Ju Feng is a Senior Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in Wind Energy Systems , Wind Farm Optimization , and Control Strategies . He contributes to research in Floating Offshore Wind Farms , Multi-Disciplinary Optimization , and Noise Propagation . His work includes developing simulation tools, wake models, and control frameworks for wind farms in complex environments. Research Interests: Optimization of wind farm design and operation Advanced wake and flow modeling AI-driven wind energy solutions Noise control and acoustic propagation Multi-fidelity/multi-disciplinary modeling Cost-effective wind farm technologies Publication Trends: Ju Feng's recent work (2022-2024) focuses on floating offshore wind farms , noise constraints , and multi-disciplinary integration . Older articles (2012-2017) emphasize control algorithms , wake modeling , and optimization frameworks . Advising: Supervising PhD Student Wang R. (AI-Augmented Wind Farm Design Optimization, 2025-2028) Co-supervising Nyborg C. M. (Noise Control in Wind Farms, 2019-2023) Collaboration Network: Active in international projects like DecoWind, ModFarm, and FarmConners. Collaborates with institutions such as DTU Wind Energy and researchers including Shen W. Z. , Réthoré P.-E. , and Bredmose H. .
Chiara Fratini is a Senior Researcher at the Department of Environmental and Resource Engineering Water Systems at the Technical University of Denmark (DTU) in Kgs. Lyngby, Denmark. She holds a PhD in Planning and Governance of Critical Infrastructures for Sustainability Transitions and is actively engaged in research at the intersection of society, technology, and environmental systems, with particular focus on urban sustainability transitions. Dr. Fratini's research spans multiple domains of sustainability science. Her theoretical work centers on science and technology studies (STS), transition theories, and institutional analysis, while her empirical research focuses on urban infrastructure systems, particularly water management. She investigates nature-based solutions, climate change adaptation strategies, participatory governance processes, and the implementation of socio-technical imaginaries like Nature-Based Solutions and the Water-Energy-Food Nexus. Her work consistently addresses the social dimensions of sustainability transitions, with growing emphasis on justice and equity considerations in circular economy approaches. Analysis of Dr. Fratini's publication record reveals a strong focus on urban sustainability transitions, particularly in water management systems. Her research has evolved from detailed case studies of Danish urban water systems toward broader theoretical contributions to sustainability transitions theory and comparative international work. A notable trend is the increasing attention to governance dimensions, justice considerations, and the social implications of circular economy approaches within sustainability transitions research, reflecting the maturation of the field toward more holistic understandings of sustainability challenges. Current Supervision: Stoumpou, V. (PhD project: Decentralized treatment of household wastewater by membrane-based technologies, 2024-2027) Collaborative Networks: Extensive international collaborations, particularly with researchers in Germany and the United Kingdom on energy transitions and urban sustainability governance Research Impact: Work referenced in policy sources and widely shared on social media, indicating practical relevance to sustainability governance Dr. Fratini's research is organized around understanding the complex interplay between technological systems, social practices, and governance arrangements in urban sustainability transitions. Her work on urban water systems in Copenhagen represents a significant case study in how cities can navigate transitions toward more sustainable water management practices through innovative governance approaches and public engagement, with implications for sustainable development globally.
Andreas Aakerberg is an Assistant Professor at Aalborg University's Department of Architecture, Design and Media Technology within the Technical Faculty of IT and Design. His research focuses on Deep Learning applications in Image and Video Enhancement, particularly for Forensics, Surveillance, and Computational Photography. He is affiliated with the Visual Analysis and Perception and AI for the People research groups. His work contributes to UN Sustainable Development Goals through advancements in technology and accessibility. Key research interests include Super-Resolution techniques, Low-Light Image Enhancement, and Generative AI. He has developed datasets like RELLISUR and Spatially Variant Super-Resolution (SVSR) to advance real-world applications. His publications address challenges in surveillance systems, thermal imaging, and semantic segmentation. Aakerberg teaches Deep Learning, MLOps, and Image Processing, emphasizing practical, industry-relevant skills. Notable contributions include the PDA-RWSR method for pixel-wise degradation adaptation and the RELIEF framework for joint low-light enhancement and super-resolution using transformers. His work bridges theoretical advancements with real-world usability, such as improving face-image resolution from surveillance cameras.
