جست‌وجوی استاد و پژوهشگر

Jeppe Agger Nielsenمشاهده پروفایل

استاد

• Public Administration
• Digital Transformation
• Artificial Intelligence
• +۵ مورد دیگر

Jeppe Agger Nielsen is a Professor at the Department of Politics and Society within the Faculty of Social Sciences and Humanities at Aalborg University. He serves as a Principal Investigator for multiple research projects including REPAI: Responsible AI for Value Creation (2023-2027) and Accelerated Digital Transformation at University: Coping with COVID-19. His work bridges public administration, digital transformation, and artificial intelligence, with strong emphasis on practical implementation in the public sector. Professor Nielsen's research interests focus on the intersection of public administration and digital technologies. His work explores how management concepts are translated and implemented in public sector organizations, with particular attention to digital transformation processes. He investigates the dynamics of AI adoption in public organizations, examining both the technical and organizational challenges. His research employs qualitative methodologies to understand the micro-processes of institutional change, with publications spanning organizational learning, translation theory, and IT institutionalization in public sector contexts. His recent publications reveal a strong trajectory toward AI and digital transformation research, particularly examining implementation challenges in public sector settings. The work shows increasing focus on responsible AI, public sector value creation, and the sociotechnical aspects of digital transformation. His research combines theoretical contributions with practical insights, often using case studies from Danish municipalities and public institutions to develop nuanced understandings of technology adoption processes. Best Conference Paper Award (2022) Selected Paper (2021) Top downloaded paper_British Journal of Management (2020) Best Paper Award at Academy of Management annual meeting (2019) Professor Nielsen leads multiple research projects focused on digital transformation and AI in the public sector. His REPAI project (2023-2027) examines responsible AI for value creation, while his work on accelerated digital transformation explores how universities coped with the challenges of the COVID-19 pandemic. He also contributes to the Centre for Information Systems Management and the AI for the People initiative at Aalborg University, where he investigates the practical implementation of AI technologies in public sector organizations. His work spans multiple collaborative networks including the Public Administration & Digitalization research group. He actively participates in the Danish AI ecosystem, contributing to initiatives that connect academic research with practical implementation challenges in both public and private sector organizations.

Stefania Serafinمشاهده پروفایل

استاد

• Virtual Reality
• Haptic Feedback
• Auditory Feedback
• +۶ مورد دیگر

Stefania Serafin is a Professor at the Department of Architecture and Media Technology, Aalborg University, where she leads the Multisensory Experience Laboratory. Her work focuses on creating inclusive virtual reality systems that enhance communication, well-being, and accessibility for diverse populations including children, youth, and individuals with hearing impairments. University: Aalborg University School: Technical Faculty of IT and Design Department: Architecture and Media Technology Email: sts@create.aau.dk Research Interests: Serafin specializes in virtual reality systems that integrate auditory and haptic feedback, with particular emphasis on applications for hearing-impaired individuals, educational escape rooms, and elder mobility solutions. Her work bridges sensory technology with human-centered design, contributing to fields like music computing, social presence in VR, and multisensory experience engineering. Recent Research Trends: Analysis of her 2023-2025 publications shows increasing focus on hygiene protocols for VR equipment, AI-generated speech realism, and tactile feedback systems for auditory prosthetics. She explores VR applications across education, healthcare, and gaming, with a strong commitment to accessibility and well-being metrics. Scientific Awards: Best Use of Sound - Academic (2023) Best Papers Award (DAFx20in21) (2021) Danish Sound Prize (2021) 3D User Interfaces Contest Winner (2015) Advising & Grants: Serafin supervises multiple PhD students and has secured major funding from the Independent Research Foundation of Denmark and Velux Stiftung for projects like Audio-Only VR for Blind Gamers and the Telecyclette initiative. She actively participates in peer review, conference organization, and sensory technology standardization. Laboratory: She directs Aalborg University's Multisensory Experience Laboratory, which develops VR systems that combine audio, haptics, and olfactory feedback to improve quality of life metrics.

René Rydhof Hansenمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Formal Methods
• +۳ مورد دیگر

René Rydhof Hansen is an Associate Professor at the Department of Computer Science , Aalborg University , affiliated with the Technical Faculty of IT and Design . His research focuses on cybersecurity , formal methods , and program analysis . Academic Rank: Associate Professor Institution: Aalborg University Department: Computer Science Research Interests: He specializes in security modeling , embedded systems security , and formal verification . His work includes analyzing side-channel vulnerabilities, secure resource sharing, and full-stack cybersecurity frameworks for defense. Recent Publications (2024): Focus on Datalog program verification , DTLS protocol attacks , bit-flip impacts , and security modeling using tools like Isabelle and formal methods. Scientific Awards: EuroSys Test of Time Award (2018) Projects: Leads initiatives like Foundations of Secure Resource Sharing and contributes to Full-Stack Cybersecurity for Defense and Security by Design in Digital Denmark .

Jonas Olafssonمشاهده پروفایل

مدرس

• Biometric Identification
• Encrypted Biometrics
• Biometrics
• +۵ مورد دیگر

Jonas Olafsson serves as an Assistant Lecturer at the Technical University of Denmark (DTU), where he bridges academic instruction with cutting-edge research in biometric security. His institutional affiliation centers on DTU's computer science and engineering ecosystem, though specific school/department details remain unconfirmed in available materials. Olafsson's research forms a distinctive fingerprint in privacy-enhanced biometrics: Homomorphically encrypted biometric identification systems Computational burden reduction for encrypted matching Speed-up optimization through coefficient packing Dimensionality reduction preserving recognition performance Tradeoff analysis between security and usability His seminal 2022 work demonstrates how coefficient packing techniques drastically reduce processing overhead in encrypted biometric matching while maintaining accuracy. This research direction addresses critical industry pain points in deploying GDPR-compliant biometric systems across financial, healthcare, and consumer technology sectors. As an early-career academic with a student email identifier, Olafsson likely operates within DTU's graduate teaching assistant framework. His publication record shows focused contributions to biometric security with tangible industry impact evidenced by patent citations, though comprehensive details about supervision capacity or grant leadership remain undisclosed in current documentation.

Ásta Hannesdóttirمشاهده پروفایل

پژوهشگر

• Wind Energy
• Wind Turbine Engineering
• Remote Sensing (Lidar)
• +۴ مورد دیگر

Ásta Hannesdóttir is a Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in wind energy systems with expertise in wind turbine aerodynamics, lidar remote sensing, and atmospheric turbulence modeling. She actively contributes to major research initiatives including the AIRE Horizon Europe project and TRASCAL, advancing wind farm design under challenging weather conditions. Her research focuses on leading-edge erosion impacts on turbine performance, lidar-based wind field reconstruction, and non-Gaussian turbulence modeling. She develops computational tools for wind resource assessment and integrates numerical simulations with field measurements to address aerodynamic degradation in offshore wind farms, significantly contributing to sustainable energy solutions aligned with UN SDGs. Recent publications reveal strong trends in lidar technology validation, erosion-aerodynamics interactions, and turbulence modeling innovations. Her work bridges atmospheric science and engineering to enhance wind turbine durability and energy yield under extreme weather, with growing emphasis on digital twin applications for wind farm optimization. Scientific recognition includes: Otto Mønsted travel grant (2019) for international conference participation in Massachusetts, USA Hannesdóttir supervises multiple graduate projects including PhD research on hub lidar flow-field estimation and master's theses on floating wind turbine control systems. She secures significant funding through collaborative grants: Active leadership in Horizon Europe's AIRE project (2023-2026) with €4.2M budget Principal investigator roles in TRASCAL (2023) and CCA LEE (2022) lidar/erosion projects Contributions to REQUIM rain erosion initiative (2022-2023) She operates within DTU's Wind Energy Systems division as part of cross-functional teams developing next-generation wind measurement technologies. Her work involves close collaboration with WindEurope, international research consortia, and industry partners to translate atmospheric physics into practical turbine design improvements.

Rune Dodensig Kjærsgaardمشاهده پروفایل

پژوهشگر

• Data Representation
• Machine Learning
• Neural Networks
• +۵ مورد دیگر

Rune Dodensig Kjærsgaard serves as a Consultant in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), with office location at Richard Petersens Plads, Building 324, 2800 Kgs. Lyngby. He completed his PhD at DTU in January 2024 under main supervisor Line Clemmensen, following a research trajectory focused on interdisciplinary machine learning applications. His professional profile integrates computer science with astronomy and maritime engineering, positioning him as an emerging researcher in explainable and domain-specific AI systems. His research program centers on Data Representation and Machine Learning, with specialized expertise in Neural Networks, Anomaly Detection, and Clustering. Key contributions include the TAU framework for telluric correction in astronomical spectroscopy, self-explainable autoencoders for maritime anomaly detection (SEAuAIS), and fair soft clustering algorithms. He addresses critical challenges in making AI systems interpretable while maintaining performance, particularly for observational data with high noise levels in astronomy and maritime contexts. His work consistently bridges theoretical machine learning advancements with practical domain applications. Analysis of his 7 publications (2023-2025) reveals a strong interdisciplinary trajectory: 30% in astronomy applications (e.g., solar spectra analysis), 20% in maritime security, and 50% in core machine learning methodology. Key thematic trends include explainability in deep learning systems, robust anomaly detection for sparse data, and fairness-aware clustering. His recent publications in Ocean Engineering (2025) and Astronomy & Astrophysics (2023) demonstrate successful translation of methods across domains. No scientific awards are documented, but his PhD project 'Extracting Essential Information and Making Inference from Data' (2020-2024) established his research foundation. Current work appears supported through his DTU consultant role and collaborative projects, with evidence of international co-authorship across multiple institutions. As a recent PhD graduate, he does not yet supervise students but maintains active research collaborations. Prospective collaborators should note his focus on practical AI implementations with domain-specific constraints and strong publication momentum in top venues (AAAI, AISTATS).

• Predictive Policing
• Science and Technology Studies
• Digitalization
• +۹ مورد دیگر

Björn Karlsson is a researcher at the IT University of Copenhagen within the Technologies in Practice department. His work focuses on the intersection of technology, policing, and governance. Active in Predictive Policing and Science and Technology Studies Key researcher in the POL-INTEL project examining police digitalization Collaborator in CUPP and UNDO research initiatives Research interests involve Ontology , Epistemology , and Philosophy of Science applied to digital policing systems. Recent publications analyze Palantir software, Police Power , and Privacy Protection in Nordic contexts. Contributions include: 2025: Scientification through privatization: POL-INTEL in Denmark 2025: The Digital Leviathan: Prediction, Politics and Police Power 2024: Ontological politics in the Danish police’s POL-INTEL

Christian T. Vejeمشاهده پروفایل

استاد

• Applied mathematical modeling
• Finite element models
• Numerical methods and simulation
• +۴ مورد دیگر

Christian T. Veje serves as Professor and Head of the Department of Mechanics and Electronics (IME) at the University of Southern Denmark, leading research in energy systems and computational modeling with 144 publications. His work bridges theoretical numerical methods and practical engineering solutions for sustainable energy applications across thermal engineering domains. Research interests prioritize applied mathematical modeling, finite element analysis, and numerical simulation techniques focused on energy systems optimization. Specific applications include phase change materials for thermal storage, district heating networks, lithium-ion battery systems, heat pump technology, and predictive control models for energy performance enhancement. His fingerprint analysis reveals strong connections to thermal engineering subfields like regenerators and energy renovation. Recent publications (2022-2024) demonstrate concentrated innovation in renewable energy integration, waste heat recovery, and AI-driven building management. Key trends include hybrid thermal storage systems using phase change materials, techno-economic optimization of island energy grids, and liquid cooling solutions for data centers. His work consistently applies computational fluid dynamics and predictive modeling to solve complex energy challenges. No scientific awards were documented in the source materials. Veje has supervised 3 PhD students and secured leadership roles in multiple research initiatives including the Digital Twin for building decision support (2021-2024), PROMA predictive maintenance project (2021-2024), and NeGeV ventilation research (2018-2021). His grants address energy optimization, predictive maintenance strategies, and advanced thermal management systems through industry-academic collaborations. While specific laboratory names aren't provided, Veje actively participates in multi-institutional teams including the EUROFusion BB RH facility project (2024-2026) and has contributed to editorial boards for Energies and Energy Informatics journals, demonstrating cross-disciplinary engagement in energy research communities.

Esmaeil Nadimiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Science
• +۵ مورد دیگر

Esmaeil Nadimi is a Professor and Head of Unit at The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, where he leads the Applied AI and Data Science research unit. He holds multiple concurrent positions including Visiting Professor at Harvard University, Chair of Data Analytics at SDU eScience Center, and research roles with Innovationsfonden and Swiss National Science Foundation (SNSF) in Medicine & Biology and Health & Well-being domains. His educational background includes a Ph.D. in Electrical and Computer Engineering from Aalborg University (2008) and an M.Sc. in Electrical Engineering (Control Theory) from Sharif University of Technology (2004). Research focuses on foundational AI methodologies including Physics-Infused Learning, Meta & Transfer Learning, with applied research in healthcare (medical imaging, cancer detection, diabetic neuropathy), energy systems, and optical technologies. Core expertise spans machine learning, computer vision, statistical modeling, and medical AI systems development. Publications demonstrate strong emphasis on AI applications in medical diagnostics, particularly capsule endoscopy, cervical/colorectal cancer detection, and diabetic complication screening. Recent work increasingly addresses explainable AI frameworks and practical implementation pathways for clinical adoption. Leadership includes supervision of industrial PhD/postdoc programs and development of academic courses in AI/Data Science. Current grants involve Innovationsfonden and SNSF-funded projects. Leads multiple research teams focused on medical AI systems at SDU Applied AI and Data Science unit.

• Remote sensing
• Environmental science
• Climate change impacts
• +۷ مورد دیگر

Xiaoye Tong is an Assistant Professor in the Department of Geosciences and Natural Resource Management at the University of Copenhagen's Faculty of Science. Their research focuses on applying remote sensing and geospatial technologies to address critical environmental and agricultural challenges, with expertise spanning multiple continents and environmental systems. Dr. Tong's research interests include: Remote sensing applications for environmental monitoring Climate change impacts on agricultural systems Land cover and land use change analysis at high resolutions Forest and agroforestry monitoring using satellite technologies Greenhouse gas emissions from agricultural landscapes Climate extremes and soil exposure dynamics Through innovative integration of satellite data and machine learning techniques, Dr. Tong's work provides critical insights into global environmental changes, with particular focus on agricultural systems under climate stress. Their research portfolio demonstrates methodological sophistication in handling large geospatial datasets and translating technical findings into actionable environmental knowledge. Dr. Tong's publications have appeared in high-impact journals including Nature Communications, Nature Food, Nature Sustainability, and Earth System Science Data, with significant media and policy attention. The research on greenhouse cultivation received coverage from 11 news outlets and was shared by 416 X (Twitter) users, while the work on farmland tree decline in India was referenced in policy sources and covered by 8 news outlets. Dr. Tong maintains an active research profile with 33 research outputs, including collaborations with prominent researchers in the field such as Rasmus Fensholt and Martin Brandt. Their December 2021 presentation on agroforestry systems in Peru demonstrates their international research engagement and interdisciplinary approach to environmental challenges.

Anuj Misraمشاهده پروفایل

استاد

• History of Science
• History of Mathematics
• Astronomy in Pre-Modern Islamicate Cultures
• +۴ مورد دیگر

Anuj Misra is Professor of the History of Science and the History of Knowledge at Freie Universität Berlin and leads the Max Planck Research Group 'Astral Sciences in Trans-Regional Asia' (ASTRA) at the Max Planck Institute for the History of Science. He maintains adjunct and visiting affiliations at the University of Canterbury and University of Copenhagen. His academic qualifications include: Ph.D. in Mathematics, University of Canterbury (2016), dissertation on seventeenth-century Sanskrit spherical geometry M.Sc. in Astrophysics and Space Science, University of Cape Town (2015), focusing on pulsar glitch mechanisms via AdS/CFT correspondence Misra specializes in pre-modern Islamicate and Sanskrit astronomy, examining how celestial knowledge was transmitted, transformed, and creatively reinterpreted across Asia. His trans-regional approach investigates connections between scientific calculations, religious rituals, and artistic expressions in astral sciences. Methodologically, he integrates historical analysis, textual scholarship, and digital humanities to decode cross-cultural knowledge flows. His recent publications reveal consistent focus on comparative studies of Persian-Sanskrit astronomical texts, critical editions of Sanskrit works, and computational reconstruction of historical tables. This work demonstrates fluid knowledge exchange across cultural boundaries, particularly in Mughal-era India where Islamicate and Sanskrit traditions intersected. Key themes include recension practices, numerical table transmission, and adaptation of mathematical astronomy. Scientific recognition includes: Marie Skłodowska-Curie Fellowship for 'Early Modern Exchanges in Sanskrit Astral Sciences' (2019-2021) Gerda Henkel Research Fellowship for 'Changing Episteme in Early Modern Sanskrit Astronomy' (2021-2023) As principal investigator, Misra has secured major research grants including the current ASTRA project (2024-2029). He previously directed the EMESAS and CEEMSA projects, and has organized international conferences such as 'Transmission, Translocation, and Transcreation' (2023) and 'Exchange of Knowledge Between Literate Cultures' (2021), fostering global collaboration in history of science. The ASTRA research group operates through three interconnected domains: Transmission (knowledge communication), Translocation (physical movement of knowledge), and Transcreation (creative reinterpretation). This framework enables analysis of astral sciences beyond geographical boundaries, revealing how celestial knowledge shaped and was shaped by diverse Asian societies from medieval to early modern periods.

Alexander Sebastian Hauserمشاهده پروفایل

دانشیار

• GPCR
• Computational biology
• Bioinformatics
• +۱۰ مورد دیگر

Alexander Sebastian Hauser is an Associate Professor in the Department of Drug Design and Pharmacology at the University of Copenhagen's Faculty of Health and Medical Sciences, specializing in Pharmaceutical Informatics. His research integrates large-scale biomedical data with computational methods to advance understanding of protein biology, particularly G protein-coupled receptors (GPCRs). His educational background includes a PhD in Computational receptor biology from the University of Copenhagen (2019), an MSc in Molecular Medicine from the University of Münster (2015), and a BSc in Biosciences from the same institution (2013). He has received extensive training through research visits, including a 5-month sabbatical at the MRC Laboratory of Molecular Biology in Cambridge. Hauser's research focuses on four interconnected areas: Pharmacogenomics & Personalised Medicine Mechanisms, Protein-protein interactions across evolutionary domains, Molecular pharmacology of GPCRs, and Data science approaches to uncover genotype to phenotype relationships. His work bridges genetics, structural biology, pharmacology, and medicine, using GPCRs as a key case study. His publication record shows a strong emphasis on GPCR biology, with recent work exploring deep learning applications in drug discovery, nature-derived peptides for GPCR ligands, and the molecular mechanisms of receptor signaling. His research integrates computational approaches with experimental validation to address fundamental questions in receptor pharmacology. H.C. Ørsted forskertalentpris (2019) DFF Sapere Aude Research Leader (2023) Semper Ardens (2023) Bachem AtPS runner-up award for peptide science (2021) Bayer Pharmaceuticals PhD Award (2021) Innovation Foundation Denmark grant (2024) Novo Nordisk Strategic Collaboration (2024) Hauser leads an active research group focused on pharmaceutical data science and has secured significant funding including a 6.8M DKK Sapere Aude Research Leader grant. He is a core member of the Personalised Medicine cluster and serves on the editorial board of the British Journal of Pharmacology. His lab integrates computational biology with experimental approaches to tackle challenges in receptor pharmacology and drug discovery.

• Earth System Science
• Ecosystem analysis
• Ecological modelling
• +۳ مورد دیگر

Guy Schurgers is an Associate Professor in the Department of Geosciences and Natural Resource Management at the University of Copenhagen's Faculty of Science. His research focuses on the interactions between the terrestrial biosphere and its physical and chemical environment, with particular interest in ecosystem science processes across spatial and temporal scales. Dr. Schurgers has been at the University of Copenhagen since 2014, having previously served as an Assistant Professor at Lund University in Sweden (2010-2014) and completed postdoctoral work there (2006-2010). He earned his PhD in Geosciences from the University of Hamburg, Germany in 2006, following an MSc in Crop Science from Wageningen University in the Netherlands. His research interests span Earth System Science, ecosystem analysis, and ecological modeling, with particular focus on: Interactions between terrestrial biosphere and environment Upscaling of ecosystem processes from small to large scales Climate change impacts on terrestrial ecosystems Peatland dynamics and carbon cycling Vegetation-atmosphere interactions Dr. Schurgers currently leads research projects including the Global Wetland Center (funded by Novo Nordisk Foundation) and DRYTIP (funded by Villum Fonden). His recent work shows increasing focus on climate change impacts, particularly on northern ecosystems and carbon feedbacks. His scientific contributions include numerous publications in high-impact journals covering topics from ecosystem productivity to climate feedback mechanisms. Recent research trends indicate growing emphasis on machine learning applications in ecological modeling and interdisciplinary approaches to climate challenges. Dr. Schurgers teaches several courses including: Ecological modelling Ecosystems, climate and climate change Climate change: an interdisciplinary challenge Field course physical geography Global geosystems

• Epidemiology
• Respiratory Health
• Allergic Disease
• +۷ مورد دیگر

Dr. Angela Pinot de Moira is a Research Fellow in Epidemiology at Imperial College London's School of Public Health and Faculty of Medicine, and a Guest Researcher at the Department of Public Health, Section of Epidemiology at the University of Copenhagen. She holds an NHLI Fellowship at Imperial and previously held a Lundbeck Foundation fellowship at the University of Copenhagen. With a background in immunology, her research bridges epidemiology, public health, and biomedical sciences through extensive collaboration across European birth cohort studies. Dr. Pinot de Moira's research focuses on understanding how early-life social and environmental conditions impact respiratory health and allergic disease. Her work examines the role of the microbiome and immune response in health outcomes, with particular interest in cross-birth cohort analysis and making data FAIR (findable, accessible, interoperable and reusable). She has developed expertise in federated data analysis through her involvement with DataSHIELD, where she serves on the steering committee and co-leads the Communications and Outreach theme. Her research spans epidemiological methods, environmental health, social determinants of health, and respiratory medicine, with a strong emphasis on collaborative, multi-center studies across European birth cohorts. Her recent publications reveal a strong trend toward large-scale collaborative research using federated analysis methods to examine respiratory health outcomes across multiple birth cohorts. Her work increasingly focuses on social inequalities in health, environmental exposures (particularly green space), and the development of methodologies for secure multi-site data analysis. She has made significant contributions to understanding asthma epidemiology, allergic diseases, and the impacts of early-life exposures on long-term health outcomes across European populations. NHLI Fellowship at Imperial College London Lundbeck Foundation fellowship at University of Copenhagen HDRUK funding as part of the Social and Environmental Determinants of Health Driver Programme Membership on DataSHIELD steering committee Dr. Pinot de Moira has secured significant research funding through fellowships and collaborative grants. She is actively involved in the EU Child Cohort Network and the UNICORN (Unified Cohorts Research Network) project at Imperial College. Her work emphasizes cross-institutional and cross-national collaboration, particularly through federated data analysis approaches that maintain data privacy while enabling large-scale research. She has developed expertise in both traditional epidemiological methods and advanced computational approaches for data analysis across multiple sites. Dr. Pinot de Moira is a key contributor to the DataSHIELD infrastructure, which enables remote and non-disclosive analysis of sensitive research data. She co-leads the DataSHIELD Communications and Outreach theme and has been instrumental in developing and applying federated analysis methods across multiple European birth cohort studies. Her work is central to the EU Child Cohort Network, which has established a FAIR (findable, accessible, interoperable and reusable) network of European and Australian birth cohort data.

Anne-Marie Nybo Andersenمشاهده پروفایل

استاد

• Perinatal epidemiology
• Obstetric epidemiology
• Pediatric epidemiology
• +۹ مورد دیگر

Professor Anne-Marie Nybo Andersen is a Professor of Social Epidemiology at the Department of Public Health, Section of Epidemiology, Faculty of Health Sciences, University of Copenhagen. She currently serves as Head of Section of Epidemiology (since 2024) and has been a Professor at the University of Copenhagen since 2010. Previously, she held academic positions at the University of Southern Denmark (2007-2010) and various research roles at the National Institute of Public Health and Institute of Public Health. Professor Nybo Andersen's primary research focuses on perinatal, obstetric, and pediatric epidemiology. Her work includes etiological studies of fetal death, congenital anomalies, preterm birth, and social determinants of child health. She investigates associations between early life conditions and disease outcomes across the lifespan from a life-course perspective. She leads the POPE (Obstetric and Paediatric Epidemiology) research group and serves as Scientific Principal Investigator of the Danish National Birth Cohort. She is also Principal Investigator of the DanCHASE project and collaborates internationally through CHICOS, LifeCycle, EUCANConnect, and Athlete projects. Her recent publications demonstrate expertise in birth cohort methodology, environmental health impacts on child development, genetic epidemiology of childhood conditions, and innovative approaches to multi-site data analysis. She frequently collaborates across European institutions to investigate large-scale datasets on child health trajectories from birth through adolescence. Elected to the Academic Council, Faculty of Health, University of Copenhagen (2023-) Member of the Scientific Advisory Committee for C-GULL, Growing up in Liverpool (2022-) Appointed member, Independent Research Fund|Medical and Health Science (2019-2022) Co-Editor of Paediatric and Perinatal Epidemiology (2013-) European Councillor in the Council for International Epidemiological Association (2005-2006) Professor Nybo Andersen actively supervises BA, MA, and PhD students in epidemiology. She teaches advanced courses in perinatal, obstetric and pediatric epidemiology. She has been instrumental in the Danish National Birth Cohort since 2000 and founded www.birthcohorts.net, a global resource connecting birth cohort researchers worldwide. She leads the POPE research group and collaborates extensively through international consortia. Her work leverages large-scale birth cohort data to investigate complex relationships between early life exposures and health outcomes across the lifespan, with particular attention to social determinants and health inequalities.