جستجوی استاد راهنمای دانشگاهی

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.

• Stochastic programming
• Two-phase and multi-phase models
• Scenario generation and reduction
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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)

• Power Electronics
• Wind Turbines
• Photovoltaic (PV) Systems
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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.

• Machine Learning
• Bioinformatics
• Deep Generative Models
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Henrik Rasmus Andersen is a Professor at the Department of Environmental and Resource Engineering, Water Technology & Processes at the Technical University of Denmark (DTU). His research focuses on water treatment processes, particularly the occurrence, transformation, and removal of micropollutants like pharmaceuticals and hormones. Key Research Areas: Chemical analysis, bioassays, ozonation, biofilter optimization, by-product profiling, and advanced oxidation processes. Projects: Leads initiatives like BIZON (ozone technology for fish farms) and Sustainable Industrial Laundry Wastewater Treatment , emphasizing sustainable solutions. Collaborations: Works with institutions such as University of Copenhagen and industry partners on municipal and industrial wastewater challenges. Education: Master of Science in Environmental Chemistry from Copenhagen University (1998).

• Water Treatment Processes
• Chemical Analysis of Water Micropollutants
• Bioassays and Ecotoxicity
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Hossein Nami is an Associate Professor at the Department of Green Technology (IGT) and SDU Life Cycle Engineering at the University of Southern Denmark . His research focuses on Power-to-X , Hydrogen production , E-fuel , and system modeling for sustainable energy solutions. PhD, University of Tabriz (2018) Postdoc, Technical University of Denmark (2020-2022) Assistant Professor, University of Southern Denmark (2022-2025) Nami's research output includes 15 articles (2024-2026) on topics like ammonia-fueled fuel cells , geothermal cycles , chemical looping combustion , and electrolysis optimization . His work emphasizes techno-economic analysis, exergy efficiency, and multi-objective optimization for low-carbon energy systems. He leads the FLEX-ENVIRONMENT project (2024-2027) on electrolyzer integration and contributes to CARMA-Green Fuels (2023-2026) and GRACE (2025) for carbon management and grid-aware investment. His teaching includes supervision of MSc theses on renewable hydrocarbons and power-to-X technologies at SDU.

• Power-to-X
• Hydrogen
• E-fuel
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Birgitte Bak-Jensen is a Professor at the Department of Energy, Aalborg University, where she has worked since 1988. She specializes in intelligent control of power distribution systems, with research focusing on grid stability, power quality, and integration of dispersed generation and smart grid technologies. Her work also addresses multi-energy system interactions between electrical grids, heating, and transport sectors. Projects : Led EU H2020 projects (SERENE, SUSTENANCE) and Danish initiatives (EFFORT, SMARTCE2H) Publications : Over 250 papers on distribution grid control and smart energy systems Her research combines renewable energy integration , electric vehicle grid interaction , and energy storage optimization . Recent work includes explainable AI for wind forecasting and voltage control strategies for EV charging. 2025 Awards : Best Student Paper Award (2023), Best Paper Award (2021), CIGRE Technical Council Award (2018) Organizational Roles : Vice Head of AAU Energy Research, leadership positions in IEEE and CIGRE

• Smart Grids
• Electric Power Distribution Systems
• Multi-Energy Systems Integration
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Remus Teodorescu is a Professor at AAU Energy , Aalborg University , specializing in Power Electronics System Integration and Materials . His work bridges Lithium-Ion Batteries , Modular Multilevel Converters , and Smart Battery Systems . Education : Not explicitly mentioned in the text. Research Interests focus on Battery Management Systems , AI-Driven Energy Optimization , and Power Electronics for renewable energy integration. Key projects include Digital Twin for Lithium-Ion Batteries and BMS-DC for Data Centers . Recent Publications (2025) emphasize Finite Set MPC , Gradient Descent Optimization , and AI in Battery Parameter Estimation . His 2024 work explores Physics-Informed Neural Networks and Fault-Tolerant Converters . Scientific Awards : Villum Foundation Grant (313 million kroner, 2021) Named world's best in electrical engineering (2023) Advising includes supervising PhD projects on AI-Accelerated Battery Twins and Data-Driven SOH Estimation . Collaborations span Energy Cluster Denmark and Villum Fonden .

