جستجوی استاد راهنمای دانشگاهی

Beatriz Soretمشاهده پروفایل

دانشیار

• Satellite Communications
• Internet of Things (IoT)
• Wireless Networks
• +۳ مورد دیگر

Beatriz Soret is an Associate Professor at Aalborg University's Department of Electronic Systems, part of The Technical Faculty of IT and Design. Her research focuses on satellite communications, IoT, wireless networks, and AI-driven network systems. She leads and collaborates on projects like STELLAR (2019-2021) and SATNEX V WI Y4.6 (2024-2025), addressing latency, reliability, and real-time data challenges in 6G and satellite networks. Her work emphasizes distributed computing, edge computing for Earth observation, and semantic communication frameworks. Key publications include advancements in RAN slicing for VR traffic, coded distributed computing, and AI-integrated network layers. She actively contributes to special issues on distributed intelligence and 6G technologies. Her research spans theoretical and experimental analyses of delay, age of information, and network performance in scenarios like LEO satellite constellations and industrial IoT. She collaborates with institutions globally, advancing non-terrestrial networks and smart connectivity solutions.

Daniel-Ioan Stroeمشاهده پروفایل

دانشیار

• Energy Storage Systems
• Lithium-ion Batteries
• Battery Testing
• +۵ مورد دیگر

Daniel-Ioan Stroe is an Associate Professor at Aalborg University's Department of Energy, part of The Faculty of Engineering and Science. He leads the Batteries Research Group and has held visiting roles at RWTH Aachen and Czech Technical University. His research focuses on energy storage systems, lithium-ion battery modeling, and diagnostics, with over 250 peer-reviewed publications. He earned his PhD in 2014 from Aalborg University, specializing in battery lifetime modeling for virtual power plants. Education: Dipl.-Ing. in Automatics, Transilvania University of Brasov, Romania (2008) M.Sc. in Wind Power Systems, Aalborg University, Denmark (2010) PhD in Energy Engineering, Aalborg University (2014) Research Interests: Dr. Stroe's work centers on advancing energy storage technologies for grid and e-mobility applications. Key areas include lithium-ion battery performance, lifetime modeling, state estimation, and diagnostics. His projects address challenges like fast-charging protocols, impedance-based health monitoring, and sustainable battery lifecycle analysis. Awards & Grants: Best Poster Award (2024) for collaborative work on battery diagnostics Best Paper on Ecological Vehicles (2019) Lead on funded projects such as Listen2Battery (Villum Foundation), DeBatT (Innovation Fund Denmark), and BattMaxLife (EU) Labs & Teams: He directs the Batteries Research Group, collaborating internationally on initiatives like non-woven sodium-ion batteries (NOWOS) and acoustic-based battery health monitoring. His team emphasizes interdisciplinary approaches to tackle energy storage challenges.

• Marine Engineering
• Digital Twins
• Co-simulation Systems
• +۳ مورد دیگر

Yingguang Chu is an Associate Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in Mechatronics. His research focuses on co-simulation systems, digital twins, and marine engineering applications. Research Interests : Digital twin technologies, co-simulation frameworks, marine crane systems, hydraulics, and control algorithms. Projects : Active participant in the ShippingLab II project (2024-2027) on digital twins and human factors in vessel performance. Research Output Trends : Recent work emphasizes physics-inspired neural networks for mobile machinery dynamics, environmental load sensitivity analysis, and Vico-based co-simulation systems for marine operations. Publications frequently address crane path planning, digital twin implementation, and dynamic response optimization. Scientific Awards : IEEE Robotics and Automation Magazine Best Paper Award (2024) Teaching Responsibilities : Supervises master's theses on topics like CFD simulations, membrane valve systems, and fluid mechanics, while teaching mobile hydraulics courses.

Ehsan Forootanمشاهده پروفایل

استاد

• Geodesy
• Satellite Gravity
• Hydrology
• +۷ مورد دیگر

Ehsan Forootan is a Professor of Geodesy and Earth Observation at Aalborg University, Denmark. He holds a PhD in Geodesy from the University of Bonn and has held academic positions at Cardiff University, University of Hohenheim, and Robert Bosch GmbH. His research focuses on applying satellite geodetic techniques (GNSS, satellite gravity, altimetry) to monitor Earth System processes, including mass redistribution, hydrological cycles, and climate change impacts. He leads projects on flood awareness systems, digital twin Earth hydrology, and data assimilation frameworks. Forootan serves as vice-chair of the IAG's Sub-Commission 4.3 (Atmosphere Remote Sensing) and editor for Remote Sensing journals. Education: B.Sc. Civil-Surveying Engineering (Khaje Nasir Technical University, 2006), M.Sc. Geodesy-Hydrography (University of Tehran, 2008), PhD in Geodesy (University of Bonn, 2014). Postdoctoral fellowships include Curtin University and German Aerospace Center (DLR). Research interests include geodetic data assimilation, satellite remote sensing applications, and Bayesian methods for hydrological modeling. His work addresses UN SDGs related to climate action, water sustainability, and environmental monitoring. Key contributions include frameworks for GRACE/GRACE-FO data integration into hydrological models and thermospheric neutral density forecasting. Awards: ABC/J Young Academic Award (2015). Active in research networks (ESA, NASA) and editorial roles (Geodinamica Acta, Nature Geoscience). Projects include Space-based Flood Awareness System for Africa (SFAS) and Digital Twin Earth Hydrology initiatives.

