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Frede BlaabjergView profile

Professor

• Power Electronics
• Wind Turbines
• Photovoltaic (PV) Systems
• +6 more

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)

Hossein NamiView profile

Associate Professor

• Power-to-X
• Hydrogen
• E-fuel
• +3 more

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.

• Machine Learning
• Pattern Recognition
• Classification
• +6 more

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

• Computer Vision
• Image Analysis
• Machine Learning
• +5 more

Serge Belongie is a Professor at the Department of Computer Science (DIKU) at the University of Copenhagen, where he holds dual affiliations with the Pioneer AI research section and the Image Analysis, Computational Modelling, and Geometry section. His academic position places him at the forefront of interdisciplinary research connecting computer vision with language models, geospatial analysis, and cultural understanding. Professor Belongie's research program encompasses several critical domains in modern artificial intelligence: Advanced computer vision and image analysis techniques Vision-language model integration and multimodal systems 3D point cloud processing and semantic segmentation Geospatial representation learning for environmental applications Fine-grained object recognition and detection Cultural context understanding in AI systems His recent publication record reveals a sophisticated trajectory toward developing precise control mechanisms for vision-language models, with applications spanning forensic analysis, cultural heritage preservation, and social media understanding. The research demonstrates increasing sophistication in handling cultural context and enabling fine-grained manipulation of visual content through natural language interfaces. Professor Belongie maintains an active research group producing significant scholarly output, with over 280 research publications documented in his academic profile. His work is supported by research funding that enables cutting-edge exploration in multimodal AI systems with practical societal impact. He plays a key role in the Pioneer AI center at the University of Copenhagen, which focuses on advancing artificial intelligence through interdisciplinary collaboration and innovative research approaches that bridge theoretical computer science with real-world applications.

Fabio PierellaView profile

Associate Professor

• Offshore Wind Energy
• Fluid Dynamics
• Structural Engineering
• +3 more

Fabio Pierella is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Wind and Energy Systems Flows, specializing in Wind Turbine Design Division. His research focuses on offshore wind energy systems, fluid dynamics, and structural engineering. He has contributed to projects like OC6 Phase IV and the DeRisk database, validating numerical models for floating offshore wind structures and extreme wave loads. Key research interests include computational fluid dynamics (CFD), hydrodynamic load modeling, and the design of large-scale floating wind turbines. His work spans numerical simulations, experimental validation, and database development for extreme sea states. Pierella has presented at international conferences on topics like wave-structure interaction and turbine control systems. He received the Best Poster Presentation Award (2024) and contributed to datasets such as the DeRisk Database, which provides critical wave data for offshore wind turbine design. His research emphasizes practical applications, including monopile structural integrity under extreme loads and control strategies for floating platforms. Pierella's activities include conference presentations on ultra-large floating turbines (EMULF2 project) and the impact of wave shape on 15MW turbine loads. His interdisciplinary approach integrates computational models with experimental results to address challenges in offshore renewable energy systems.

• Bayesian Machine Learning
• Medical Image Analysis
• Graph-based Learning
• +3 more

Raghavendra Selvan, an Assistant Professor (Tenure Track) at the University of Copenhagen, holds joint appointments in the Machine Learning Section (Department of Computer Science), Kiehn Lab (Department of Neuroscience), and the Data Science Laboratory. His academic journey includes a PhD in Medical Image Analysis (2018), MSc in Communication Engineering (2015), and BSc in Electronics and Communication Engineering (2009). PhD - Medical Image Analysis, University of Copenhagen (2018) MSc - Communication Engineering, Chalmers University (2015) BSc - Electronics and Communication Engineering, BMS Institute of Technology, India (2009) His research focuses on Bayesian Machine Learning with emphasis on Medical Image Analysis, Graph-based Learning, Tensor Networks, Approximate Inference, and Multi-Object Tracking Theory. Recent publications highlight his contributions to environmentally sustainable AI practices, efficient deep learning in medical imaging, and novel applications of tensor networks. Key research areas: Green AI and Environmental Sustainability Medical Image Analysis Graph Neural Networks Crystal Structure Prediction Model Compression Materials Science Applications

