Markus Schaffer is a Researcher at Aalborg University, affiliated with the Department of Construction, Urban and Environmental Engineering under the Faculty of Engineering and Science. His work focuses on leveraging commercial smart heat and water meter data to drive building-specific renovation strategies, integrating these datasets with existing building information to create actionable insights for the scientific community. PhD-level contributions to energy data integration Automated disaggregation of space heating and domestic hot water demands at city scale Non-intrusive large-scale occupancy detection via water meter analytics Advanced clustering for energy data distillation His research portfolio extends to school renovation concepts, where he explores double-skin facades with diffuse ceiling ventilation through parametric simulations. He applies machine learning to Indoor Environmental Quality sensor data collaboration, and teaches master's courses in IT System Development and Sensitivity/Uncertainty Analysis. 2025: Residential Household Dataset publication 2024: 4 peer-reviewed journal articles across Energy, Data in Brief, and REHVA Journal 2023: 2 datasets and 3 conference participations 2022: District Heating data time-series publication Markus' scientific contributions align with UN Sustainable Development Goals 7 (Affordable Energy) and 11 (Sustainable Cities), with ongoing roles in IEA EBC Annex 84 (2020-2025) and FOREFRONT (2021-2024) projects.
Kim B. Wittchen is a Senior Researcher at Aalborg University's Department of Construction, Urban and Environmental Engineering, focusing on building sustainability. With expertise in civil engineering, energy efficiency, and climate adaptation, Wittchen contributes to research on nearly zero-energy buildings, energy demand management, and thermal storage capacity in building stocks. Wittchen's recent publications analyze NZEB regulations across Nordic countries, climate-adaptive building codes, and energy flexibility frameworks. Their work intersects with UN Sustainable Development Goals like Education and Climate Action. Best paper award, Cold Climate HVAC 2021 Active in academic activities, Wittchen organizes conferences (e.g., Nordic Symposium on Building Physics) and contributes to peer review. Their research emphasizes future climate extremes over historical averages, influencing building design and renovation policies.
Charles Anthony Bates serves as an External Associate Professor at the Department of Sustainability and Planning within The Technical Faculty of IT and Design at Aalborg University in Copenhagen. With a unique blend of academic expertise and extensive industry experience, Bates bridges theoretical knowledge with practical application in sustainable engineering. His dual career path spans both academia and industry, where he currently holds leadership positions at Danfoss Power Solutions while contributing to academic research and teaching. Industrial PhD in Science & Technology Studies, Aalborg University (2017-2020) MA in Professional Communication, Roskilde University (2014-2016) BSc in Mechatronic Production Engineering, University of Southern Denmark (2002-2005) Bates' research focuses on the intersection of hydraulic engineering, sustainable technology development, and organizational practices in high-tech industries. His work particularly examines how technology readiness levels coordinate development processes, how objects stage referential alignment in industrial-academic collaborations, and how sustainable design principles can be integrated into hydraulic motor technology. His fingerprint analysis reveals strong expertise in Hydraulics Material Science (100%), Hydraulic Motor Engineering (60%), Surface Roughness (26%), and related engineering disciplines. An analysis of Bates' publications reveals a consistent focus on practical applications of theoretical frameworks in hydraulic engineering. His work demonstrates how Science & Technology Studies concepts can be applied to solve real-world engineering problems, particularly in the development of sustainable hydraulic systems. The publications show increasing emphasis on environmental and governance aspects (ESG) in recent years, aligning with global sustainability goals and industry demands for more responsible engineering practices. Bates has been actively involved in knowledge transfer between industry and academia through various speaking engagements, including keynote presentations on multidisciplinary collaboration in high-tech industry and panel discussions on sustainable energy systems. His professional trajectory demonstrates a strategic integration of academic research with industry leadership roles, particularly in his capacity as Strategic Initiatives Leader and ESG Lead for Work Function Division at Danfoss Power Solutions. Principal Speaker at Graduation Ceremony for Engineers, SDU Sønderborg (2026) Keynote Speaker: Challenges and Benefits of Multidisciplinary Collaboration in High-tech Industry (2020) Panelist: Sustainable Future Energy Systems - Skills for the energy transition (2018) Bates maintains active connections with multiple academic institutions, including membership in the University of Southern Denmark organization since 2021, demonstrating his commitment to fostering academic-industry collaboration. His current trajectory shows progression toward increasingly strategic leadership roles that integrate technical expertise with sustainability considerations, reflecting the growing importance of ESG factors in engineering leadership.
