Jan Østergaard is a Full Professor in Information Theory and Signal Processing at Aalborg University's Department of Electronic Systems. He leads the AI and Sound research section and directs the CASPR center. His expertise spans AI-driven acoustic signal processing, information theory, and EEG signal analysis. Østergaard holds a M.Sc. from Aalborg University and a PhD (cum laude) from Delft University of Technology. Major awards include the Danish Young Researcher’s Award and a EURASIP Best Thesis honor. His work focuses on speech enhancement, sound zone technologies, and neural tracking of auditory attention. Recent research emphasizes low-latency speech transmission, deep learning for sound field control, and robust voice activity detection. He serves on editorial boards and national committees, advancing Denmark’s sound technology initiatives. Education: M.Sc. (Aalborg, 1999), PhD (Delft, 2007) Research interests emphasize practical AI applications in sound systems, including hearing aid improvements, data-efficient acoustic modeling, and feedback control in networked systems. Over 210 publications and 17 active projects reflect his interdisciplinary impact across academia and industry.
Trine Krogh Boomsma is a Professor in the Department of Insurance and Economics at the University of Copenhagen's Department of Mathematical Sciences. Her research focuses on optimization under uncertainty with significant applications in energy systems, particularly electricity markets, renewable energy investments, and power system planning. PhD in Mathematics-Economics, Aarhus University (2003-2007) Visiting PhD at University of Duisburg-Essen (2004) Academic career includes positions at Risø National Laboratory for Renewable Energy and Imperial College London Her work spans stochastic programming, real options analysis, and dynamic programming to address energy sector challenges. Key areas include support schemes for renewables, market risk modeling, and operational optimization of hybrid conventional-renewable systems. Recent research explores policy impacts on investment decisions and advanced scenario generation techniques. Major publications (2012-2020) cover renewable energy policy frameworks, power plant valuation models, and sequential market bidding strategies. These works emphasize electricity market dynamics, investment risk quantification, and robust planning under uncertainty. She teaches linear programming, integer programming, and stochastic programming applications in operational analysis, contributing to energy economics education at the department.
Peter Brodersen is a Professor at the Department of Biology, University of Copenhagen , specializing in Bioinformatics and RNA Biology . His research focuses on RNA modification (m6A), YTHDF proteins, and small RNA pathways in plants. Recent research trends from his group include: (1) molecular mechanisms of ARGONAUTE-small RNA interactions, (2) m6A-YTHDF regulatory systems in plant development, and (3) RNAi-independent roles of DICER-LIKE proteins in antiviral defense. Collaborations span Denmark and international institutions. Publications highlight cross-disciplinary work bridging computational biology and experimental plant genetics. Key subfields include RNA structure, epigenetic regulation, and antiviral immunity.
Amartya Sanyal is a Tenure Track Assistant Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Machine Learning. He also serves as an Adjunct Professor at the Indian Institute of Technology Kanpur (2023–2025). His research focuses on critical areas of AI safety, data privacy, and robust learning. University: University of Copenhagen Department: Department of Computer Science Academic Rank: Assistant Professor Adjunct Role: IIT Kanpur (2023–2025) His work addresses challenges like differential privacy , data poisoning attacks , machine unlearning , and robust mixture learning . Recent publications analyze privacy-preserving techniques for large language models, fairness in collective action algorithms, and certified data release mechanisms. Amartya has received the Villum Young Investigator Award (2025). His research outputs emphasize online learning , adversarial robustness , and privacy-utility tradeoffs through rigorous theoretical frameworks and practical implementations. Scientific Award: Villum Young Investigator Award His collaborations span institutions like IIT Kanpur and involve interdisciplinary projects with industry partners. Current activities include talks on privacy with correlated data and machine unlearning advancements.
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
Pepa Kostadinova Atanasova is a Tenure Track Assistant Professor in the Natural Language Processing Section of the Department of Computer Science , University of Copenhagen. She co-leads the CopeNLU group with Isabelle Augenstein and has special teaching duties for industry practitioners. Research Interests: Interpretability of Language Models Explainability Methods Factuality in Language Models Parametric Knowledge Analysis Human-AI Alignment Trustworthy AI Scientific Awards: Marie Skłodowska-Curie Fellowship ELLIS Best PhD Thesis Award Informatics Europe Best PhD Thesis Award Collaborations: Active in interdisciplinary research, including partnerships with Meta and Google, and a postdoctoral project combining language model explanations with trading behavior analysis.
Allan Larsen is a Professor and Deputy Head of Division at the Department of Technology, Management and Economics (DTU Management) at the Technical University of Denmark. He heads the Operations and Supply Chain Management Section. His academic background includes an MSc in Applied Mathematics and a PhD in Operations Research, both from DTU. He teaches courses in Operations Management and Simulation at both undergraduate and graduate levels. Research Focus: His work applies operations research methodologies to complex planning problems in supply chain management, logistics, healthcare operations, and public transport. Key areas include urban freight transport, healthcare supply chains, and optimization of public transport resources like crew and fleets. Collaborations with industries, especially in freight transport, have been extensive. He previously co-directed the Transport DTU research center and co-chaired Denmark’s Transport Innovation Network. Education: MSc in Applied Mathematics (1989–1995), PhD in Operations Research (1997–1999), both from DTU. Recognition: Recipient of the Hedorf’s transportpris award in 2022 for contributions to transport research. Research Projects: Supervises multiple PhD students (e.g., on electric freight transport, healthcare resource optimization, and Industry 4.0 applications). Active in projects like 'Pioneering Electric Heavy-Duty Freight Transport' and 'Resource optimization in healthcare.' Labs/Teams: Leads the Operations and Supply Chain Management research group and collaborates in initiatives like the Transport Innovation Network, focusing on sustainable transport solutions.
Jan Madsen is a Professor at DTU Compute, Technical University of Denmark, and Head of the Embedded Systems Engineering section. His research focuses on system-level modeling and design of embedded computing systems, particularly cyber-physical systems, microfluidic biochips, and synthetic biology applications. Develops design automation tools and methodologies for embedded systems Supervises numerous PhD students and leads major research projects Research Interests Key areas include: Embedded systems-on-a-chip Cyber-Physical Systems (Internet-of-Things) Microfluidic Lab-on-Chip devices Synthetic biology with molecular computing Design, modeling, and optimization of complex systems Scientific Awards DATE Fellow (2019) IEEE CEDA Outstanding Recognition (2019) DTU Scientific Advise Award (2013) Best Paper Awards at MECO (2013) and CASES (2009) Jorck’s Foundation Research Award (1995) Publications His 14+ journal papers and 115+ conference papers demonstrate expertise in: SystemC-based modeling frameworks Energy-aware sensor networks Self-healing eDNA architectures Microfluidic biochip synthesis RTOS modeling and MPSoC exploration
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.
Getachew Agmuas Adnew is a Postdoctoral Researcher in Forest and Landscape Ecology at the Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen. His research focuses on isotope geochemistry applications to understand climate-relevant processes in extreme environments. Dr. Adnew's research interests center on isotope geochemistry , particularly clumped isotope measurements to investigate methane dynamics beneath the Greenland ice sheet and atmospheric CO 2 composition. His work bridges glaciology, atmospheric science, and climate change research, with significant contributions to understanding subglacial biogeochemical processes. He also participates in interdisciplinary projects like CloudRoots-Amazon22 that examine land-atmosphere interactions across multiple scales. Analysis of his 18 research outputs (15 journal articles and 3 conference abstracts from 2023-2025) reveals a strong thematic focus on methane emissions from subglacial environments and atmospheric isotope signatures . His work frequently employs advanced isotopic techniques to trace biogeochemical processes relevant to climate change. The research demonstrates increasing collaboration across international boundaries, particularly with European and South American institutions. Dr. Adnew actively collaborates with major climate research groups, including those led by T. Röckmann, T. Blunier, and C.J. Jørgensen. His work appears in high-impact journals such as Geochimica et Cosmochimica Acta, Atmospheric Measurement Techniques, and Bulletin of the American Meteorological Society. His research has garnered attention across academic platforms with multiple citations and mentions in scientific networks. His current research involves field work at the Greenland ice sheet margin and analysis of atmospheric samples from various global locations. The ongoing projects suggest continued focus on understanding the connections between subglacial processes and global climate systems through innovative isotopic approaches.
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.