Tuukka RuotsaloView profile

Associate Professor

• Brain-Computer Interfaces
• Human-Information Interaction
• Recommender Systems
• +4 more

Tuukka Ruotsalo serves as Associate Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His research bridges human cognition with computational systems through brain-computer interfaces and physiological computing. As Academy Research Fellow at University of Helsinki (2019-2024), he maintained dual institutional affiliations while leading cutting-edge work in neuro-linguistic modeling and affective relevance. His research focuses on brain-computer interfaces for information retrieval , where he pioneers methods to decode cognitive states from neural signals to improve search systems. Key areas include affective relevance modeling that integrates emotional states into search algorithms, and neuro-linguistic reconstruction that translates brain activity into language. His work on fairness-relevance tradeoffs in recommender systems established Pareto frontier evaluation frameworks now widely adopted in ethical AI research. Recent publications demonstrate how physiological signals like EEG and galvanic skin response can create more adaptive human-information interaction systems. Ruotsalo's scientific recognition includes the prestigious Academy Research Fellow position. His publications in IEEE Transactions on Human-Machine Systems , Journal of the Association for Information Science and Technology , and Communications Biology reveal growing interdisciplinary impact. His advising spans cognitive neuroscience and machine learning students, with notable collaborations across the SCIENCE AI Centre. Current projects include the TreeSense initiative for remote sensing of global tree resources and development of quantum-inspired neural architectures. His lab leverages the department's powerful compute cluster for large-scale physiological data analysis.

Peyman Afzali GorouhView profile

Researcher

• Power Engineering
• Smart Grids
• Renewable Energy Systems
• +5 more

Peyman Afzali Gorouh is a Postdoctoral Researcher in the Applied Power Electronic Systems group within the Faculty of Engineering and Science at Aalborg University, Denmark. His research focuses on developing innovative models for energy communities, smart grids, and renewable energy integration. Dr. Afzali's research interests span power engineering, smart grid technologies, renewable energy systems, and energy communities. His work particularly emphasizes prosumer economics, peer-to-peer energy trading, risk modeling in power systems, and energy democracy frameworks. He has developed novel approaches for optimizing energy communities while considering socio-economic-environmental factors, demand response, and uncertainty management. His recent publications (2020-2024) demonstrate a consistent focus on energy community modeling, with particular emphasis on peer-to-peer trading mechanisms, risk-constrained optimization, and multi-objective planning. His work bridges technical power system challenges with socio-economic considerations, creating integrated models that address both engineering and human aspects of modern energy systems. Dr. Afzali maintains an active research profile with numerous publications in high-impact journals including IEEE Transactions on Engineering Management, Energy and Buildings, Applied Sciences, and Sustainable Cities and Society. His research shows strong international collaboration, particularly with researchers from Iranian institutions.

Torben Anker LenauView profile

Associate Professor

• Biomimetics
• Engineering Design
• Sustainable Design
• +3 more

Torben Anker Lenau is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His work focuses on biomimetic design, sustainable engineering, and innovative material applications. He leads research projects addressing multi-functional problem-solving, renewable energy systems, and eco-design principles. His expertise contributes to UN Sustainable Development Goals, particularly in sustainable cities, clean energy, and responsible consumption. Key research interests include biomimicry in product development, lifecycle assessment, and bio-inspired materials. Notable projects include kinetic energy harvesting for wildlife tracking and bio-inspired medical devices. He has published extensively on topics like prototyping strategies, material selection, and biomimetic self-healing systems. Projects: Integrated Design (1999–present), Processed Material Selection (1996–present), CAD/CAM Prototyping (1996–present) Contributions: Over 100 publications, 27 projects, and patents in medical and energy sectors His work emphasizes translating biological principles into engineering solutions for sustainability challenges. Collaborations span academia and industry, with a focus on global impact through innovative design methodologies.