Sergey Sorokin is a Professor in the Department of Materials and Production at Aalborg University, Faculty of Engineering and Science, Denmark. His research centers on solid and computational mechanics, with a focus on structural dynamics, wave propagation, vibro-acoustics, and finite element modeling. His research interests include: Wave propagation in periodic and elastic structures Vibro-acoustics and noise control Finite element methods and reduced-order modeling Nonlinear dynamics of beams and shells Acoustic black hole effects and vibration suppression Structural optimization and industrial system analysis The recent publications (2020–2025) demonstrate sustained activity in mechanical wave analysis, nonlinear structural behavior, and acoustic optimization. Key themes include the suppression of bending waves, asymptotic modeling of cylindrical shells, and bi-orthogonality in waveguides. These works reflect an interdisciplinary blend of theoretical mechanics, numerical simulation, and engineering applications. Scientific contributions include: Active participation in long-term research projects on mechanical vibro-acoustics and wave transmission since 2010 Supervision of at least four PhD students Extensive publication record (188 research outputs) with consistent contributions to journals like the Journal of the Acoustical Society of America and European Journal of Mechanics A/Solids He has advised several researchers and contributed to collaborative projects involving structural optimization and industrial component analysis. His work is deeply integrated into both theoretical and applied mechanical engineering, with emphasis on modeling and enhancing structural performance under dynamic loads. Sergey Sorokin is actively involved in research through ongoing projects such as 'Mechanical Vibro-Acoustics and Noise' and 'Analysis and Optimization of Wave Propagation in Periodic Structures'. These efforts are supported by advanced computational modeling and collaboration with peers like N. Olhoff and E. Lund.
Josep M. Guerrero is a Professor at the Faculty of Engineering and Science, Aalborg University, specializing in Electric Power Systems and Microgrids. He holds advanced degrees in Electronic Engineering, Psychobiology, and Cognitive Neuroscience, and is a Villum Investigator with the Villum Foundation since 2019. His research focuses on microgrid control strategies, renewable energy integration, and power electronics for sustainable energy systems. Education: M.Sc. in Electronic Engineering, Ph.D., M.Sc. in Psychobiology and Cognitive Neuroscience Current Roles: Project Participant (NEST), Supervisor (4 PhD projects), Member of National Committee for Research Infrastructure (NUFI) Research interests span microgrid engineering, control strategies, and energy systems. His recent work includes decentralized control for shipboard power systems, fractional-order regulators for grid-forming converters, and hybrid energy storage optimization for seaports. Publications emphasize agricultural microgrids, cascaded converter synchronization, and sustainable heavy microgrids. Scientific awards include: CSEE Journal of Power and Energy Systems Excellent Paper Award (2024) IEEE Modeling and Control Technical Achievement Award (2023) IEEE PES Douglas M. Staszesky Distribution Automation Award (2022) IEEE Bimal Bose Award for Industrial Electronics Applications (2021) Best Paper Award (2021) He has supervised 39 PhD students and leads 8 ongoing projects, including NEST (National Research Infrastructure Roadmap) and LastWind (Ethiopian wind integration). Media coverage highlights his global recognition as a leading researcher in electrical engineering and contributions to sustainable energy solutions.
Christa Gall is an Associate Professor at the Niels Bohr Institute , University of Copenhagen, specializing in astrophysics within the DARK and Cosmic Dawn Center (DAWN) research groups. Her work focuses on the life cycle of cosmic matter, particularly elemental synthesis in massive stars and subsequent cosmic dust formation. Research Areas : Astrophysics, Cosmic Dust Evolution, Supernovae Studies, Galaxy Formation, Machine Learning Applications Projects : Villum Experiment COSMO-BRIDGE, LSST transient follow-up systems, Gravitational Wave Multi-messenger Studies Methodologies : Bayesian modeling, Hierarchical data analysis, Multi-wavelength observations Her publications demonstrate expertise in Type Ia supernova standardization, dust removal timescales in galaxies, and real-time transient detection systems. She contributes to machine learning implementations for time-domain astronomy and gravitational wave counterpart studies. Collaborations span institutions in Europe, North America, and Asia, with recent work appearing in Astronomy & Astrophysics and Monthly Notices of the Royal Astronomical Society . She actively participates in international telescope campaigns and data stream optimization initiatives.
Daniel Lee Ashbrook is an Associate Professor in the Department of Computer Science at the University of Copenhagen (DIKU). He specializes in Human-Centred Computing, focusing on tangible user interfaces, wearable technology, and computational fabrication. His work bridges hardware innovation with practical applications in interactive design. Research Themes : Embedded sensors, 3D-printed interactive systems, pneumatic computing, and accessible fabrication tools. Collaborations : Regularly works with researchers like Victor Savage and Hyeon-Jeong Kim on novel interface technologies. Recent publications highlight advancements in tactile feedback systems, multi-material fabrication, and sensor integration in everyday objects. His projects often combine physical and digital elements for intuitive user experiences. Key trends include democratizing hardware prototyping and enabling electronics-free interactivity. Awards : ISWC 2012 Best Papers Award. Contact : Email dan@di.ku.dk or call +45 53638312.
Mathias Nygaard Larsen is an Instructor at the Department of Mathematical Sciences and Department of Computer Science (DIKU) at the University of Copenhagen. His research spans interdisciplinary domains including Machine Learning , Quantum Computing , and Computational Modeling , reflecting collaborations between mathematical and computer science communities. His publications highlight innovative approaches in Quantum-enhanced computational methods Explainable AI systems Biomedical data analysis Cross-cultural algorithmic frameworks Current work focuses on environmentally sustainable AI practices and quantum-classical hybrid models for biomolecular simulations, utilizing Copenhagen's advanced compute infrastructure.
Zakka Ugih Rizqi is a Researcher at Aalborg University's Department of Materials and Production within the Faculty of Engineering and Science. His research focuses on optimizing decision-making through the fusion of optimization techniques, multi-method simulation, and data science, with primary applications in supply chains, energy systems, and smart manufacturing. He currently contributes to the design of future aseptic production systems through the AP2030 project. He holds a Ph.D. in Industrial Engineering from National Taiwan University of Science and Technology (2022–2024). Research Interests: His work emphasizes realistic modeling of complex systems, including uncertainty and dynamic complexity. Key areas include simulation-based Digital Twin frameworks for smart warehouses, energy-efficient AS/RS configurations, and system dynamics modeling for policy analysis. He explores multi-objective optimization approaches to balance operational efficiency and environmental sustainability. Projects & Grants: He participates in the AP2030: BRD Aseptic Factory 2030 (2023–2027), focusing on aseptic production innovation. His research has been recognized with awards such as The Best Paper Award (2023) and The Best Presenter Award (2023). Collaborations: Recent visits include The University of Tokyo, Kyoto University, and Tohoku University (2024). He has presented at conferences like the National University of Singapore's Analytics for X 2023. Labs & Teams: Engaged in interdisciplinary teams within the Faculty of Engineering and Science, collaborating on projects blending automation, sustainability, and data-driven decision-making.
Professor Juan C Vasquez is a faculty member at Aalborg University's Department of Energy Technology, serving as Co-Director of the Center for Research on Microgrids (CROM). Recognized as a Highly Cited Researcher (2017-2023), his work spans technical and interdisciplinary domains in energy systems, with a focus on microgrids, renewable integration, and cybersecurity. His research includes smart grid control, power electronics reliability, and AI-driven energy management systems. He also explores computational creativity in electroacoustic music, evidenced by performances at ISEA 2025 and ACMC 2024. Key subtopics involve fault diagnosis, EV infrastructure, and resilience analysis for disaster-struck communities. Scientific accolades include a First Prize at the 'Città di Barletta' competition. His publications bridge energy technology and digital arts, reflecting a unique interdisciplinary approach to sustainable energy systems and computational sound design.
Ulrik Pagh Schultz Lundquist is a Professor at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), where he serves as Head of both the SDU UAS Center and SDU Climate Cluster. With over 123 research outputs spanning robotics, drone technology, and programming languages, Lundquist leads significant initiatives including WildDrone (2023-2026) and Terra Salva (2024-2026), and has established himself as a leading expert in unmanned aerial systems research with extensive field applications in wildlife conservation. Lundquist's research focuses on the intersection of robotics and environmental science, with particular expertise in drone swarms for ecological monitoring. His work bridges theoretical computer science with practical conservation challenges, developing programming languages and formal models specifically for modular robotics systems. Key research thrusts include minimizing wildlife disturbance through optimized drone operations, multi-perspective data collection techniques, and scalable BVLOS (Beyond Visual Line of Sight) systems for conservation areas. His fingerprint analysis reveals strong contributions to domain-specific languages (67%), unmanned aerial vehicles (28%), and object-oriented programming (28%). Recent publications demonstrate a clear trajectory toward practical conservation applications, with increasing emphasis on ethical drone deployment, wildlife disturbance minimization, and operational safety in complex environments. Lundquist's work shows growing integration of swarm intelligence techniques with traditional conservation practices, particularly in African ecosystems as evidenced by field trials at Kenya's Ol Pejeta Conservancy. Lundquist actively leads multiple research projects including WildDrone (focusing on multi-perspective animal monitoring), Terra Salva (terahertz data transmission via drones), and a High Altitude Balloon platform for vegetation monitoring. His professional leadership includes chairing the ACM International Conference on Generative Programming Steering Committee (2019-2022) and significant roles in COST Action IC1405 (2015-2019). As a highly visible expert, he has contributed to 107 media appearances, frequently advising on drone policy including Denmark's regulatory approaches to drone safety and wildlife protection. As Head of the SDU UAS Center, Lundquist directs a multidisciplinary research team specializing in conservation drone technology. The center maintains strong international collaborations, particularly with African conservation organizations, focusing on developing drone swarm methodologies that balance data quality with minimal ecological disturbance. Current team efforts prioritize field-deployable systems that can operate effectively in remote natural habitats while providing conservationists with high-quality multi-perspective monitoring capabilities.
Theresia Veronika Rampisela is a PhD student and Guest Researcher in the Department of Computer Science at the University of Copenhagen's Faculty of Science, specializing in Machine Learning. She actively contributes to the Algorithms, Data, and Democracy (ADD) project (https://algorithms.dk/), which investigates the societal implications of algorithmic decision-making systems. Her academic background includes a Master's degree in Computer Science from the University of Indonesia, providing foundational expertise in computational methods and data analysis. This education has enabled her transition from early work in information retrieval to specialized research in algorithmic fairness. Rampisela's research program critically examines fairness evaluation in machine learning applications, with particular focus on recommender systems. She investigates both group and individual fairness metrics, exploring their practical implementation challenges and limitations. Her work addresses the fundamental tension between recommendation relevance and equitable treatment of diverse user populations. Earlier research included academic expert finding using semantic techniques and medical applications involving schizophrenia classification with SVMs. Analysis of her publication trajectory reveals progressive sophistication in algorithmic fairness research. Starting with foundational work on expert finding systems, she has advanced to developing novel frameworks like Pareto optimization for balancing competing objectives in recommendation algorithms. Her publications in top venues including ACM Transactions on Recommender Systems and the ACM SIGIR Conference demonstrate growing recognition in this critical field. Mensa International Scholarship (2024) Rampisela collaborates extensively with Maria Maistro, Tuukka Ruotsalo, and Christina Lioma through the ADD project. Her research has significant practical implications for technology companies developing recommendation systems and policymakers regulating algorithmic fairness. She maintains an active scholarly profile documented through her ORCID (https://orcid.org/0000-0003-1233-7690) and demonstrates growing influence with mentions across academic social platforms.
Mette Termansen is a Professor in the Department of Food and Resource Economics at the University of Copenhagen, specializing in spatially explicit economic analysis of land use decision-making, ecosystem service valuation, and environmental policy design. Her current leadership of the H2020 EFFECT project focuses on optimizing voluntary environmental schemes for farming systems across Europe. Her academic credentials include: 2005: YCAP York Certificate of Academic Practices (MA Level), University of York 2001: DPhil in Environmental Economics and Environmental Management, University of York 1996: MSc in Environmental Economics, University of York 1994: MSc in Forest Science, Royal Veterinary and Agricultural University, Copenhagen Termansen's research centers on quantifying trade-offs between agricultural production and environmental objectives, with emphasis on biodiversity conservation, climate adaptation, water quality, and recreational values. She develops spatially explicit models to evaluate policy impacts, particularly investigating how alternative contract designs influence farmer participation and environmental outcomes in agri-environmental schemes. Her interdisciplinary approach integrates ecological data with economic behavior to inform evidence-based environmental governance. Analysis of her 2024-2025 publications reveals consistent methodological focus on integrated environmental-economic modeling, scenario analysis, and policy pathway evaluation. Key thematic clusters include spatial optimization of land use for multiple environmental goals, behavioral insights in agricultural decision-making, and valuation frameworks incorporating diverse societal values of nature. Her work predominantly addresses European agricultural contexts with strong policy relevance for nitrogen regulation, biodiversity protection, and climate mitigation. Termansen teaches BSc and MSc modules in Environmental and Natural Resource Economics while leading externally funded research initiatives. Her primary active grant is the Horizon 2020 EFFECT project, with additional collaborations conducted through contractual agreements with the Danish Ministry of Environment and Food. She maintains partnerships with agricultural producers, marine sectors, and environmental NGOs, primarily serving in advisory capacities within research consortia where the University of Copenhagen acts as the contracting entity.
Professor Peter Nielsen is a faculty member at Aalborg University's Department of Materials and Production, part of The Faculty of Engineering and Science. He specializes in Artificial Intelligence for Operations Research, focusing on logistics optimization, unmanned aerial vehicles (UAVs), and heuristic algorithms. His work bridges theoretical research and practical applications in industrial automation and sustainable systems. He has led or participated in multiple research projects, including the ORMS project (Operational Reliability Management System) and the ValuePole initiative, which addressed value chain optimization for SMEs. His research emphasizes AI-driven solutions for maritime search and rescue, UAV operations in dynamic environments, and autonomous systems for healthcare logistics. Notable research interests include optimizing routing and scheduling problems, trustworthiness in autonomous vehicle algorithms, and cross-infection risk mitigation in indoor environments. His contributions span over 210 publications, with recent work highlighted in journals like Journal of Intelligent and Robotic Systems and Marine Policy . Peter has advised two PhD students and contributed to academic activities as a peer reviewer for Production & Manufacturing Research . His work often integrates computational fluid dynamics (CFD) and Taguchi methods for optimizing ventilation systems and reducing disease transmission risks.
Muhammad Usman Tahir is a Postdoctoral Researcher at Aalborg University's Faculty of Engineering and Science within the Department of Applied Power Electronic Systems. His primary affiliation is with AAU Energy, where he conducts research on advanced battery technologies and power electronic systems for sustainable energy applications. His research focuses on lithium-ion battery optimization, particularly multi-stage charging strategies for electric vehicles and energy storage systems. Key interests include thermal management during charging, cycle life extension, charging time reduction, and reliability-oriented design of battery management systems. His work bridges theoretical modeling with experimental validation to address real-world challenges in battery performance and safety. Analysis of his 2023-2025 publications reveals a concentrated effort on multi-stage constant current charging techniques, with significant contributions to understanding performance trade-offs between charging speed, temperature rise, and battery degradation. His research increasingly incorporates optimization frameworks and expands into multi-source power system control for specialized applications like shipboard networks. Dr. Tahir serves as Principal Investigator for the project "Reliability-Oriented Fast Charging Strategies for Lithium-Ion Batteries and EV Chargers" (2022-2025) and participates in the Horizon Europe SOLARIS project (2024-2028) focused on solar energy systems and drone-based maintenance. His collaborative work spans multiple international research groups within Aalborg University's energy ecosystem.