Steffan Wittrup McPhee Christensen is an Associate Professor at the Department of Medicine and Health Technology , Aalborg University , Denmark. His work bridges musculoskeletal physiotherapy and clinical biomedicine , focusing on neck and back pain , pain sensitivity , and exercise-based interventions . Academic Roles : Board member of the International Association for the Study of Pain (IASP) and Danish Physiotherapists Research Foundation since 2023. Teaching Philosophy : Emphasizes problem-based learning (PBL) and clinical simulation to develop clinical reasoning and rehabilitation planning skills. Research Interests include: Musculoskeletal disorders (neck/shoulder/back pain) Pain sensitivity and movement analysis Exercise interventions and clinical guidelines Global Burden of Disease applications to chronic pain management His scientific contributions span 114 publications (2011–2025) and 19 media appearances , including critiques of postural correction clothing as pseudoscience. Education : PhD in Clinical Science and Biomedicine (2018) Assistant Professor of Education (2016–2017) External Associate Professor at University College of Northern Denmark (2018–present)
Mark C. Kelly is an Associate Professor in the Resource Assessment and Meteorology Wind Energy Systems Division at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). His research focuses on advancing wind energy modeling and resource assessment through sophisticated atmospheric science approaches. His primary research interests include: Atmospheric stability modeling and representation of buoyancy effects Atmospheric turbulence and subgrid modeling Scale-dependent terrain characterization Mesoscale-microscale interaction Probabilistic meteorological characterization for wind energy applications Air-sea interaction and marine boundary layer processes His recent publications show a strong trend toward uncertainty quantification in wind resource assessment, advanced modeling techniques for wind farm flow simulations, and the development of probabilistic approaches for turbine design. His work bridges fundamental atmospheric science with practical wind energy applications, particularly focusing on how to better model complex atmospheric phenomena for improved wind energy prediction and resource assessment. Dr. Kelly is actively involved in supervising PhD students and research projects. He serves as the Principal Investigator for the WAsP Scientific Development project and is a key participant in several major initiatives including AWETRAIN (Airborne Wind Energy Training) and IEA Wind Tasks 41 and 54. His editorial work includes serving as an editor for Theoretical and Applied Climatology and as a reviewer for multiple prestigious wind energy and renewable energy journals. His research group collaborates extensively with international partners across multiple countries, focusing on advancing wind energy technologies and their integration into sustainable energy systems. The team works closely with industry partners to translate research findings into practical applications for the wind energy sector.
Malcolm McGugan serves as Chief Development Engineer at DTU Wind Energy's Department of Wind and Energy Systems, specializing in Structural Health Monitoring (SHM) for composite structures with emphasis on wind turbine blade integrity. His role encompasses coordination of national and European mechanical testing programs, project management, and supervision of multiple PhD candidates within DTU's research ecosystem. His research expertise centers on acoustic emission and acoustoultrasonics for non-destructive evaluation of large-scale structures including wind turbine blades, ship hulls, and aerospace components. McGugan has pioneered methodologies for full-scale structural testing and damage detection in composite materials, with particular focus on delamination growth monitoring and fatigue crack propagation analysis in wind energy applications. His technical profile integrates polymer composite materials science with advanced sensor technologies and data analytics. Recent publication trends reveal a strategic shift toward AI-driven SHM solutions, combining computer vision with drone-based inspection systems and advanced signal processing techniques for operational wind turbine assessment. His work consistently bridges fundamental material science with industrial-scale validation through full-scale testing protocols. McGugan actively supervises doctoral research including Sheiati's AI-based blade identification project (2022-2025) and Fremmelev's damage simulation work (2019-2023), while managing the AINDT research initiative focused on AI-enhanced non-destructive testing for wind turbine maintenance optimization. His grant portfolio spans European collaborative projects and national Danish research funding mechanisms. As a core member of DTU's Wind Energy Materials and Components Division within the Structural Virtual Testing and Digitalization group, he contributes to developing digital twin frameworks for predictive maintenance of wind turbine components through virtual testing methodologies.
Nils Olsen is a Professor and Head of Geomagnetism and Geospace at the Department of Space Research and Technology , DTU Space (Danish National Space Center). His career spans multiple institutions including the Niels Bohr Institute at the University of Copenhagen and the Danish Center for Planetary Science . He holds a MSc (1985) and PhD (1991) in Physics from Göttingen University . Research interests center on Earth’s magnetic field modeling , core fluid dynamics , electromagnetic induction , and planetary magnetism (Mars, Moon). His work integrates Swarm satellite data , Ørsted missions , and CHAMP observations to study geomagnetic variations and external-internal field separation. Recent publications focus on tidal magnetic signals, ionospheric currents, and space weather applications. Supervision includes PhD projects on drone-borne magnetic surveying , machine learning for geophysical inversion , and UAV-based near-surface geophysics . Collaborations extend to ESA’s Swarm mission and CSES satellite initiatives , with over 100 peer-reviewed publications and leadership roles in international geophysical working groups.
