Marie Brøns is an Assistant Professor at the Department of Solid Mechanics, Danish Technical University (DTU), specializing in vibration analysis and structural dynamics. Her work focuses on bolted joints, frequency-based substructuring, and nonlinear system modeling. Academic Affiliation: DTU, College of Civil and Mechanical Engineering Key Research Areas: Bolted joint dynamics, Timoshenko beam theory, hybrid modeling frameworks Her recent publications highlight advancements in vibration-based bolt tension estimation (2025) and measurement correction frameworks for substructuring (2024). These works intersect mechanical engineering, applied mechanics, and computational modeling. Marie received the Young Researchers Award in 2021 for her contributions to structural health monitoring. She leads the DDSUB project (2021-2024) exploring dynamic disturbance substructuring and participated in a PhD project (2017-2020) focused on experimental vibration methods. Scientific Awards Young Researchers Award 2021
Anders Schmidt Kristensen is an Associate Professor at Aalborg University's Faculty of Engineering and Science, affiliated with the Esbjerg Energy Section and the Danish Centre for Risk and Safety Management. His work spans mechanical engineering, computational mechanics, and risk analysis, with a focus on structural design optimization and safety systems. Specializes in CAD-integrated structural modeling and finite element method (FEM) simulations Active in offshore energy and space debris mitigation research Key technologies: drag sail systems for satellite deorbiting, wind turbine power quality control, and tube-tubesheet joint modeling Recent research trends include: Structural health monitoring under thermal stress Optimized evacuation protocols for sports venues Advanced numerical modeling techniques for industrial components
Leon Derczynski is an Associate Professor of Computer Science at the IT University of Copenhagen , with a dual role as Principal Research Scientist/LLMSEC at NVIDIA . He leads the Strømberg NLP research group and coordinates NLP South at ITU, while also being affiliated with the Machine Learning group. Specializes in Natural Language Processing , Machine Learning , and LLM security Focus on Misinformation detection , Clinical text mining , and Danish language technology Research grants include Verif-AI (2.9M DKK), ClinRead (544K DKK), and LITHME (EU COST action, €11K). He has coordinated major projects like COMRADES and PHEME , and contributed to uComp and TrendMiner . Scientific recognition includes the University of Sheffield Exceptional Contribution Award (twice), WEBIST Best Student Paper award , and FP7 funding . His technical work includes the garak.ai LLM vulnerability scanner and generalised-brown clustering library. Actively supervises students and maintains numerous GitHub repositories (86 public projects) related to NLP, machine learning, and computational linguistics. He has delivered keynotes and guest lectures , including at Innopolis University (Russia) and PET (Danish Security and Intelligence Service).
Ulrik Dam Nielsen is an Associate Professor in the Section for Fluid Mechanics, Coastal and Maritime Engineering at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). He also held an external position as Associate Professor II at the Norwegian University of Science and Technology (NTNU) from 2014 to 2023, reflecting strong international collaboration. His work contributes to UN Sustainable Development Goals related to sustainable maritime operations and clean energy. His research focuses on naval architecture and ship motion dynamics , particularly in the context of sea state estimation , added resistance in waves , and real-time prediction of vessel responses . He integrates data analytics , estimation theory , and machine learning to develop methods for monitoring hydrodynamic performance and enhancing maritime safety and energy efficiency. A central theme of his work is using ships as mobile wave sensors—transforming operational vessels into 'sailing wave buoys' for environmental monitoring. His recent publications show a clear shift toward data-driven methodologies, especially machine learning applications in sea state estimation, added resistance modeling, and performance monitoring. These works span journals like Ship Technology Research and Journal of Offshore Mechanics and Arctic Engineering , and conferences such as IEEE MetroSea, highlighting interdisciplinary innovation at the intersection of classical marine engineering and modern AI. Best Paper Presented by a Young Researcher Award (First Classified), 2024 (jointly awarded) He actively supervises PhD students—such as R. E. G. Mounet, M. Mittendorf, J. P. Tomy, and A. Oikonomakis—on projects funded by DTU and collaborative initiatives. His leadership in projects like WEFOSWAB (Wave Estimation and Forecasting Using Ships as Buoys) and data-driven added resistance modeling underscores his role in advancing smart maritime technologies. He also contributes to open science through the public release of datasets such as NetSSE . He teaches core courses including Introduction to Ships and Floating Structures , Marine and Ocean Engineering , and Ship Operations , shaping the next generation of maritime engineers.
Ming Shen is an Associate Professor at the Department of Electronic Systems, part of The Technical Faculty of IT and Design at Aalborg University. His research focuses on antennas, millimeter-wave systems, and AI-driven RF sensors with applications in 5G/6G communications, biomedical engineering, and smart systems. His research interests span antenna design (including phased arrays, metamaterials, and compact structures), AI integration in electromagnetic systems, and medical sensor technologies. Recent projects include drone-based electromagnetic signature analysis, vibration energy harvesting for pacemakers, and smart healthcare systems for posture recognition and surgical site infection monitoring. Key projects include DRONES: Drone-Obtained Electromagnetic Signatures (2024–2028), Sensor Intelligence for Healthcare and Sports (2022–2027), and DeepBone (2021–2022), which explored deep learning for surgical infection detection. His work also bridges machine learning and electromagnetic design, with breakthroughs in surrogate modeling and automated antenna optimization. Ming Shen has supervised 6 PhD students and published over 160 peer-reviewed articles. Notable contributions include AI-assisted NLOS sensing, ultra-wideband antenna innovations, and medical applications such as electrical impedance-based bone healing assessment.
Cintia Organo Quintana is an Associate Professor in the Department of Biology at the University of Southern Denmark (SDU), affiliated with the SDU Climate Cluster. Her research focuses on benthic marine invertebrates and ecosystem responses to environmental stressors such as pollution, climate change, and habitat restoration. She investigates processes like bioturbation, biodiversity-ecosystem functioning relationships, and nutrient cycling in coastal systems. Key projects includelarge-scale sand-capping restoration in Danish fjords, climate mitigation via blue carbon ecosystems, and coastal rewilding strategies. She leads the SCC Elite Centre for aquatic nature-based solutions and collaborates on EU-funded initiatives like ClimateBlue and Blue4All. Recent publications emphasize sand capping’s biogeochemical impacts, citizen perceptions of climate vs. biodiversity priorities, and greenhouse gas dynamics in coastal environments. She actively engages in public communication through media contributions addressing coastal management and climate adaptation challenges.
Anne Kær Gejl is an Associate Professor at the Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, where she conducts research in the Research Unit of Exercise Epidemiology. Her work bridges public health, exercise science, and educational psychology, with a strong focus on physical activity's role in cognitive and mental health development among children and adolescents. Her research interests center on physical activity , cognitive function (especially inhibitory control and executive function), brain-derived neurotrophic factor (BDNF) , and child development . She investigates how structured physical activity and screen-free interventions can enhance pre-reading, spelling, and mental health outcomes in young populations. Her work often employs randomized controlled trials , systematic reviews , and population-based studies , reflecting a rigorous methodological approach. Recent publications highlight trends in embodied learning , digital screen use , and feasibility of behavioral interventions . Her research consistently emphasizes the integration of physical activity into educational settings to support both academic and psychological well-being. Scientific Awards: None listed in the provided text. Anne Kær Gejl actively mentors students, including PhD candidates such as Anne Sofie Bøgh Malling and Lars Damsgaard. She has been involved in significant research grants related to physical activity interventions and educational outcomes, though specific grant names are not detailed. Her collaborative network includes researchers from public health, sports science, and education disciplines. She is part of the Research Unit of Exercise Epidemiology, contributing to team-based studies on youth health, physical activity monitoring, and cognitive development. Her lab engages in both experimental and observational research, often in school and community settings.
Hans Martin Kjer is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he is affiliated with the UltraSound and Biomechanics group within the Visual Computing Center and the Center for Fast Ultrasound Imaging. His research bridges engineering and medical imaging, with a strong emphasis on developing and validating advanced ultrasound techniques for biomedical applications. Research Interests: His work focuses on super-resolution ultrasound imaging, microvascular analysis, 3D reconstruction of biological structures, and image registration. He applies computational methods to improve the resolution and accuracy of ultrasound, particularly in renal and lymph node vasculature imaging. His research contributes to the UN Sustainable Development Goals in health and well-being through innovative diagnostic tools. Publication Trends: Over the past several years, Kjer has consistently published in high-impact journals and conferences in biomedical engineering and imaging. His recent work emphasizes the validation of super-resolution ultrasound against micro-CT, realistic 3D blood flow simulation, and the application of AI in enhancing imaging resolution. These studies reflect a strong trend toward quantitative, reproducible, and clinically relevant imaging solutions. Scientific Contributions: While no specific awards are listed, his leadership in major research projects and frequent collaborations with leading experts in ultrasound (e.g., Jørgen Arendt Jensen) underscore his significant role in the field. Advising and Funding: Kjer serves as a supervisor and principal investigator in several funded research initiatives, including AI for Extreme Super-Resolution CT , 3DIM: 3D Imaging Center , and QIM: Center for Quantification of Imaging Data from Max IV . He mentors PhD students and collaborates across disciplines, contributing to both biomedical and materials science imaging projects. Laboratories and Teams: He is an integral member of the Center for Fast Ultrasound Imaging and the Visual Computing Center at DTU. These teams focus on cutting-edge ultrasound technologies, image processing algorithms, and multimodal imaging integration, positioning Kjer at the forefront of computational biomedical imaging in Denmark.
Per Goltermann is a Professor and Head of Study Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), where he leads the Digital Building Technologies research group. His work focuses on sustainable and innovative construction technologies, including concrete structures, E-learning, and material lifecycle design. PhD in Civil Engineering, DTU (1982–1985) MSc in Civil Engineering, DTU (1976–1981) His research interests include Integrated Structures and Materials Design , with emphasis on reinforced concrete, ZeroWaste strategies for material upgrading, and Superlight Concrete Structures for sustainable design. His international expertise spans concrete deterioration, monitoring, and structural health assessment. The research footprint highlights strong engagement in civil engineering, fiber-reinforced polymers, and sustainable materials. Recent publications (2024–2025) reflect a focus on sustainable construction materials (e.g., unfired clay bricks, rammed earth), advanced bridge testing (proof loading, inverted T-sections), and CFRP strengthening techniques. These works emphasize durability, sustainability, and structural performance, aligning with UN Sustainable Development Goals. His scientific awards include: Annual DTU Award for developing Teaching and Learning (2017) DTU Award for Development of Teaching and Learning 2017 Teacher of the year at DTU (2013) Per Goltermann has supervised multiple PhD students and led significant research projects, including Advanced engineering tool for lightweight composite 3D print of concrete design formwork and Monitoring thresholds in full-scale bridge testing . He has been a main supervisor in projects funded by public and industrial sources, focusing on structural reliability, bridge reclassification, and shear behavior of concrete members. His activities include guest lectures and invited talks on sustainable building materials and smart structural inspection. He is actively involved in research networks and collaborations, particularly in Denmark and internationally, with a strong presence in bridge safety, sustainable materials, and digital construction technologies.
Jon Juel Thomsen is an Associate Professor at the Technical University of Denmark (DTU), Department of Civil and Mechanical Engineering, specializing in Solid Mechanics. His research focuses on theoretical and experimental analysis of mechanical vibrations, particularly nonlinear phenomena and high-frequency effects. He leads projects on fast vibrations and dry friction, short-term damping estimation for wind turbines, and vibration-based bolt tension estimation. He advises PhD students including J. D. Richardt, K. L. