in the Department of Culture and Language at the University of Southern Denmark, where he specializes in the spatial dimensions of history, particularly focusing on the Funen region and Northwestern Europe from 1000 AD to the present. His work emphasizes long-term landscape transformations, human imprint on cultural environments, and heritage preservation. Education: Master of Arts in History and Medieval Archaeology, 1984 (Odense and Århus Universities) Lic.phil. in History, 1988 (Odense University), thesis: From village to dormitory town. Rural settlements and their economic and cultural landscape preconditions on Funen ca. 1770–1965 His research interests include settlement history, landscape history, agricultural history, historical cartography, cultural heritage, and planning. He explores the interplay between nature and culture, particularly in rural and urban landscapes, with a focus on sustainable development and historical continuity. His recent publications (2022–2025) reflect a consistent engagement with manor landscapes, cultural environments, road networks in Viking and medieval Denmark, and the evolving perception of heritage. Themes such as agricultural transformation, historical land use, and the integration of heritage into modern planning are recurrent across his work, indicating a strong interdisciplinary approach bridging history, geography, and environmental studies. Scientific and Professional Engagement: Head, Changing Landscapes – Center of Strategic Studies in Cultural Environments, Nature and Landscape History (1997–2000) Head of History Studies (2008–2015) Chairman, Agricultural Society (2001–2009) Danish Representative, Permanent European Conference for the Study of Rural Landscape (until 2022) Member, COST-network A27 LANDMARKS (2004–2008) Board member of multiple historical and cultural societies, including the Historical Society for Funen, HisKIS, and Earth ESF-program He has supervised students and taught courses in Danish social and cultural history, historical methods, and medieval urban development. His advisory roles and public lectures highlight his commitment to knowledge dissemination and community engagement in heritage matters. Per Grau Møller is actively involved in research, teaching, and public outreach, contributing significantly to the understanding of Denmark’s cultural landscapes and their historical evolution.
Martin Elsman is a full-time Professor in the Programming Languages and Theory of Computation section at the Department of Computer Science, University of Copenhagen (DIKU). He serves as head of the PLTC section and head of studies for the BSc education in Computer Science and Economics. Elsman is also an active maintainer of several software tools including the MLKit and SMLtoJs. Joined DIKU in 2012 after 4 years at SimCorp (2008-2012) and previous Associate Professorship at IT University of Copenhagen (2003-2008). Co-developer of Futhark, TAIL APL compiler, SMLtoJs, and SMLserver. Education: M.Sc. in Engineering, Technical University of Denmark Ph.D. in Computer Science, University of Copenhagen (DIKU), supervised by Mads Tofte. Research Interests: Elsman works on programming language design and implementation, with a focus on functional programming, module systems, domain-specific languages for financial contracts, region-based memory management, compilation techniques for parallelism, program optimization, and static type systems. His work spans both theoretical and applied domains, including blockchain-based financial contract execution, web technology, and GPU programming using functional languages. Publication Trends: His recent articles focus on functional programming, array programming, parallelism, and memory management. Topics include region inference, type systems for data-parallelism, program optimization techniques, and domain-specific compilation for financial and quantum computing. He frequently collaborates with Troels Henriksen and others on tools like Futhark and MLKit.
Jonas Vinther is a Research Fellow at the Department of Computer Science , University of Copenhagen, specializing in Machine Learning and its intersections with quantum computing, medical data analysis, and sustainability. He is also an external PhD student in the Quantum Information Science & Technology program at the Niels Bohr Institute. Email: jonas.vinther@nbi.ku.dk , jonas.vinther@di.ku.dk Location: Universitetsparken 1, 2100 København Ø His research spans quantum machine learning , AI ethics , medical imaging , and environmentally sustainable AI , with recent publications on topics ranging from quantum neural networks to fairness in recommender systems . He contributes to the SCIENCE AI Centre and collaborates on initiatives like TreeSense for global tree resource monitoring.
Omry Ross is an Associate Professor at the Department of Computer Science, University of Copenhagen. His research focuses on Programming Languages and Theory of Computation, with significant contributions to decentralized finance (DeFi), blockchain technology, and algorithmic governance. Research Interests: Decentralized Finance (DeFi) and Smart Contract Systems Blockchain Protocol Design and Cryptoeconomics Programming Language Theory and Formal Verification Token Governance in Decentralized Autonomous Organizations (DAOs) Algorithmic Game Theory and Market Mechanisms Recent publications highlight his work in AI moderation of online communities, compliance reporting in DLT systems, and MEV optimization in multi-block scenarios. His research bridges theoretical computer science with practical applications in financial cryptography. Scientific Awards: Nasdaq Nordic Foundation Grant (2021) Omry Ross collaborates extensively with researchers in blockchain and DeFi, including contributions to the Financial Cryptography and Data Security workshops.
