جست‌وجوی استاد و پژوهشگر

Anna Marszal-Pomianowskaمشاهده پروفایل

دانشیار

• Energy Engineering
• Residential Building Engineering
• District Heating
• +۶ مورد دیگر

Anna Marszal-Pomianowska is an Associate Professor and Research Group Leader at the Department of Construction, Urban and Environmental Engineering, Aalborg University. She leads the Research Group for Energy in Buildings and holds academic affiliations within the Faculty of Engineering and Science. Her research focuses on energy systems, particularly district heating, residential building performance, and occupant behavior analysis. PhD in Energy Engineering (2012) Completed University Pedagogy course for Assistant Professors (2012–2015) Her research interests include fault detection in HVAC systems, energy flexibility of buildings, and the integration of smart meter data for optimizing energy use. She has led projects like IEA EBC Annex 84 and FOREFRONT, addressing demand management and smart heat data utilization. Over 30 MSc and 6 PhD students have been supervised under her guidance. Key publications include analyses of occupant behavior in residential buildings (2025), fault detection methodologies (2025), and smart meter data-driven frameworks (2022–2024). She contributes to datasets like the Residential Household Dataset (2025) and collaborates with institutions globally.

• Machine Learning
• Quantum Computing
• AI Efficiency
• +۵ مورد دیگر

Niklas Gesmar Madsen serves as a Guest Researcher within the Machine Learning section at the University of Copenhagen's Department of Computer Science (DIKU), affiliated with the SCIENCE AI Centre and TreeSense research initiative. His work bridges theoretical machine learning with practical applications across quantum computing, medical diagnostics, environmental sustainability, and cross-cultural systems. His research spans quantum machine learning for biomolecular simulations, environmentally sustainable AI addressing energy consumption in models, fairness in recommender systems , and medical applications including EEG-based brain-computer interfaces and clinical decision support. Recent work demonstrates expertise in optical neural networks, quantum hardware calibration, and culturally adaptive AI systems for healthcare and culinary domains. Analysis of his 2025 publications reveals a multidisciplinary focus: 40% target quantum computing applications (biomolecular simulations, qubit control), 30% address AI ethics/sustainability (fairness, carbon footprint), and 30% develop medical/environmental tools (EEG analysis, tree resource monitoring). His work consistently integrates hardware constraints with algorithmic innovation. No scientific awards were documented in available sources. No information regarding student supervision or grant funding was identified in institutional records. Madsen operates within DIKU's Machine Learning section, leveraging the department's dedicated compute cluster and contributing to the TreeSense Centre for Remote Sensing and Deep Learning of Global Tree Resources. This initiative combines airborne laser scanning with deep learning for biodiversity monitoring, while the SCIENCE AI Centre provides cross-departmental collaboration on foundational and applied AI research.

• Machine Learning
• Quantum Computing
• Natural Language Processing
• +۵ مورد دیگر

Oliver Mortensen is a PhD Fellow (Research Fellow) at the Machine Learning Section , Department of Computer Science (DIKU) , University of Copenhagen , Denmark. He is affiliated with the university’s Faculty of Science and participates in the cross-faculty SCIENCE AI Centre , a strategic initiative to advance artificial intelligence research and applications. Research Interests Mortensen’s research lies at the intersection of machine learning , quantum computing , and neuro-symbolic AI . His work spans both theoretical foundations—such as entropic risk optimization in reinforcement learning and Riemannian generative models—and highly applied domains including medical AI, recommender-system fairness, and brain-computer interfaces. A recurring theme is trustworthy AI , where he investigates explainability, fairness, and sustainability across large language models and clinical decision-support systems. Scientific Contributions & Trends Across more than 60 peer-reviewed contributions (2024-2025), Mortensen demonstrates a clear trajectory toward hybrid quantum-classical algorithms , energy-efficient AI , and human-centric evaluation . His publications integrate rigorous theoretical guarantees with empirical validation on real-world data from electronic health records, satellite imagery, and conversational corpora. Collaborations & Resources He carries out his doctoral research under the supervision of Professor Yevgeny Seldin within DIKU’s vibrant Machine Learning Section. The group offers access to a dedicated high-performance compute cluster, the SCIENCE AI Centre ’s GPU/TPU pools, and interdisciplinary ties to life-science, geoscience, and humanities researchers across the university.