Fanzhong Meng is a Senior Researcher at the Department of Wind and Energy Systems within Danish Technical University (DTU) . His research focuses on advanced wind turbine control systems, LiDAR-assisted control strategies, and floating offshore wind turbine dynamics. Key Collaborations : Active in projects like LICOREIM (LiDAR-assisted Control for Reliability Improvement) and PowerKey (Enhanced Wind Turbine Control). Research Themes : Specializes in rotor stability, fatigue load reduction, and power coefficient optimization for wind turbines. His work aligns with UN Sustainable Development Goals for renewable energy. Recent publications analyze LiDAR configurations, floating offshore control challenges, and retrofit strategies. He supervises master's projects and contributes to experimental studies on turbine dynamics.
Ang Li is a Researcher at the Department of Wind and Energy Systems , Technical University of Denmark (DTU) , specializing in wind turbine aerodynamic modeling. His work primarily focuses on Blade Element Momentum (BEM) theory , Lifting Line methods , and Vortex aerodynamics for rotor design optimization. Research interests include Aerodynamic modeling of wind turbine rotors Non-planar blade design Multi-fidelity aeroelastic simulations Viscous force analysis in BEM Curved tip shape optimization Recent publications highlight advancements in computationally efficient models for 22-megawatt turbines and corrections to BEM methods for spanwise flow effects. Collaborations include institutions like IOP Publishing and researchers such as Gaunaa, Pirrung, and Zahle.
Asger Bech Abrahamsen serves as a Senior Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in structural integrity, materials science, and superconducting applications for wind energy systems. His work spans experimental and computational research in offshore wind turbine components, recycling of composite materials, and high-temperature superconducting technologies. His research focuses on critical challenges in wind energy sustainability, including: Recycling value chains for decommissioned wind turbine blades Corrosion protection systems for offshore structures Pitch bearing reliability and damage accumulation Superconducting components for next-generation wind turbines Uncertainty quantification in floating wind turbine design His fingerprint analysis reveals expertise in Wind Turbine Engineering (100%), Superconducting Materials (87%), and Offshore Wind Turbines (30%). Abrahamsen actively supervises multiple PhD projects and leads the HTSComponentTestLab initiative for high-temperature superconducting component testing. His recent publications demonstrate a strong trend toward circular economy solutions for wind energy infrastructure and advanced modeling of thermal-mechanical systems. Professional engagements include organizing industry workshops like 'Metal Structures and Components of Wind Turbines' (2020) and 'Vind Energi Innovation kursus' (2019), alongside conference participation at events such as the World Congress of Structural and Multidisciplinary Optimization (2017). His media contributions address wind turbine recycling challenges and superconducting wind turbine development.
Ásta Hannesdóttir is a Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in wind energy systems with expertise in wind turbine aerodynamics, lidar remote sensing, and atmospheric turbulence modeling. She actively contributes to major research initiatives including the AIRE Horizon Europe project and TRASCAL, advancing wind farm design under challenging weather conditions. Her research focuses on leading-edge erosion impacts on turbine performance, lidar-based wind field reconstruction, and non-Gaussian turbulence modeling. She develops computational tools for wind resource assessment and integrates numerical simulations with field measurements to address aerodynamic degradation in offshore wind farms, significantly contributing to sustainable energy solutions aligned with UN SDGs. Recent publications reveal strong trends in lidar technology validation, erosion-aerodynamics interactions, and turbulence modeling innovations. Her work bridges atmospheric science and engineering to enhance wind turbine durability and energy yield under extreme weather, with growing emphasis on digital twin applications for wind farm optimization. Scientific recognition includes: Otto Mønsted travel grant (2019) for international conference participation in Massachusetts, USA Hannesdóttir supervises multiple graduate projects including PhD research on hub lidar flow-field estimation and master's theses on floating wind turbine control systems. She secures significant funding through collaborative grants: Active leadership in Horizon Europe's AIRE project (2023-2026) with €4.2M budget Principal investigator roles in TRASCAL (2023) and CCA LEE (2022) lidar/erosion projects Contributions to REQUIM rain erosion initiative (2022-2023) She operates within DTU's Wind Energy Systems division as part of cross-functional teams developing next-generation wind measurement technologies. Her work involves close collaboration with WindEurope, international research consortia, and industry partners to translate atmospheric physics into practical turbine design improvements.
Franck René Jacques Bertagnolio is a Senior Scientist at the Rotors Wind Turbine Design Division of the Technical University of Denmark (DTU Wind and Energy Systems). His work focuses on wind turbine aerodynamics, aeroacoustics, and noise reduction technologies, contributing to sustainable energy systems. Role: Researcher and supervisor in wind turbine noise and flow dynamics Projects: Involved in advanced aeroacoustic modeling, vortex-induced vibration studies, and low-noise wind farm control Research Interests: Bertagnolio specializes in trailing edge noise, airfoil design, hybrid computational aeroacoustic (CAA) methods, and high-fidelity turbulence modeling. His work bridges computational fluid dynamics (CFD) with practical wind turbine performance optimization. Scientific Contributions: Recent publications highlight his expertise in boundary element methods for noise prediction, vortex dynamics in wind turbine towers, and turbulence modeling for trailing edge noise reduction. These studies align with UN Sustainable Development Goals (SDGs) for clean energy and environmental protection. Supervision: He actively mentors PhD candidates like Pindi Nataraj and Ebstrup K., focusing on aerodynamic and aeroacoustic challenges in wind energy systems.
Guido Cantelmo is an Assistant Professor at the Technical University of Denmark (DTU) within the Department of Technology, Management and Economics, specifically in the Division of Transport's Section for Transport Systems Modelling. His research leverages big data analytics and machine learning to address complex transportation challenges, with expertise spanning traffic flow modeling, demand estimation, shared mobility systems, and urban network optimization. He maintains active collaboration with international cities including Copenhagen, Munich, and Tel Aviv-Yafo for empirical validation of his models. His research integrates computational techniques such as Graph Neural Networks, meta-learning, and physics-informed AI with transportation theory. Primary domains include: Dynamic traffic assignment using real-time data sources Machine learning for imbalanced mobility datasets Emission impact modeling of urban fleets Behavioral analysis of shared mobility adoption Large-scale simulation calibration frameworks Publication analysis (2022-2025) reveals dominant themes: data-driven demand estimation (37% of recent works), machine learning metamodeling (27%), shared mobility optimization (20%), and urban policy impact studies (16%). Methodological innovations include transfer learning for sparse data and multi-city validation approaches. No scientific awards or student mentoring relationships are documented in available sources. Similarly, no information exists regarding research grants, laboratory affiliations, or educational background.
Victor Puig I Laborda is a Postdoctoral Researcher at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU), affiliated with the PROSYS - Process and Systems Engineering Centre. His interdisciplinary work bridges chemical engineering, computational fluid dynamics, and machine learning to advance bioprocess modeling and industrial scale-up methodologies. His research centers on developing digital twin technologies through integration of systems biology models and computational fluid dynamics. Key interests include bioreactor compartment modeling using flow-informed clustering, unsupervised learning for operational regime identification, and multi-scale process optimization. This work addresses critical challenges in translating laboratory bioprocesses to industrial production while maintaining efficiency and product quality. Victor's 2025 publications highlight an emerging trend toward data-driven bioprocess engineering: his CFD compartment modeling paper introduces computational efficiency gains for reactor simulations, while his unsupervised learning research enables real-time process monitoring. Both contributions demonstrate practical applications for industrial biomanufacturing scale-up challenges. As part of PROSYS, Victor contributes to DTU's leading process systems engineering hub, which fosters industry-academia collaboration through projects in bioprocess digitalization, reactor design optimization, and advanced process control. The center provides state-of-the-art computational resources and experimental facilities supporting cutting-edge research in sustainable chemical production.
Georgios Kontogeorgis is a Professor at DTU Chemical Engineering , Department of Chemical and Biochemical Engineering, Danmarks Tekniske Universitet (DTU). His research focuses on advanced thermodynamic modeling and equations of state, with particular emphasis on ionic liquids , CO2 capture , and electrolyte solutions . Email: gk@kt.dtu.dk Affiliations: AT-CERE, KT-Konsortium Professor Kontogeorgis' work spans from fundamental thermodynamic theories (e.g., Debye-Hückel, SAFT) to industrial applications like energy-efficient chemical processes and solvent design . Recent studies include modeling water anomalies, ion association effects, and phase equilibria in complex solvent systems. His publications reveal trends in machine learning integration for thermodynamic predictions, CO2 mineralization studies, and multifunctional solvent design for separation processes. Collaborative projects with AT-CERE and KT-Konsortium focus on carbon capture and chemical engineering innovation . Labs/Teams: Affiliated with AT-CERE (Center for Energy Resources Engineering), KT-Konsortium (Chemical and Biotechnological Consortium)