Vera Hemmelmayrمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Logistics
• Operations Research
• +۷ مورد دیگر

Vera Hemmelmayr is an Associate Professor at the Institute for Transport and Logistics Management, School of Business, Vienna University of Economics and Business (WU Vienna). She earned her PhD from the University of Vienna and completed her habilitation at WU. Prior to her current role, she held postdoctoral positions at the University of Vienna and CIRRELT in Montreal, and conducted research collaborations at Georgia Institute of Technology, University of Bologna, and Northwestern University. Research Interests: Vera's research centers on combinatorial optimization in logistics, with emphasis on enhancing solution methods and real-world applications. She specializes in metaheuristics, parallel algorithms, and hybrid exact-heuristic techniques. Her work addresses critical challenges in waste collection, city logistics, nonprofit logistics collaboration, and sustainable urban transport—particularly the integration of cargo bikes into freight distribution networks. Publication Trends: Her recent publications reflect a consistent focus on vehicle routing problems, green logistics, and optimization under uncertainty. Themes include two-echelon delivery, drone-truck collaboration, stochastic demands, and multi-depot systems. Methodologically, she advances matheuristics, adaptive large neighborhood search, and simulation-optimization frameworks applied to urban and humanitarian logistics. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no students are listed, Vera has served as project leader for multiple research initiatives funded by the Austrian Science Fund (FWF) and the Austrian Research Promotion Agency (FFG), indicating leadership in securing competitive grants and managing research teams. Labs and Teams: Although no formal lab name is given, her affiliation with the Institute for Transport and Logistics Management suggests active participation in a research group focused on logistics optimization, likely involving collaboration with national and international partners in both academia and industry.

Kirsten Elisa Petersenمشاهده پروفایل

دانشیار

• Educational Psychology
• Social Sciences
• Child and Youth Well-being
• +۳ مورد دیگر

Dr. Kirsten Elisa Petersen is an Associate Professor in Educational Psychology at the Danish Institute of Education (DPU), Copenhagen. Her research focuses on child and youth well-being, social inclusion, and the role of leisure education within Nordic welfare systems. She leads multiple ongoing projects addressing educational challenges during the pandemic, youth vulnerability, and cross-national welfare state comparisons. Current Projects (2020–present): Danish day care pandemic impacts, Nordic youth well-being, and sensitive research methodologies. Recent Publications: Over 117 works including 2025's International Journal of Inclusive Education and edited volumes on Nordic pedagogical responses to inequality. Professional Roles: Editorial board member for FPPU , committee member for Diaconal Education, and frequent conference speaker (e.g., NERA 2024). Her research emphasizes marginalized groups, leveraging qualitative methods to explore educational interventions. Media contributions include analyses on youth gangs and leisure clubs' societal roles. She teaches modules on problem analysis, PhD supervision, and vulnerable youth populations. Collaborations span Nordic institutions, with active networks in Sweden, Iceland, and Finland. Her work bridges academia and practice, influencing policy through empirical studies on social exclusion and pedagogical innovation.

Hiromichi Suetaniمشاهده پروفایل

استاد

• Neuroinformatics
• Computational Neuroscience
• Nonlinear Dynamics
• +۸ مورد دیگر

Hiromichi Suetani is a Professor at the Department of Co-creative Science and Engineering , Faculty of Science and Engineering , Oita University . He holds concurrent positions as an Affiliated Researcher at the International Research Center for Neurointelligence , University of Tokyo , and has previously worked at institutions including RIKEN Center for Brain Science , ATR , and Kagoshima University . His research bridges nonlinear dynamics , machine learning , and neuroscience . Education : PhD in Informatics from Kyoto University, with research at the Institute of Statistical Mathematics and graduate training in Mathematical Engineering at the University of Tokyo. Research Society Affiliations : Society for Neuroscience Japan Neuroscience Society Physical Society of Japan His research focuses on decoding brain information and controlling complex systems using techniques like reservoir computing , topological data analysis , and nonlinear modeling . He investigates human EEG individuality , collective patterns in active matter , and chaotic synchronization in dynamical systems. Recent work with collaborators explores hybrid prediction models combining anticipating synchronization and echo state networks to improve time series forecasting in chaotic systems. Earlier studies analyzed EEG consistency under noisy stimuli and applied manifold learning to map brain oscillations. His teaching includes mechanics , computational physics , and nonlinear science at Oita University. He has secured competitive funding from the Japan Society for the Promotion of Science for projects on critical computation systems , stable chaos in neural networks , and topological analysis of biological data .