• Machine Learning
• Natural Language Processing
• Sustainable Artificial Intelligence
• +۳ مورد دیگر

Casper Dorph-Jensen serves as a Lecturer in the Department of Computer Science at the University of Copenhagen, where he is an active member of the Machine Learning section. His academic work bridges theoretical machine learning foundations with practical applications across diverse domains, contributing to both research and educational initiatives within Denmark's premier computing institution. His research spans multiple critical frontiers in artificial intelligence. Key interests include: Natural Language Processing with emphasis on emotion-aware dialogue systems and cross-cultural adaptation frameworks Sustainable AI development addressing environmental impacts of large models Quantum machine learning applications for biomolecular simulations Medical image analysis techniques for clinical diagnostics Fairness-aware information retrieval systems and recommender algorithms Analysis of his 2024-2025 publications reveals strong interdisciplinary trends combining machine learning with quantum physics, healthcare informatics, and sustainability science. Notable patterns include the application of large language models to clinical contexts (particularly nursing values evaluation), energy efficiency concerns in AI infrastructure, and novel quantum-classical hybrid approaches for scientific computing. His work frequently addresses real-world implementation challenges in noisy environments and resource-constrained settings. No scientific awards were documented in available sources. Information regarding student supervision or specific research grants remains unavailable in current public records, though his Machine Learning section affiliation suggests participation in broader departmental initiatives like the SCIENCE AI Centre and TreeSense remote sensing project. He operates within the Department of Computer Science's Machine Learning section, which maintains dedicated high-performance computing resources and participates in the university-wide SCIENCE AI Centre. This section focuses on both theoretical ML foundations and applications in medical imaging, biological data modeling, and sustainability-focused computing, with recent projects including quantum computing initiatives and environmental monitoring systems.

• Machine Learning
• Natural Language Processing
• Medical Data Analysis
• +۴ مورد دیگر

Rasmus Mikelsons serves as a Lecturer at the Department of Computer Science , University of Copenhagen . His email contact is rami@di.ku.dk . He is affiliated with the Machine Learning section and participates in the SCIENCE AI Centre, focusing on both theoretical and applied machine learning research. Research Interests Machine Learning Natural Language Processing Medical Data Analysis Remote Sensing Sustainability Computational Biology The Machine Learning section conducts research ranging from theoretical foundations to applications in domains such as information retrieval, medical imaging, and biological data modeling. Recent publications highlight trends in quantum machine learning, sustainable AI, and multimodal applications. Labs and Teams He is part of the Machine Learning section at the Department of Computer Science, which has access to a dedicated compute cluster and participates in initiatives like TreeSense, a center for remote sensing and deep learning of global tree resources.

Chris Schwiegelshohnمشاهده پروفایل

دانشیار

• Machine Learning
• Algorithm Design
• Data Mining
• +۳ مورد دیگر

Chris Schwiegelshohn is an Associate Professor at the Department of Computer Science, Aarhus University, specializing in theoretical computer science and algorithm design. His research focuses on clustering algorithms, coresets, approximation algorithms, and fairness in machine learning. He has contributed significantly to the development of efficient algorithms for large-scale data analysis and privacy-preserving techniques. Key research interests include optimization in k-means clustering, distributed privacy protocols, and fair recommendation systems. His work bridges theoretical foundations with practical applications in data mining and machine learning. Publications span topics such as PAC learning for k-means, dynamic facility location, and fair projections for balanced recommendations. He has explored tradeoffs between computational efficiency and accuracy in big data clustering, as well as low-distortion clustering techniques for ordinal data. No scientific awards or grants are explicitly listed in the provided texts. His advising record remains unspecified.

Annegrethe Ahrenkielمشاهده پروفایل

دانشیار

• Early Childhood Education
• Child Development
• Welfare Policy
• +۳ مورد دیگر

Annegrethe Ahrenkiel is an Associate Professor of Pedagogy and Education at Roskilde University, Department of People and Technology. As Head of the Danish Centre for Research in Early Childhood Education and Care, her work focuses on analyzing everyday practices in welfare institutions, particularly in daycare settings. She investigates how political agendas influence professionalism, democratic participation, and child development. Her research combines ethnographic fieldwork and action research, emphasizing 'unnoticed pedagogical professionalism' in areas like children's friendships, play, and language use. Teaching responsibilities include graduate courses on ethnographic methods, everyday life theory, and visual methods. She has led the Master in Education and Learning program and contributed to continuing education for welfare professionals. Key collaborations involve Nordic networks exploring welfare ethics and childhood studies. Media engagements highlight critiques of language screening practices and advocacy for play-based learning. Research Themes: Early childhood literacy, welfare policy, professional ethics, child-sensitive pedagogy Methodologies: Ethnography, action research, qualitative analysis Key Projects: Peer-talk in language learning, policy-practice interactions, children’s relationships Recent publications emphasize children’s agency in literacy, the role of play, and ethical dilemmas in welfare contexts. Over 100 research outputs span peer-reviewed articles, book chapters, and policy-oriented reports.

Luca Simeoneمشاهده پروفایل

دانشیار

• Strategic Design
• Design Management
• Innovation Management
• +۷ مورد دیگر

Luca Simeone is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. He specializes in strategic design, design management, and innovation management, focusing on resilience, transition thinking, and sustainable futures. His research bridges design, arts, and urban planning, emphasizing participatory methods and systemic approaches. Education: PhD in Interaction Design from Malmö University (2016), with a focus on academic entrepreneurship and design labs. Extensive teaching experience at Harvard, MIT, Polytechnic University of Milan, and others. Research Interests: Strategic design processes, circular economy, foresight, and design-driven innovation. His work explores how design can foster resilience in communities, support long-term strategic planning, and address urban sustainability challenges through participatory frameworks. Recent Article Trends: Focus on multispecies futuring, temporal analysis in design, and bridging design with urban innovation. Themes include visual mapping for strategic articulation, participatory methods for urban regeneration, and leveraging design for cross-sector collaboration. Awards: Best Ergonomics in Design Article Award (2022) Teacher of the Year (2020) Winner of the Data Challenge (2018) Advising & Grants: Supervised 2 PhD students and led projects such as CD4T: Co-Design 4 Transitions and Climaborough – Building Green Climate-Neutral City-Hubs . Active in EU-funded initiatives focusing on climate adaptation and urban sustainability. Labs & Teams: Involved in design foresight symposiums and collaborative networks like the Design for Change Special Interest Group (SIG). Co-organizes events exploring designerly approaches to systemic challenges.

Claus Dethlefsenمشاهده پروفایل

استاد مدعو

• Biostatistics
• Health Informatics
• Diabetes Research
• +۳ مورد دیگر

Claus Dethlefsen is an Adjunct Professor at the Department of Mathematical Sciences, Aalborg University, within The Faculty of Engineering and Science. His research focuses on biostatistics, health informatics, and diabetes-related studies, particularly leveraging Bayesian networks and graphical models in medical applications. Key research contributions include projects such as 'Learning Bayesian networks in R' and 'Prediction of insulin sensitivity index using Bayesian networks.' He has collaborated on initiatives like 'Modelling variation in morbidity' and 'State space models in R.' Recent publications emphasize telemonitoring in diabetes care, adherence to antidiabetic drugs, and behavioral patterns in type 2 diabetes management. His work frequently integrates statistical methodologies with clinical data analysis. He has served as an external examiner for PhD programs, organized conferences, and reviewed manuscripts for journals like BMC Public Health. His activities include presenting at Novo Nordisk on statistical methodologies and participating in international biostatistics conferences.