Lars Kayser is an Associate Professor at the Department of Public Health within the Faculty of Health and Medical Sciences at the University of Copenhagen. His research focuses on health informatics, digital health literacy, and innovative healthcare service design. He has over a decade of collaboration with international partners on developing the eHealth Literacy Questionnaire (eHLQ), now available in 18+ languages. Current projects include the Canada-European SMILE initiative for inclusive living environments and redesigning health services for aging populations. Key collaborations span Norway, Australia, and Canada, with ongoing involvement in studies like Epital TEMOKAP and Region Sjælland's Precare Project. He has contributed to national strategies for frail elderly care research in Denmark through high-impact policy articles. His work integrates clinical experience as an Internal Medicine specialist with expertise in web-based learning systems from leading educational development centers (2002-2009). Over 150 publications emphasize themes like technology readiness among elderly patients, patient empowerment through digital tools, and inclusive design for health technology. He actively participates in EU programs and international networks, advocating for user-centered healthcare innovation.
Ruben Niederhagen is an Associate Professor at the Department of Mathematics and Computer Science, University of Southern Denmark. His roles include affiliation with the Digital Democracy Centre and the VIP group in Artificial Intelligence, Cybersecurity, and Programming Languages. He holds external positions as Assistant Research Fellow at Academia Sinica (since 2022) and previously led the 'Advanced Cryptographic Engineering' and 'Post-Quantum Cryptography' departments at Fraunhofer SIT (2016–2020). He earned his PhD in Mathematics and Computer Science from Eindhoven University of Technology (2010–2012). His research focuses on cryptology, post-quantum cryptography, and embedded security. Key areas include quantum-resistant algorithms, cryptographic protocols, and hardware security implementations. His work addresses challenges like signature scheme optimization, electric vehicle cybersecurity, and quotable signature systems for data authenticity. Niederhagen has been featured in multiple media outlets discussing post-quantum cryptography’s role in future security. He teaches courses such as Cryptographic Engineering (DM886) and Networks and Cybersecurity (DM572). His research outputs span 33 publications, including book chapters and peer-reviewed conference papers, with a focus on practical implementations and theoretical advancements in cryptographic systems.
Dimitris Chrysostomou is an Associate Professor in the Department of Materials and Production at Aalborg University, Denmark. He leads the Robotics & Automation Group and directs the AI:Cybernetics Lab. His work focuses on developing safe, intuitive robotic systems for industrial and social contexts, emphasizing human-robot interaction (HRI), AI ethics, and collaborative robotics. Chrysostomou has over 15 years of research experience, funded by EU frameworks and national grants, with over 70 peer-reviewed publications. Education: PhD in Robot Vision (2013) and Diploma in Production Engineering (2006) from Democritus University of Thrace. He coordinates courses in robotics and manufacturing technology, emphasizing problem-based learning models. Administrative roles include heading the Robotics and Automation Group and the Aalborg Robotics Challenge steering committee. Research interests span AI-driven robotics, ethical implications of robot behavior, and HRI evaluation methodologies. Key projects include SAPIENT (2025-2027) for robotic intelligence and RIACT (2024-2025) on collaborative robot technology. Editor-in-Chief of *Industrial Robot* journal, IEEE Senior Member, and leader in euRobotics standardization initiatives. Notable contributions include virtual assistants for industrial robots, trust evaluation frameworks in HRI, and energy-based approaches for collaborative robotics. Active in conference organization, editorial roles, and industry collaborations, including co-founding AI startups.
Ivan Adriyanov Nikolov is an Assistant Professor at the Department of Architecture, Design and Media Technology within Aalborg University's Technical Faculty of IT and Design. He specializes in Computer Graphics, Computer Vision, and Augmented Reality, with a focus on 3D reconstruction techniques like Structure-from-Motion (SfM). His work bridges academic research and industrial applications, particularly in wind turbine blade inspection and educational technology. His educational background includes contributions to computer science education through innovative teaching methods. He has led projects like 'Drone Application for Pioneering Reporting in Wind Turbine Blade Inspection' (2017–2019) and 'Leading Edge Roughness - Wind Turbine Blades' (2015–2019), advancing drone-based inspection and 3D modeling for wind energy sectors. Research interests include synthetic data generation, environmental monitoring datasets (e.g., BrackishMOT, DigiWeather), and improving VR/AR user experiences. He has developed tools for dynamic lighting in pixel art games and multimodal guardian systems in VR. His datasets, such as Sewer Defect Point Clouds and Wind Turbine Blade SfM Reconstructions, are publicly available for academic use. He actively contributes to educational innovation, such as flipped classroom strategies to boost programming class engagement. His interdisciplinary approach spans computer graphics, AI-driven NPC interactions, and collaborative mixed-reality games for trust-building. Labs/Teams: Member of the Computer Graphics Group and Visual Analysis and Perception team at Aalborg University. Collaborates with industry partners on drone technology and environmental surveillance systems.
