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Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).

• Bioinformatics
• Machine Learning
• Deep Learning
• +5 more

Anders Søgaard is a Professor at the University of Copenhagen , affiliated with both the Department of Computer Science and the Department of Communication. His research bridges Natural Language Processing and Machine Learning with a focus on AI ethics , explainability , and human-AI interaction . Primary Affiliation: Department of Computer Science, University of Copenhagen Secondary Affiliation: Department of Communication, University of Copenhagen Email: soegaard@di.ku.dk, soegaard@hum.ku.dk Research Interests His work spans Natural Language Processing , Machine Learning , and AI ethics , with recent studies addressing: Trustworthiness in AI systems Explainable AI (XAI) frameworks Multilingual model fairness and alignment Human-AI collaboration in reasoning tasks Ethical implications of social robots Mental health analytics using ML Recent Publications His 2025 output highlights trends in: AI ethics (e.g., fairness metrics, trustworthy systems) Multilingual model analysis (knowledge retention, cross-lingual transfer) Human-centric AI (gaze data, cultural considerations) Applications in healthcare and social good

• Natural Language Processing
• Machine Learning
• Artificial Intelligence Ethics
• +3 more

Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.

• Efficient Machine Learning
• Deep Learning
• Embedded Systems
• +12 more

Alena Thiel is an Associate Professor at the Centre of African Studies within the Faculty of Social Sciences at the University of Copenhagen. Her research examines digital technologies' impact on state formation and knowledge systems across Africa, with primary field sites in Ghana, Senegal, Botswana, and Kenya. Her core research areas include: State knowledge systems (biometric ID, census histories, DHIS2 health records) Digital governance (addressing systems, payment solutions, disaster risk datafication) African/feminist AI development and implementation Anthropology of the state through Science and Technology Studies (STS) frameworks Recent publications (2024-2025) reveal concentrated analysis of health data infrastructures in Ghana, trust dynamics in Africa's global networks, and critical sociological examinations of digital identification. Her work consistently bridges anthropological theory with practical governance challenges in African contexts. As an active member of the Centre of African Studies, she maintains interdisciplinary collaborations across multiple African countries and European institutions, with particular emphasis on Ghanaian research partnerships and editorial leadership for Africa Spectrum journal.

• State knowledge systems
• biometric identification technologies
• census and census histories
• +13 more

Aage Hill-Madsen is an Associate Professor at the Department of Culture and Learning, Aalborg University (Denmark), affiliated with the Communication, Language, and Discourse (CLD) research unit. His work focuses on translation studies, medical communication, and systemic-functional linguistics. He holds a Cand.mag. et ling.merc. and a PhD in English linguistics. Research Interests: Translation theories (especially intralingual translation) Medical terminology simplification and communication Systemic-functional grammar applications Legitimation Code Theory in educational contexts Genre analysis of specialized texts Semiotic approaches to knowledge transmission Recent Publications Trends: His 2024-2025 work emphasizes medical translation between technical and lay audiences, with studies on EPAR summaries, patient information leaflets, and historical East-West medical terminology exchanges. He combines functionalist translation theory with systemic-functional frameworks to analyze textual transformations. Grants & Projects: Participated in the 2024-ongoing project Udvikling af kommunikative kompetencer gennem frivilligt brobygningsarbejde i NGO’en Social Sundhed , exploring communication skills through NGO activities. Academic Engagement: Active peer reviewer for journals like Globe and Across Languages and Cultures , with conference presentations on intralingual translation strategies and medical text accessibility.

• Translation Studies
• Medical Communication
• Systemic Functional Grammar
• +5 more

Desmond Elliott is an Associate Professor in the Natural Language Processing section at the Department of Computer Science, University of Copenhagen (UCPH). His research focuses on multimodal and multilingual models with specific emphasis on vision-language integration and tokenization-free NLP approaches. He teaches Bachelor and Master's level courses including Advanced Topics in Natural Language Processing (since 2019), Grundlæggende Data Science (since 2023), and previously Data Science (2021-2023). His research interests center on building and understanding multimodal and multilingual models , particularly exploring vision and language interactions through billion-parameter systems. Current work investigates cultural representation disparities in vision-language models, parameter-efficient captioning, and multimodal distributional semantics across diverse domains including food culture and medical imaging. His methodology emphasizes real-world applicability in non-English contexts and ethical considerations in multimodal systems. Elliott's recent publications (2025) demonstrate leadership in multimodal NLP, with significant contributions to vision-language pretraining, multilingual evaluation frameworks, and clinical NLP applications. His work spans theoretical advancements in model architectures and practical implementations addressing challenges in low-resource languages and domain adaptation. Best Long Paper Award at EMNLP 2021 Best Poster Award at COLING 2019 As an active educator, Elliott contributes to courses on Fair and Transparent Machine Learning and previously taught Information Retrieval. His research collaborations span international institutions with particular focus on European and non-English language contexts, reflecting UCPH's recognition as Europe's #1 institution for HCI research over the past decade.