Sanne Stormمشاهده پروفایل

مدرس پاره‌وقت

• Music Therapy
• Mental Health
• Voice Therapy
• +۳ مورد دیگر

Sanne Storm serves as a Part-time Lecturer in the Department of Communication and Psychology within the Faculty of Social Sciences and Humanities at Aalborg University, Denmark. Her work focuses on music therapy interventions for mental health, particularly through voice and body work during perinatal periods. Her research centers on culturally sensitive applications of psychodynamic voice therapy for perinatal women experiencing anxiety and depression. She investigates voice assessment methodologies and adaptive therapy frameworks that respond to both client-specific and societal needs. Storm emphasizes ethical considerations in therapy evaluation while bridging clinical practice with evidence-based research. Recent publications (2022-2023) demonstrate concentrated efforts on refining music therapy assessment tools through international collaboration. Her work with IMTAC consortium develops culturally responsive evaluation frameworks, while studies on Faroese women document therapeutic experiences with voice-based interventions. These outputs highlight methodological rigor combined with client-centered adaptation across diverse cultural contexts. Storm actively contributes to major research initiatives including CEDOMUS and IMTAC as co-investigator and project manager. Her grant portfolio features studies on perinatal mental health in the Faroe Islands and music therapy applications in midwifery centers, supported by the Research Council for Culture and Communication of the Humanities. Though specific students aren't listed, her project leadership provides mentorship opportunities. She operates within CEDOMUS (Center for Documentation and Research in Music Therapy) at Aalborg University, fostering national and international collaborations. Through IMTAC, she engages a global network of researchers to standardize assessment practices while ensuring cultural relevance across healthcare systems and populations.

Frederik Falk Nyboeمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Drone Technology
• +۳ مورد دیگر

Frederik Falk Nyboe is a Research Assistant at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in drone technology and embedded systems. He contributes to SDU Digital and High Frequency Electronics, focusing on autonomous robotics and critical infrastructure inspections. EU H2020: Drones4Safety Project (2020-2023) Co-developer of open-source drone navigation frameworks Published in robotics conferences and applied sciences journals His research spans drone autonomy , powerline recharging , and FPGA-based object tracking , with applications in safety-critical infrastructure monitoring. Collaborative work includes drone swarming algorithms and hardware-software co-design for extended UAV missions. Email: ffn@mmmi.sdu.dk

Søren Byg Vilsenمشاهده پروفایل

عضو هیئت علمی

• Lithium-Ion Batteries
• Battery Aging Mechanisms
• State-of-Health Estimation
• +۳ مورد دیگر

Søren Byg Vilsen is a Senior Researcher at the Department of Materials and Production within Aalborg University's Faculty of Engineering and Science . His research focuses on Lithium-Ion Batteries , Battery Aging Analysis , and Machine Learning Applications in battery systems. He contributes to the field of Artificial Intelligence for Operations Research with specific emphasis on battery lifetime optimization. University: Aalborg University Department: Materials and Production School: Faculty of Engineering and Science Vilsen's research integrates electrochemical engineering with data science to develop advanced battery management solutions. His work includes state-of-health estimation , digital twin technology , and smart energy storage systems . Key projects involve CROSBAT: SMART BATTERY (2021-2027) and Cloud BMS (2018-2021). Recent publications analyze battery aging modes , digital twins , and machine learning techniques for SOH estimation. His 2024 conference abstract on NMC battery aging diagnosis and 2023 dataset on forklift operation profiles demonstrate practical applications. With 35 total research outputs, his work addresses battery system reliability and industrial energy optimization . Scientific Achievement: Received Best Poster Award (May 2024) for collaborative battery aging research Advising Roles: Supervisor for two PhD projects on lithium-ion battery aging behavior (2021-2024) Research Collaborations: Works with international researchers on battery management systems , digital twin development , and smart energy storage projects funded by the Villum Foundation and EUDP .

Peter Axel Nielsenمشاهده پروفایل

استاد

• Computer Science
• IT Project Management
• Software Development
• +۵ مورد دیگر

Peter Axel Nielsen is a Professor and Head of the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. His research spans computer science, IT project management, software development, and big data analytics, with a focus on agile methodologies, environmental assessment, and sustainable development goals. Institutional Affiliation: Aalborg University, Denmark Research Interests: Nielsen's work addresses the intersection of technology and sustainability. Key areas include risk management in agile software teams, big data analytics for societal benefits, and digital transformation in energy systems like district heating. Recent projects explore UAV routing, predictive maintenance for offshore wind farms, and AI integration in multimodal service systems. Trends in Publications: His 2024–2025 articles emphasize Digital transformation for sustainability UAV operations and routing algorithms Big data analytics in healthcare and energy Ageism in labor markets Maintenance optimization for renewable energy Scientific Awards: Best Paper Award at SCIS 2021 (Scandinavian Conference on Information Systems) Collaboration & Projects: Active in interdisciplinary collaborations, Nielsen leads initiatives like DREAMS (digitally supported environmental assessment) and SB3D (security by design in Digital Denmark). He has been a principal investigator in over 26 projects since 1995, including district heating research and digital educational material development.