• Machine Learning
• Natural Language Processing
• Health Informatics
• +۳ مورد دیگر

Maher Harring Kassem serves as a Guest Researcher within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His position falls under the research staff category, reporting to Head of Section Professor Yevgeny Seldin, and contributes to the department's mission in theoretical and applied machine learning research. His research spans Machine Learning , Natural Language Processing , Health Informatics , Sustainable AI , Quantum Machine Learning , and Cross-Cultural Computing . This interdisciplinary profile integrates computational methods with real-world applications in mental health analysis, culinary adaptation systems, emotion recognition, and environmental sustainability, reflecting the department's focus on domains like medical data analysis and biological modeling. Analysis of his 2024-2025 publications reveals a distinct trend toward high-impact interdisciplinary work. Key themes include sustainable AI development (addressing energy consumption in models), quantum-biomolecular applications (free energy calculations), cross-cultural NLP systems (recipe adaptation), and clinical AI (nursing values evaluation). His output demonstrates technical depth across optical neural hardware, EEG-based semantic relevance, and fairness-aware recommender systems, while consistently tackling societal challenges like climate impact and healthcare equity. No scientific awards or fellowships were documented in the available materials. As a Guest Researcher, Kassem leverages the department's powerful compute cluster and participates in initiatives like the SCIENCE AI Centre and TreeSense project for remote sensing of global tree resources. His collaborative work spans medical imaging analysis, quantum computing applications, and sustainable AI development, utilizing the university's infrastructure for large-scale computational tasks in domains ranging from wetland conservation to quantum photonic computing.

• Machine Learning
• Quantum Machine Learning
• Neural Networks
• +۶ مورد دیگر

Sebastian Bugge Loeschcke is a PhD Fellow at the Machine Learning Section of the Department of Computer Science (DIKU), University of Copenhagen . His research spans theoretical and applied machine learning with focus on quantum machine learning, language modeling, and sustainability. Current affiliation: Machine Learning Section, DIKU Key research areas: Quantum-classical hybrid models, neural language processing, geospatial analysis Collaborative initiatives: SCIENCE AI Centre, TreeSense Centre Loeschcke's recent work includes Coarse-To-Fine Tensor Trains for compact representations and LoQT: Low-Rank Adapters for Quantized Pretraining , reflecting his focus on efficient neural architectures and quantum-inspired methods. His publications address cross-disciplinary challenges in climate modeling, healthcare, and quantum computing. Scientific contributions include: 2024: Tensor train compression methods for visual representations 2024: Low-rank adapter techniques for quantized models 2025: Quantum computing applications in molecular binding energy calculation 2025: Ethical frameworks for sustainable AI development 2025: Quantum dot array simulation tools (QDarts) Loeschcke contributes to interdisciplinary projects involving: TreeSense (remote sensing of global tree resources) Quantum computing optimization with Danish research consortia

Andreas Kühne Larsenمشاهده پروفایل

پژوهشگر ارشد

• Operations Research
• Optimization
• Artificial Intelligence
• +۳ مورد دیگر

Andreas Kühne Larsen is a PhD Fellow at Aalborg University's Department of Materials and Production within the Faculty of Engineering and Science. He conducts research in the Section of Applied Systems Research specializing in Artificial Intelligence for Operations Research and is affiliated with AAU BLUE – Marine & Maritime Research. Education: MSc in Mathematical Engineering Research Interests: Larsen focuses on developing optimization algorithms and AI-driven solutions for complex operational problems. His work integrates deep learning, genetic algorithms, and dynamic probability modeling to address challenges in maritime search and rescue, drone-based detection systems, and satellite scheduling under real-world constraints. Publication Trends: His 2024-2025 publications reveal a consistent emphasis on constraint optimization for dynamic environments, particularly in maritime operations (e.g., path-finding with probabilistic target modeling) and industrial systems (e.g., throughput tradeoff mitigation). These works frequently employ heterogeneous sensor networks and AI techniques to enhance decision-making in time-sensitive scenarios. Professional Engagement: Larsen actively participates in the academic community, including attendance at the 33rd European Conference on Operational Research (2024). His research is embedded within interdisciplinary initiatives like AAU BLUE, targeting marine and operational challenges through collaborative frameworks.