• Multimodal Learning
• Multilingual NLP
• Vision-Language Models
• +4 more

Remus Teodorescu is a Professor at AAU Energy , Aalborg University , specializing in Power Electronics System Integration and Materials . His work bridges Lithium-Ion Batteries , Modular Multilevel Converters , and Smart Battery Systems . Education : Not explicitly mentioned in the text. Research Interests focus on Battery Management Systems , AI-Driven Energy Optimization , and Power Electronics for renewable energy integration. Key projects include Digital Twin for Lithium-Ion Batteries and BMS-DC for Data Centers . Recent Publications (2025) emphasize Finite Set MPC , Gradient Descent Optimization , and AI in Battery Parameter Estimation . His 2024 work explores Physics-Informed Neural Networks and Fault-Tolerant Converters . Scientific Awards : Villum Foundation Grant (313 million kroner, 2021) Named world's best in electrical engineering (2023) Advising includes supervising PhD projects on AI-Accelerated Battery Twins and Data-Driven SOH Estimation . Collaborations span Energy Cluster Denmark and Villum Fonden .

• Battery (Electrochemical Energy Engineering)
• Modular Multilevel Converter
• Lithium-Ion Batteries
• +6 more

Christian Geisler Asmussen serves as Professor of Strategic and International Management at Copenhagen Business School's Department of Strategy and Innovation. His research investigates competitive advantage, globalization, and multinational enterprise organization through formal modeling, game theory, and theories of the firm, with current emphasis on foreign location choices and global corporate social responsibility. Appointed after earning his PhD from CBS in 2007, he maintains active contributions to international business scholarship and executive education. His research portfolio centers on: Organization and Expansion of Multinational Firms Internalization Theory Game Theory applications Corporate Social Responsibility frameworks Foreign location decision-making Global CSR implementation challenges Analysis of his recent publications reveals a strategic evolution toward integrating sustainability into multinational operations, with 2024-2025 works examining global cities' role in reducing liability of foreignness, modular value chain design, and CSR orchestration mechanisms. His scholarship consistently applies game-theoretic approaches to multinational strategy while addressing emerging challenges in global governance and ethical operations. Recognition for his scholarly impact includes: Barry M. Richman best dissertation award Haynes Prize Tietgen Prize JIBS Decade Award Professor Asmussen supervises Cand.Merc. Master Theses and CEMS Business Projects while teaching Strategy, Contemporary Issues in International Business, Macroeconomics, and PhD-level Strategic Management. His external engagements include providing Strategic Risk Management training for Saxo Bank (2024) and serving as external accreditor for Cyprus' Higher Education Quality Assurance Agency (2024-2025).

• Organization and Expansion of Multinational Firms
• Internalization Theory
• Game Theory
• +3 more

Francisco Camara Pereira is a Professor and Head of Section at the Department of Technology, Management and Economics at the Technical University of Denmark (DTU). His research focuses on Intelligent Transportation Systems, Machine Learning, and Data-Driven Decision-Making in transportation contexts. He actively contributes to advancing transportation science through interdisciplinary approaches combining simulation, optimization, and AI techniques. His work addresses challenges in public transport analysis, charging infrastructure planning, and multimodal demand prediction. Recent projects include developing graph-based optimization methods for electric vehicle networks and causal discovery frameworks for transportation systems. He supervises multiple PhD students in areas like federated learning for cyclist safety, causal graph neural networks, and socially aware AI models. Key contributions include publications on smart card data analysis for travel surveys, stochastic infrastructure expansion models, and transfer learning for bike-share systems. His research aligns with UN Sustainable Development Goals related to sustainable cities and innovation. Dr. Pereira collaborates internationally on transportation policy and infrastructure projects. His lab focuses on translating theoretical advancements into practical solutions for urban mobility challenges.

• Intelligent Transportation Systems
• Machine Learning
• Active Learning
• +3 more

Mads Leth Jakobsen is an Associate Professor at the Department of Political Science , Aarhus University, specializing in Public Leadership , Leadership Development , and Bureaucracy and Debureaucratization . He serves as a member of the King Frederik Center for Public Leadership management team, focusing on leadership for public value creation and handling complex social challenges like the climate crisis. Academic Rank: Associate Professor Primary Research: Public Leadership, Distributed Leadership, Climate Governance Teaching: Public Leadership and Governance on political science programs Key Projects: Public Value Leadership (2022), Distributed Leadership (2012-2016) His research explores paradox leadership , organizational responses to climate challenges, and leadership credibility. Recent publications examine municipal climate strategies, bureaucratic dynamics, and leadership development frameworks. He emphasizes the interplay between leadership practices and employee outcomes in public sector organizations. Scientific awards and student supervision details are not listed in the available information. His articles highlight a strong focus on reconciling performance regimes with organizational learning, leadership credibility, and innovative governance models in public sector contexts.