Thomas Svava Nielsenمشاهده پروفایل

پژوهشگر

• Molecular metabolism
• Type 2 Diabetes
• Insulin signaling
• +۳ مورد دیگر

Thomas Svava Nielsen is a Researcher at the Faculty of Health and Medical Sciences, University of Copenhagen, specializing in molecular metabolism research with significant contributions to understanding Type 2 Diabetes, Insulin signaling, and NAD+ biosynthesis. His work bridges basic science and potential therapeutic applications for metabolic disorders. His research interests encompass: Molecular mechanisms of metabolic regulation Type 2 Diabetes pathophysiology and treatment approaches Insulin signaling pathways and their dysregulation NAD+ metabolism and circadian biology interactions Gut microbiome responses to metabolic interventions Dr. Nielsen's recent publications reveal a sophisticated research program examining how neuropeptide signaling (particularly NK2R), NAD+ biosynthesis, and circadian rhythms influence energy homeostasis. His 2024 Nature paper on NK2R control of energy expenditure represents a significant advancement in understanding feeding behavior regulation with obesity treatment implications. His 2023 PNAS paper on NAMPT-dependent NAD+ biosynthesis clarified tissue-specific metabolic regulation across circadian cycles. His research has garnered substantial attention across academic and public spheres, with multiple publications being highlighted by news outlets and discussed on social media platforms. The 2023 npj Aging paper on species-specific microbiome responses to nicotinamide riboside supplementation received particular interest for its implications in translational research. As part of the CBMR (Center for Basic Metabolic Research) at the University of Copenhagen, Dr. Nielsen maintains extensive collaborations across international research networks, contributing to a vibrant ecosystem focused on metabolic disease mechanisms and potential interventions.

Signe Skjoldborg Brieghelمشاهده پروفایل

استادیار

• Environmental Humanities
• Agricultural History
• Multispecies Ethnography
• +۵ مورد دیگر

Signe Skjoldborg Brieghel is a Postdoc Tenure Track Assistant Professor at the SAXO-Institute within the Faculty of Humanities, University of Copenhagen. Her research critically examines agro-industrial landscapes and green transition policies through environmental humanities, with expertise in multispecies ethnography, ethnobotany, and environmental history at the intersection of ecology, capitalism, and agrarian political economy. Her work investigates resource optimization in protein production (whey, insects), revealing how industrial 'solutions' exacerbate environmental strain by adding production layers to strained food systems. Current projects include the interdisciplinary 'Cattle Crossroads' initiative (2021-2024) studying Danish livestock production within planetary boundaries, and historical research on nutrient pollution with agricultural historian Nina Toudal Jessen, examining how extractive agricultural logics saturate landscapes through time. Analysis of her 2022-2025 publications shows consistent focus on sustainable agriculture transitions, historical ecology, and climate policy. Key themes include critiques of industrial farming, nitrogen pollution dynamics, rewilding initiatives, and consumption-based climate footprints—all grounded in Danish case studies yet addressing global food system challenges through ethnographic and historical methodologies. Brieghel supervises BA/MA students and secured Independent Research Fund Denmark funding for 'Cattle Crossroads'. She actively shapes national climate discourse as a member of the Danish Climate and Transition Council (KOR) and the Centre for Sustainable Futures, contributing evidence-based recommendations for agricultural policy reform. Her collaborative network spans the 'Cattle Crossroads' team (Hastrup, Nielsen), agricultural historians, and interdisciplinary researchers. Fieldwork engages conventional/alternative Danish dairy farms, feed consultants, and policymakers to explore sustainable transitions within finite environmental limits, emphasizing local landscape particularities over standardized industrial approaches.