Niels AageView profile

Associate Professor

• Topology Optimization
• Acoustics and Vibroacoustics
• Biomechanics
• +5 more

Niels Aage is an Associate Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on topology optimization, biomechanics, and multiphysics modeling, with applications in acoustic devices, biomedical implants, and microelectromechanical systems (MEMS). He holds roles such as Vice President of the International Society for Structural and Multidisciplinary Optimization (2023–2027). Education and Professional Background: Conducted a 5-month research visit at the University of Colorado, Boulder (USA) in 2010. Specializes in giga-scale numerical modeling, finite element methods, and topology optimization algorithms. Research Interests: Develops novel methods for topology optimization of fluidic, thermal, and acoustic systems. Explores applications in patient-specific spinal implants, metamaterials with vibroacoustic bandgaps, and nonlinear dynamic substructuring. His work integrates machine learning and reduced-order modeling for efficient simulation. Publications: Over 100 peer-reviewed articles, including recent contributions on connectivity promotion in topology optimization (2025), vibroacoustic metamaterial design (2025), and anatomically conforming spinal fusion cages (2024). Research emphasizes high-resolution modeling and bridging computational design with additive manufacturing. Scientific Awards: ISSMO Haftka Young Investigator Award (2021), Equinor Prize 2020, and Hyperion Innovation Excellence Award (2017). Recognized for contributions to structural optimization and computational mechanics. Advising and Grants: Supervises multiple PhD projects, including work on vibroacoustic shape optimization, quantum-opto-mechanical systems, and smart hearing aid modeling. Engages in collaborative projects funded by industry and academia. Labs/Teams: Collaborates with DTU’s Solid Mechanics group and industry partners on projects involving topology optimization, multiphysics simulation, and biomedical engineering. Active in international conferences and serves on editorial boards.

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +4 more

Jonas Vinther is a Research Fellow at the Department of Computer Science , University of Copenhagen, specializing in Machine Learning and its intersections with quantum computing, medical data analysis, and sustainability. He is also an external PhD student in the Quantum Information Science & Technology program at the Niels Bohr Institute. Email: jonas.vinther@nbi.ku.dk , jonas.vinther@di.ku.dk Location: Universitetsparken 1, 2100 København Ø His research spans quantum machine learning , AI ethics , medical imaging , and environmentally sustainable AI , with recent publications on topics ranging from quantum neural networks to fairness in recommender systems . He contributes to the SCIENCE AI Centre and collaborates on initiatives like TreeSense for global tree resource monitoring.

• Human-Computer Interaction
• Machine Learning
• Natural Language Processing
• +1 more

Sarah Frances Homewood is an Assistant Professor (Tenure Track) in the Department of Computer Science at the University of Copenhagen, affiliated with the Human-Centred Computing research section. Her research focuses on the intersection of human-computer interaction and artificial intelligence, with applications in healthcare, natural language processing, and interpretable machine learning. Her diverse research interests span Human-Computer Interaction, Machine Learning, Natural Language Processing, and Artificial Intelligence. Recent investigations include interpretability of large language models, clinical NLP applications, fairness in recommender systems, and quantum natural language processing. Analysis of her recent publications reveals strong emphasis on NLP interpretability techniques, healthcare applications of AI, and theoretical foundations of machine learning. Her work frequently bridges fundamental computer science with practical applications in medicine and human-centered systems. Emerging research directions include quantum NLP and protein sequence modeling. Dr. Homewood's research contributes to the Machine Learning Section's focus on both theoretical foundations and applied domains including medical data analysis and information retrieval.

