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.
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
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.
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.
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)
Klaus Mølmer is a Professor at the Niels Bohr Institute, University of Copenhagen, specializing in Quantum Optics and Photonics. His research spans quantum information, entanglement, and cavity QED, leveraging machine learning and Grover's algorithm for quantum state engineering. His recent work focuses on spin squeezing, Rydberg atom interactions, and mechanical resonator cooling. A leader in quantum simulation and superradiance, he collaborates on cavity-mediated emission and quantum network design. The 15 most recent articles highlight advancements in quantum state manipulation, entanglement protocols, and robust differential phase sensing. These studies bridge theoretical frameworks with experimental applications in cavity QED, Rydberg arrays, and zero-photon detection.
Roberto Mora Cortez serves as an Associate Professor in the Department of Business and Sustainability at the University of Southern Denmark (SDU), Kolding campus, with a primary focus on Business-to-Business (B2B) marketing research and instruction. His academic contributions span teaching, publication, and industry engagement within the global B2B domain. His research expertise centers on B2B Marketing , Market Segmentation , and Quantitative Methods , with significant extensions into Sales , Trade Shows , Customer Journey mapping, and DEI in B2B contexts. His methodological approach combines systematic reviews, survey research, and empirical analysis, emphasizing practical applications for businesses across diverse economic environments including Chile and Peru. Key investigations address segmentation efficacy, digital transformation of trade shows, and the integration of diversity principles into B2B selling frameworks. Analysis of his 15 most recent publications (2022-2025) reveals dominant trends toward digitalization, sustainability, and inclusivity in B2B practices. His work consistently bridges theoretical frameworks with actionable implementation strategies, particularly in global and emerging markets. Notable thematic clusters include AI-driven business processes, relationship marketing resilience during economic fluctuations, and social media's role in B2B engagement. No scientific awards, prizes, or fellowships are documented in the available records. Mora Cortez has supervised at least one bachelor thesis student (Catherine Scheck) and teaches courses including Business-to-Business Marketing, Advanced Quantitative Analyses, and Scientific Research Processes. His academic service includes peer reviewing for the Journal of Business & Industrial Marketing and participation in conferences such as the AMA Winter Academic Conference. International collaborations with Georgia State University and the University of Chile indicate active research networking. His departmental work within SDU's sustainability-focused business unit involves media engagement on mining industry marketing in Latin America, including contributions to Peruvian business media on value propositions and trade show ROI. Current research trajectories emphasize digital transformation, sustainable innovation, and DEI integration within evolving B2B landscapes.
Sascha Struwe serves as a Postdoctoral Researcher at Aalborg University Business School within the Faculty of Social Sciences and Humanities, actively contributing to the International Business Research Group. Based at Fibigerstræde 11 in Aalborg Øst, Denmark, Struwe operates at the intersection of service innovation theory and business practice with international focus. Research expertise centers on service innovation , value co-creation , and digital servitization , particularly examining B2B contexts and open banking ecosystems. Work consistently explores institutional influences through German-Chinese case studies, addressing how cultural and regulatory frameworks shape service design. Recent trajectories reveal evolution from foundational service design challenges (2019-2021) toward digital transformation implications (2022-2023), with emphasis on value co-destruction mechanisms in financial ecosystems. Struwe led the PhD project Innovating the Invisible and Intangible: Value Creation in B2B service (2018-2021) investigating co-creation capabilities across industrial sectors. Academic engagement includes conference participation at EIBA and CICALICS events, plus a visiting researcher appointment at Fudan University's Nordic Centre (2019-2020). Current work continues through the International Business Research Group, focusing on digital literacies and service ecosystem resilience.
Claudia Acciai is a Guest Researcher at SODAS (Sociology Department) at the University of Copenhagen, where she works on the research project "Quantifying institutional and country-related Matthew effects in science." She holds a PhD in Political Science and Sociology from the Scuola Normale Superiore, with a dissertation focused on policy design in the Research and Innovation sector. Her academic journey includes research visits at Alliance Manchester Business School, Science Po Paris, and Copenhagen Business School. Her research interests lie at the intersection of comparative public policy, innovation studies, and science of science. She combines computational and experimental methods with qualitative content analysis techniques to examine policy design, institutional effects in science, and research evaluation. Her work frequently addresses how policy instruments function in complex governance environments and investigates gender-related differences in academic publishing. Analyzing her recent publications reveals a strong focus on the science of science, with particular attention to bibliometrics, policy instrument effectiveness, and gender dynamics in academic careers. Her work spans multiple disciplines including political science, sociology of science, and innovation studies, often employing mixed-methods approaches that combine quantitative analysis with qualitative insights. Acciai is an active member of the Knowledge, Organization and Politics research group at the Department of Sociology. Her collaborations span multiple countries and institutions, reflecting the international nature of her research on comparative policy and science studies. She has conducted significant work for research projects funded by the Italian Ministry of Education, including analyses of policy analysis capacity in Italian policymaking and governance changes in higher education systems.
Konstantinos Kalogeropoulos is an Assistant Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), leading research at the Cell Diversity Lab. His work bridges proteomics, computational biology, and snake venom research. Current projects: "The Proteomic Landscape during Influenza Infection" (2022-2025) Supervisor for PhD projects on protease network rewiring in psoriasis and wound exudate degradomics Research interests include: Proteomic analysis of inflammatory diseases Snake venom toxin structure prediction Extracellular matrix biomechanics De novo peptide sequencing algorithms Computational modeling of protease networks Recent article trends demonstrate his work in • Database-free proteomics (InstaNovo/InstaNexus) • Snake venom pathophysiology (V-ToCs clustering) • Inflammatory disease biomarkers (psoriasis, impaired healing) • Extracellular matrix mechanics (fibronectin tension, gut inflammation) Advising: Supervises PhD students Polhaus, C. J. M. and Haack, A. M., focusing on protease networks and wound healing.
Anders Krogh is a Professor at the Department of Computer Science, University of Copenhagen, and also holds a position at the Department of Public Health in the Section for Health Data Science and AI. He serves as the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. Previously, he was affiliated with the Department of Biology at the University of Copenhagen until 2020. Dr. Krogh earned his PhD in theoretical physics but transitioned into machine learning and bioinformatics during his doctoral studies. His research spans both theoretical foundations and practical applications in these fields. He is particularly renowned for his pioneering work on hidden Markov models for biological sequences, which has had significant impact in computational biology. In recent years, Krogh's research has focused on deep generative models applied to gene expression data and other biomedical applications. His work bridges computer science with healthcare, developing AI-driven approaches for precision medicine, cancer diagnostics, and analysis of complex biological systems. His current research integrates machine learning with quantum computing applications in biomolecular modeling. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence to healthcare challenges, particularly in rare diseases, cancer diagnostics, and personalized medicine. His work increasingly incorporates federated learning approaches to address privacy concerns while enabling collaborative research across institutions. There's also a growing emphasis on quantum computing applications in biomolecular modeling and drug discovery. As head of the Center for Health Data Science, Krogh leads interdisciplinary research efforts that bring together computer scientists, medical researchers, and clinicians. His team develops novel computational frameworks like MOSAIC for multimodal analysis of rare cancers and multiDGD for multi-omics data integration. These tools are designed to translate AI innovations into clinical practice while addressing the unique challenges of medical data.
Claus Thustrup Kreiner is a Professor of Economics and Director of the Center for Economic Behavior and Inequality (CEBI) at the University of Copenhagen's Faculty of Social Sciences, Department of Economics. He also serves as Area Director of Public Economics in the CESifo network and was co-editor of the Journal of Public Economics from 2014 to 2020. Kreiner has held various leadership positions including Director of the Economic Policy Research Unit (EPRU) since 2005 and Director of the Center of Excellence WEST from 2011-2013. Education: Ph.D. in Economics, University of Copenhagen, 1998 Visiting Ph.D. student, University of York, 1996 M.Sc. in Economics, University of Copenhagen, 1994 B.Sc. in Economics, University of Copenhagen, 1991 Claus Thustrup Kreiner's research primarily focuses on Public Economics , with secondary specializations in Labor Economics, Household Finance, Applied Microeconometrics, and Experimental Economics. His work examines inequality in income, wealth and health, optimal redistribution policy, and behavioral responses to public policy. Kreiner has conducted significant research using Danish administrative data to analyze tax compliance, labor supply responses, and inequality dynamics. His research often involves collaborations with institutions like Columbia University, London School of Economics, and UC Berkeley. His recent publications reveal a strong focus on inequality across multiple dimensions (income, wealth, health, life expectancy), tax policy design and compliance, labor market responses to policy changes, and the intersection of behavioral economics with public policy. Kreiner frequently employs high-frequency administrative data from Denmark to provide empirical evidence on how individuals and households respond to economic policies and shocks. Scientific Awards and Recognition: Appointed Knight of The Order of Dannebrog by Queen Margrethe II (2018) The Invisible Hand Award from the Society of Social Economics (2006, 2001) Best Teacher Award from the Study Board of Economics at University of Copenhagen (2002) Research Fellow at Centre for Economic Policy Research (CEPR), London (2009-) Kreiner has supervised numerous students primarily in Public Economics and has received multiple research grants including from the Danish Social Science Research Council (2003, 2006, 2009), International Growth Center (2009), and Danish National Research Foundation (1998-2003). He has served on important policy bodies including as co-chair of the Danish Economic Council (2010-2014) and member of the Danish Tax Commission (2008-2009). As Director of CEBI (Center for Economic Behavior and Inequality), Kreiner leads a major research center funded by the Danish National Research Foundation. He also directs the Economic Policy Research Unit (EPRU) and has been instrumental in establishing research collaborations through networks like CESifo. His work bridges academic research and policy application, as evidenced by his practical policy experience with government commissions.