• Battery (Electrochemical Energy Engineering)
• Modular Multilevel Converter
• Lithium-Ion Batteries
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Kunihiko Kaneko is a Professor at the Niels Bohr Institute, University of Copenhagen, with a distinguished career in theoretical biophysics and complex systems. He received his PhD and MSc in Physics from the University of Tokyo, and has held leadership roles at the Universal Biology Institute and Center for Complex Systems Biology. PhD Physics, 1984 - University of Tokyo MSc Physics, 1981 - University of Tokyo His research spans five primary areas: Universal Biology, Evolutionary Constraints, Ecosystem Dynamics, Neural Cognition, and Universal Anthropology. He has published extensively on multi-level consistency principles, dimensional reduction in biological systems, and reciprocity between robustness and plasticity across scales. Recent publications show strong focus on microbial ecosystems (2025), evolutionary game theory (2025), neural modular architectures (2024), and dimensional reduction in cellular systems (2024). His work bridges physics and biology through dynamical systems theory applied to diverse phenomena from protocells to human societies.

• Theoretical Biophysics
• Complex Systems
• Chaos
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Christian Igel is a Professor at the Department of Computer Science, University of Copenhagen, and serves as director of the SCIENCE AI Centre . He is also a co-lead of the Pioneer Centre for Artificial Intelligence in Denmark. His academic journey includes a Doctoral degree from Bielefeld University (2002) and a Habilitation degree from Ruhr-University Bochum (2010). Igel is a Juniorprofessor (2002–2010) and has held editorial roles at journals like KI - Künstliche Intelligenz and Artificial Intelligence Journal . Doctoral degree: Faculty of Technology, Bielefeld University, Germany (2002) Habilitation degree: Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum, Germany (2010) His research spans Machine Learning , focusing on Support Vector Machines , Evolution Strategies , Reinforcement Learning , Deep Neural Networks , and PAC-Bayesian Analysis . He applies these methods to Environmental Monitoring , Medical Diagnostics , and Climate Research . Recent publications highlight work on adversarial machine learning , environmentally sustainable AI , and tree resource mapping using deep learning. His scientific awards include being a ELLIS Fellow . Igel’s software tools like Shark , woody , and Multi-Planar UNet are widely used in research and industry. Notable grants and collaborations involve projects with European Lab for Learning and Intelligent Systems (ELLIS) , SCIENCE AI Centre , and international teams in Denmark , Germany , and France . His lab leadership emphasizes open-source frameworks and reproducible research. Editorial Roles: German Journal on Artificial Intelligence , Evolutionary Computation Journal , Artificial Intelligence Journal Software Projects: Shark , woody , Multi-Planar UNet , U-Time Collaborations: SCIENCE AI Centre , Pioneer Centre for Artificial Intelligence , European Lab for Learning and Intelligent Systems

• Machine Learning
• Pattern Recognition
• Classification
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Navid Bayati is an Associate Professor at the University of Southern Denmark, affiliated with the Institute of Mechanical and Electrical Engineering and the Centre for Industrial Electronics. He leads the Control and Protection of Smart Grids (CAP-SG) group and focuses on renewable/hybrid power systems, microgrid protection, and grid code compliance. Education: Ph.D. in Power Systems & Microgrid Protection (2020, Aalborg University); M.Sc. in Power Systems (2017, Amirkabir University of Technology) His research spans renewable energy integration , transient analysis , grid interconnection , and digital twin applications . Recent work includes machine learning for carbon emission prediction, fault localization in DC microgrids, and supercapacitor resilience in hybrid systems. Collaborations include projects like IEA Wind Task 50 and RePoSys , addressing grid renovation, life cycle assessment, and digital twin resilience. His teaching portfolio covers power electronics , energy management , and microgrid control .

• Renewable/Hybrid Power Systems
• Protection and Transient Analysis of Power Grids
• Microgrids and Active Energy Networks
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Yanbo Wang is an Associate Professor and Vice Head of the Wind Power Research Programme at AAU Energy, part of Aalborg University's Faculty of Engineering and Science. He leads research in Electric Power Systems and Microgrids, focusing on intelligent energy systems and flexible markets. His work emphasizes stability analysis, control strategies for hybrid AC/DC systems, and renewable energy integration. He supervises multiple PhD projects on topics like multi-port energy routers and wind power converter optimization. Research interests include power electronics, microgrid stability, and energy storage systems. Key projects include the EU-funded 'S3SF: Smart Energy Solutions for Sustainable Future' and machine learning-based control strategies for multi-energy systems. He has authored over 176 publications, with recent work on DC microgrid reliability, converter design, and offshore wind energy systems. His team collaborates internationally to advance grid-friendly technologies and smart energy solutions. Notable contributions include advanced control schemes for retired batteries in DC microgrids and stability assessment methodologies for offshore wind inverters. He advises on six PhD projects and maintains a lab focused on renewable energy systems and power electronics innovation.