Thomas Pape is a Professor at The Natural History Museum of the University of Copenhagen, specializing in the systematics, taxonomy, phylogeny, biogeography and evolution of Diptera (two-winged insects), with special emphasis on Calyptratae families including Sarcophagidae, Oestridae, and Calliphoridae. He has been a professor since 2025 after serving as an Associate Professor from 2004-2024. PhD from Copenhagen University (1990) Docent at Stockholm University (1998) Associate Professor at Danish Bilharziasis Laboratory (1990-1992) Research Entomologist at Naturhistoriska Riksmuseet, Stockholm (1994-2004) His research spans taxonomy, systematics, phylogeny, biogeography and evolution of Diptera with special emphasis on calyptrate families. He collaborates on Systema Dipterorum, conducts comparative larval morphology studies, and investigates the phylogeny of Calyptrata. His work includes Diptera nomenclature and large-scale biodiversity inventories. Analysis of his recent publications reveals a strong trend toward molecular phylogenetics (using RAD-seq and anchored phylogenomics), forensic entomology applications, and biodiversity informatics. His research spans entomology, systematics, evolutionary biology, and increasingly intersects with bioinformatics and conservation science, with significant contributions to understanding flesh flies, bot flies, and blow flies. President of the International Council of Zoological Nomenclature (since 2016) Chair of the Council for the International Congresses of Dipterology (2010-2018) Member of editorial boards for Entomotropica, Studia dipterologica, Stuttgarter Beiträge zur Naturkunde, and Tijdschrift voor Entomologie Dr. Pape teaches courses in Entomology (structure, phylogeny and biology of terrestrial arthropods), Field Biology II - Zoology, and Ecology and Evolution of East Africa (a 2-week field course in Tanzania with Nikolaj Scharff). He has served on scientific panels for SYNTHESYS and as chair of the scientific advisory committee for Museum Koenig in Bonn (2006-2009). His research group employs both morphological and molecular approaches to address evolutionary questions in Diptera, with particular expertise in calyptrate families. The laboratory maintains active international collaborations across multiple continents, as evidenced by his extensive publication record and research network.
Alessandra Meddis serves as an Assistant Professor in the Section of Biostatistics within the Department of Public Health at the University of Copenhagen's Faculty of Health and Medical Sciences. Her academic work centers on developing and applying advanced statistical methodologies for longitudinal and time-to-event data analysis, with significant contributions to public health research in Denmark and internationally. Her institutional affiliation is clearly established through university contact details and departmental listings. Her primary research interests include correlated survival data analysis, competing risk modeling, informative cluster size methodology, causal inference techniques for observational studies, and environmental epidemiology applications. Dr. Meddis has developed specialized expertise in handling complex survival data structures while maintaining focus on real-world public health problems, particularly in HIV comorbidity patterns, environmental exposure effects, and pandemic-related mortality analyses. Her methodological innovations directly address challenges in clustered and censored data common across medical research domains. Analysis of Dr. Meddis's recent publication record reveals a consistent trajectory of high-impact interdisciplinary research spanning clinical medicine, epidemiology, and statistical methodology. Her work appears in leading journals across biostatistics, infectious diseases, and public health, demonstrating strong collaborative networks with clinical researchers and epidemiologists. Key thematic areas include HIV treatment outcomes, environmental health exposures, and critical care applications during the pandemic, with recent methodological papers advancing survival analysis techniques for complex data structures. Scientific Awards: No scientific awards were specified in the available institutional profile. Advising and Grants: The institutional profile does not provide details regarding graduate student supervision or specific research grant funding. Her collaborative publications suggest involvement in multi-investigator projects including the COCOMO HIV cohort study and pandemic-related research initiatives. Labs and Teams: Dr. Meddis is affiliated with the Section of Biostatistics within the Department of Public Health, though specific laboratory facilities or dedicated research teams are not described in the source material. Her extensive co-authorship patterns indicate active participation in multiple research consortia across medical specialties.
Roberta Sinatra is a Professor in Social Data Science at the University of Copenhagen, with part-time affiliations at ITU Copenhagen, ISI Foundation (Italy), and CSH (Austria). She co-founded the NERDS Research Group at ITU and co-leads the Pioneer Centre for AI in Copenhagen. Research Interests: Her work spans computational social science, network science, and data science, focusing on fairness in AI, scientific careers, and human mobility. Recent projects include analyzing child protection algorithms and modeling urban bicycle networks. Scientific Awards: ERC Consolidator Grant Villum Young Investigator Grant Complex Systems Society Junior Prize DPG Young Scientist Award for Socio- and Econophysics Sapere Aude: Starting Grant Publications: Her research, often in top-tier venues like Nature and Science , explores interdisciplinary themes, including AI ethics, gender disparities in science, and social network dynamics. Labs & Teams: She leads research initiatives at the Center for Social Data Science (KU) and co-founded the NERDS Research Group at ITU, fostering international collaboration in network science and AI ethics.
Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)