• Public Leadership
• Leadership Development
• Bureaucracy and Debureaucratization
• +4 more

Arnav Arora is a PhD Fellow at the Department of Computer Science , University of Copenhagen (DIKU), specializing in Natural Language Processing . His work focuses on ethical AI, bias detection, and societal impacts of language models. Email: aar@di.ku.dk Location: Universitetsparken 1, 2100 København Ø Arnav's research explores fine-grained value alignment in language models, harmful content detection , and cross-cultural differences in AI responses. His work bridges technical NLP advancements with social responsibility, including dual use ethical frameworks and community value analysis . Key publication trends include: 2025: Bias mitigation through BiasGym framework 2024: Factcheck-Bench benchmark development 2023: Thorny Roses dual use analysis 2022: Cross-cultural value probing methods 2020: Multi-hop fact checking systems Arnav contributes to the Software, Data, People & Society (SDPS) section, collaborating with interdisciplinary teams on projects involving language model evaluation and societal impact mitigation . His work often addresses real-world AI deployment challenges through academic-industry partnerships.

• Natural Language Processing
• Machine Learning
• AI Ethics
• +5 more

Matias Thuen Jørgensen is an Associate Professor and head of the Center for Tourism Research at Roskilde University, Denmark, within the Department of Social Sciences and Business. His interdisciplinary research bridges business studies, sociology, and human geography to examine tourism's societal impacts, with empirical focus on Chinese tourism markets and Nordic destinations. He holds a PhD in Tourism Management from The Hong Kong Polytechnic University (2017), awarded through the competitive Hong Kong PhD Fellowship Scheme. His educational foundation combines rigorous academic training with field expertise in tourism phenomena. The PhD research at Hong Kong Polytechnic University established his methodological approach to analyzing tourism distribution systems through Activity Theory and Actor-Network Theory frameworks. Jørgensen's research critically examines tourism's role in sustainable community development, emphasizing how mundane everyday experiences create destination value in Nordic contexts. His work explores social value creation through tourist-resident interactions, regenerative tourism models like CopenPay, and the socio-economic implications of tourism transitions in peri-urban areas. Key themes include the ethical dimensions of tourism development, community mobilization through social entrepreneurship, and the complex interplay between tourism policy and local realities. Analysis of his 15 most recent publications reveals dominant trends in regenerative tourism frameworks, micro-level host-guest interactions, and policy responses to overtourism challenges. His scholarship increasingly focuses on climate-responsive tourism models, ethical pricing mechanisms in aviation, and regulatory approaches to short-term rentals, demonstrating consistent evolution toward solution-oriented sustainability research. Notable recognitions include: Hong Kong PhD Fellowship Scheme (2014) Nomination for Danish National University Teaching Award (2023) Peter Keller Award (2022) Roskilde University Teaching Prize (2022) Teacher of the Year Award, Roskilde University (2022) As principal investigator on seven research projects totaling over 3 million DKK in funding, Jørgensen has secured grants from diverse sources including industry partnerships and public research councils. Current projects include the SeNSE initiative on sustainable nature-based tourism entrepreneurship and the Tourism Business Model Tool development. He actively supervises doctoral research on social value creation in urban tourism encounters while contributing to policy formulation through UNWTO engagements and frequent media commentary. Leading the Center for Tourism Research (CFTR), he fosters cross-disciplinary collaboration between academics, industry stakeholders, and policymakers. His recent activities include organizing the 2025 Academy of Management symposium on tourism transitions and establishing the 'Tourism and Everyday Life in Cities' research network, positioning CFTR at the forefront of contemporary tourism scholarship.

• Tourism
• Sustainable Tourism
• Tourism Development
• +6 more

Ole Winther is a Professor at the Department of Biology, University of Copenhagen, specializing in Computational and RNA Biology. He also holds a joint appointment as Professor at DTU Compute, Technical University of Denmark. His research bridges machine learning, bioinformatics, and natural language processing with applications in biological sequence analysis, transcriptomics, and health informatics. Education: 1998: PhD in Physics, University of Copenhagen 1994: Master of Science in Physics, University of Copenhagen Winther's research focuses on developing advanced machine learning methodologies for biological applications. He has pioneered protein language models for sequence analysis (DeepLoc, SignalP, DeepTMHMM), interpretable deep learning for RNA subcellular localization, and benchmarking frameworks for DNA language models. His work spans latent variable models, variational inference, diffusion models, and novel architectures for deep generative modeling, with increasing emphasis on practical healthcare applications including rare disease diagnosis through findzebra.com and medical question answering with large language models. Scientific Recognition: ELLIS Fellow (2021) Head of ELLIS Copenhagen Unit H-index of 61 (Google Scholar, May 2023) 19,700+ citations (Google Scholar, May 2023) Winther has supervised 25+ PhD students to completion with 7 currently in progress, along with over 100 master's projects. He frequently serves as PhD opponent and committee chairman across European institutions. His research is supported by substantial funding including multiple Novo Nordisk Foundation grants totaling over 60 million DKK for the Center for Basic Machine Learning Research in Life Science and CAZAI projects, plus significant funding from the Danish Independent Research Fund. He leads an active research group developing cutting-edge machine learning approaches for bioinformatics and NLP challenges. Winther co-founded two spin-out companies: findzebra.com (2014, 2018), a search engine for rare diseases, and raffle.ai, an NLP startup for enterprise search. He initiated DTU's popular BSc in AI and Data program and teaches the highly enrolled MSc course in Deep Learning (450+ students) and PhD course in Bayesian Data Analysis.

• Machine learning methods development
• Bioinformatics
• Biological sequence analysis
• +8 more

Stephen Carney is a Professor (MSO) in Educational Studies at Roskilde University's Department of Humanities and Technology, where he has been based for over 20 years. An Australian by birth, he directs his research toward educational policy and comparative education. He serves as a key member of the Learning, Education and Pedagogy (LEAP) Research Center for Problem-Oriented Project Learning and previously served as head of studies for the University's Global Humanities bachelor program from 2018-2024. Carney earned his Doctor of Philosophy in Educational Studies from the University of Oxford in 2001, following a Master of Science in Educational Governance from the same institution in 1993. His academic journey began with a Master of Arts in Interdisciplinary Studies from UNSW Australia in 1990 and a Bachelor of Economics from The Australian National University in 1986. His research focuses on policy issues in higher education and schooling systems globally, with particular emphasis on university governance in Denmark and Europe, and school reform in the global south (primarily Nepal, India and western China). Carney has employed both policy analysis and ethnographic methods in his work. In recent years, he has explored methodological issues in education, particularly performative strategies for presenting schooling experiences. He served as president of the Comparative Education Society in Europe (CESE) from 2016-2022, demonstrating his significant standing in the international academic community. Analysis of Carney's recent publications reveals a consistent focus on comparative education, educational policy in a globalized world, and methodological innovations. His work frequently addresses the intersection of educational policy with cultural contexts, particularly examining how global educational trends are adapted in different national settings. A notable recent trend shows increasing attention to indigenous perspectives, reconciliation processes, and southern epistemologies in educational research. Book of the year (Shortlist): Globalization and Education Special Interest Group, Comparative and International Education Society, US (2022) George Bereday Prize for Most outstanding scholarly article published in the Comparative Education Review (2012) George Bereday Prize for Most outstanding scholarly article published in the Comparative Education Review (2009) Carney has served as principal investigator or participant in numerous research projects, including long-term initiatives on micro-credit financed entrepreneurial activities for women in Tanzania, local responses to global education reforms in Nepali primary schools, and comparative studies across Denmark, China and Zambia. His academic citizenship extends to review panels for new Master's programs and academic appointment committees. As an active researcher, he maintains collaborations across multiple countries and has recently engaged as a visiting researcher at the University of Modena Reggio Emilia.

• Educational Policy
• Comparative Education
• Higher Education Governance
• +5 more

Teis Hansen is a Professor of Innovation and Entrepreneurship at the Department of Food and Resource Economics , University of Copenhagen, with a side-position at SINTEF 's Department of Technology Management in Norway. His academic background includes a PhD in Economic Geography (2012) and an MSc in Regional and Urban Planning Studies (2008, LSE). His research spans innovation studies, sustainability transitions, and economic geography , focusing on spatial innovation dynamics, transformative policy, green urban development, foundational economy, and technology transfer between developed and emerging economies. Empirical work covers bioeconomy, energy-intensive industries, maritime transport, plastics, and energy systems. Recent collaborations include international partnerships in Norway, Sweden, and Denmark. His 112 research outputs include 63 journal articles, 9 book chapters, and policy-relevant reports. Key publications address climate change mitigation frameworks, carbon capture feasibility, and circular bioeconomy transitions .

• Innovation Studies
• Sustainability Transitions
• Economic Geography
• +4 more