Ignacio Rodriguez Larradمشاهده پروفایل

پژوهشگر

• Path Loss Engineering
• Wireless Communication Engineering
• Internet of Things Engineering
• +۳ مورد دیگر

Ignacio Rodriguez Larrad is a researcher at Aalborg University , affiliated with the Department of Electronic Systems under the Technical Faculty of IT and Design . His work focuses on wireless communication engineering, industrial IoT, and path loss modeling. He is currently involved in the 5G-enabled autonomous mobile robotic systems project. Current affiliations: Aalborg University, Spanish Researchers in Denmark (Vice-chairman) Research interests include 5G wireless networks, industrial IoT deployment, real-time locating systems, and antenna engineering. His work addresses practical challenges in factory environments and rural connectivity solutions. Recent publications highlight applications in corrosion mapping, robotic control, and network integration. Key trends involve deep learning for industrial automation, UWB technology, and multi-connectivity frameworks. Scientific Awards : 5G-prisen (2019) - Recognizing 5G research contributions Neal Shepherd Memorial Best Propagation Paper Award (2017) - Radio propagation studies Ignacio has co-supervised PhD research and participated in industry-focused projects. His activities include media engagement and presentations on industrial wireless systems at conferences.

• Neuro-Ophthalmology
• Retinal Diseases
• Optic Nerve Disorders
• +۳ مورد دیگر

Steffen Hamann serves as Clinical Professor in the Department of Ophthalmology within the Faculty of Health and Medical Sciences at the University of Copenhagen. His clinical and research activities are centered at Rigshospitalet (Copenhagen University Hospital) with office address at Blegdamsvej 3, 2200 København N. His work bridges clinical ophthalmology with neuro-ophthalmic research, focusing on diagnostic and therapeutic challenges in optic nerve disorders. Professor Hamann's primary research interests include neuro-ophthalmology with special emphasis on optic disc drusen, retinal vascular diseases, and AI applications in ophthalmic diagnostics. His laboratory investigates anatomical correlates of optic nerve pathologies, inflammatory markers in vasculitic eye diseases, and time-sensitive interventions for acute vision loss conditions. Current projects involve multicenter clinical trials for retinal artery occlusion and genetic studies of familial optic disc drusen. Analysis of his recent publications reveals strong concentration in three interconnected domains: (1) Optic disc drusen pathophysiology and management strategies, (2) AI-enhanced diagnostic approaches for acute retinal vascular events, and (3) Systemic disease manifestations in neuro-ophthalmology. His collaborative network spans European stroke specialists, AI researchers, and international ophthalmology centers. Principal Investigator for TenCRAOS (Tenecteplase in Central Retinal Artery Occlusion Study) Lead researcher in Nordic collaborative projects on optic disc drusen epidemiology Active participant in European networks for neuro-ophthalmic emergency protocols Professor Hamann maintains strong clinical ties with Rigshospitalet's Department of Ophthalmology while directing translational research that bridges bench findings with bedside applications. His work increasingly incorporates artificial intelligence for early detection of time-critical ophthalmic conditions.

Rudi Steffensenمشاهده پروفایل

پژوهشگر

• Immunology
• Clinical Immunology
• Genetics
• +۷ مورد دیگر

Rudi Steffensen is a Researcher at Aalborg University's Faculty of Medicine, Department of Clinical Immunology. He holds a PhD and works as a Bioanalytiker (Biomedical Laboratory Scientist) at Aalborg University Hospital, where he conducts research at the intersection of immunology, genetics, and clinical diagnostics. His primary research interests focus on Immunology , particularly Mannose-Binding Lectin genetics and function, Neutrophil Antigens , and Genotyping methodologies. His work spans autoimmune disorders, hematological conditions, and molecular diagnostics, with significant contributions to understanding genetic variations in immune-related conditions. Dr. Steffensen has published extensively, with 188 research outputs including journal articles, conference abstracts, and datasets. His recent work (2023-2025) emphasizes nanopore sequencing applications for neutrophil antigen determination, autoimmune neutropenia genetics, and sensitive mutation detection in blood disorders. His publication trends show a strong focus on translational research connecting genetic findings with clinical applications. As a supervisor, he has guided PhD research on Primary Autoimmune Neutropenia in Early Childhood, demonstrating his role in academic mentorship. His collaborative network spans multiple Danish institutions and international partners, reflecting the interdisciplinary nature of his work in clinical immunology and genetics. His laboratory work involves advanced molecular techniques including Real-Time PCR, nanopore sequencing, and comprehensive genotyping approaches. Current projects focus on genetic variations in immune-related conditions and their clinical implications, particularly in pediatric and hematological contexts.

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.