• Power Systems
• Renewable Energy
• Microgrid Control
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Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

• Internet of Things
• Optical Networking
• Wireless Communication
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Jan Engelhardt serves as Assistant Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specializing in e-mobility and prosumer integration within power and energy systems. His work directly contributes to UN Sustainable Development Goals through grid modernization and renewable energy integration. His research focuses on electric vehicle-grid integration , with core expertise in battery energy storage systems, DC microgrids, and virtual power plants. Key investigation areas include smart charging architectures for EV clusters, frequency response services, phase balancing techniques, and V2X management strategies. His experimental approach combines theoretical modeling with real-world validation of control systems for enhanced grid stability. Recent publications demonstrate a clear trend toward distributed control solutions for electric vehicle clusters, emphasizing user-centric scheduling while providing grid services. His work increasingly incorporates experimental validation of frequency control architectures and explores high-power reconfigurable battery applications for fast-charging infrastructure. Dr. Engelhardt actively supervises PhD candidates on projects including Hybrid Energy Solutions (EV charging and battery storage synergies) and Provision of Grid Services through EV Aggregation. He participates in major EU initiatives like EV4EU (Electric Vehicles Management for Carbon Neutrality in Europe) and GREAT (GRid Enhancement for Ancillaries in Tomorrow’s power systems), securing substantial research funding through Horizon Europe frameworks.

• Electric Vehicle Systems
• Battery Energy Storage
• Power System Integration
• +۴ مورد دیگر

Jens Honore Walther is a Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on fluid mechanics, coastal and maritime engineering, and computational fluid dynamics (CFD). He leads projects on wave energy converters, multiphase flow systems, and thermal energy applications. His work contributes to sustainable development goals related to clean energy and climate action. External Roles: Research associate at ETH Zurich (2003–present) Postdoctoral fellow at ETH Zurich (2000–2003) Project manager at Danish Maritime Institute (1996–1997) Research scientist at Danish Meteorological Institute (1994–1996) Research Interests: Walther’s expertise spans CFD modeling, granular flow dynamics, and nanofluidics. His recent projects include optimizing wave energy converters, analyzing gap resonances in marine structures, and developing multiphase ejector geometries for heat pumps. His work integrates high-performance computing and experimental validation to address challenges in marine engineering and energy systems. Advising & Projects: He supervises PhD students in areas such as elite sport aerodynamics, gas lubrication, and alternative fuel combustion. Notable projects include: Elite sport aerodynamics (2024–2026) Alternative fuel injection in marine engines (2023–2026) Multi-physical gas bearing modeling (2024–2027) Labs & Collaborations: Walther collaborates with institutions like ETH Zurich and engages in experimental facilities at DTU. His group focuses on advanced CFD simulations and fluid-structure interaction studies.

• Fluid Mechanics
• Coastal and Maritime Engineering
• Computational Fluid Dynamics
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Arash Nemati is an Assistant Professor at the Department of Energy Conversion and Storage, Technical University of Denmark (DTU). His research focuses on sustainable energy technologies, particularly solid oxide fuel cells, ammonia-fueled systems, and multiphysics modeling of energy conversion processes. He leads and participates in EU-funded projects such as RESCUE and X-SEED, aiming to advance renewable energy storage and green hydrogen production. His work addresses challenges in electrochemical systems, including durability, efficiency, and integration of renewable energy sources. He has received notable recognition, including a Highly-cited Paper award (Web of Science, 2022) and the DAAD Green Hydrogen Research Tour Scholarship (2024). Nemati actively supervises PhD students in areas like co-electrolysis and solid oxide electrolysis cell modeling. His expertise spans thermochemical processes, numerical simulations, and techno-economic evaluations of energy systems. Key projects include developing ammonia-driven reversible solid oxide cells for grid storage and optimizing pyrolysis-electrolysis systems for methanol and char production. His research aligns with UN Sustainable Development Goals, emphasizing clean energy and climate action.

• Solid Oxide Fuel Cells
• Renewable Energy
• Electrochemistry
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