Ivan Adriyanov NikolovView profile

Assistant Professor

• Computer Graphics
• Computer Vision
• Augmented Reality
• +6 more

Ivan Adriyanov Nikolov is an Assistant Professor at the Department of Architecture, Design and Media Technology within Aalborg University's Technical Faculty of IT and Design. He specializes in Computer Graphics, Computer Vision, and Augmented Reality, with a focus on 3D reconstruction techniques like Structure-from-Motion (SfM). His work bridges academic research and industrial applications, particularly in wind turbine blade inspection and educational technology. His educational background includes contributions to computer science education through innovative teaching methods. He has led projects like 'Drone Application for Pioneering Reporting in Wind Turbine Blade Inspection' (2017–2019) and 'Leading Edge Roughness - Wind Turbine Blades' (2015–2019), advancing drone-based inspection and 3D modeling for wind energy sectors. Research interests include synthetic data generation, environmental monitoring datasets (e.g., BrackishMOT, DigiWeather), and improving VR/AR user experiences. He has developed tools for dynamic lighting in pixel art games and multimodal guardian systems in VR. His datasets, such as Sewer Defect Point Clouds and Wind Turbine Blade SfM Reconstructions, are publicly available for academic use. He actively contributes to educational innovation, such as flipped classroom strategies to boost programming class engagement. His interdisciplinary approach spans computer graphics, AI-driven NPC interactions, and collaborative mixed-reality games for trust-building. Labs/Teams: Member of the Computer Graphics Group and Visual Analysis and Perception team at Aalborg University. Collaborates with industry partners on drone technology and environmental surveillance systems.

Haoshui YuView profile

Associate Professor

• Energy Engineering
• Chemical Process Systems Engineering
• Decarbonization
• +7 more

Haoshui Yu is an Associate Professor in the Department of Chemistry and Bioscience at Aalborg University’s Faculty of Engineering and Science in Esbjerg, Denmark. His research focuses on sustainable energy systems, decarbonization, and process systems engineering with a strong emphasis on energy storage, waste heat recovery, and renewable integration. He holds a visiting researcher experience at KU Leuven (June–August 2019) and has led significant projects like the 2022 initiatives on zero-emission energy systems and methane production using offshore infrastructure. His work bridges chemical engineering with environmental sustainability, addressing challenges in energy efficiency, carbon capture, and system optimization. Key research interests include Organic Rankine Cycles, compressed air energy storage (CAES), LNG cold energy utilization, and AI-driven process modeling. Over 68 publications since 2014 highlight contributions to energy systems, with recent work emphasizing machine learning applications in reactor design and system integration. Yu received the 2019 Excellent Researcher Award and has been actively involved in interdisciplinary collaborations, including visits to SLB (Schlumberger) in 2025. His lab’s projects often involve multi-objective optimizations and sustainability assessments, aiming to transition energy systems toward net-zero emissions.

Casper Schousboe AndreasenView profile

Associate Professor

• Topology Optimization
• Fluid Dynamics
• Heat Transfer
• +5 more

Casper Schousboe Andreasen is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Civil and Mechanical Engineering within the Solid Mechanics division. His research focuses on topology optimization, fluid dynamics, and thermal systems design, with applications in aerospace engineering, microfluidics, and sustainable energy systems. He holds a PhD (2011) and Cand. Polyt (2008) from DTU. Education: PhD in Engineering (DTU, 2011), Cand. Polyt (DTU, 2008) His research interests include fluid-structure interaction, aeroelastic wing design, thermal insulation optimization, and topology optimization for additive manufacturing. He leads projects on labyrinth seal optimization, thermal resistance walls, and high-resolution fluid topology design. His work contributes to UN Sustainable Development Goal 7 (Clean Energy) through innovative heat exchanger and insulation technologies. Recent projects involve optimizing 3D-printed walls for thermal resistance, topology-based design of hydraulic systems, and aeroelastic wing configurations under large deformations. He supervises multiple PhD students focusing on topics like exascale CFD, fiber-reinforced composites, and EHD calculations in marine engines. He is part of DTU's TopOpt group, collaborating internationally on fluid dynamics and structural optimization. His methodologies bridge computational mechanics and industrial applications, emphasizing manufacturability and high-performance design.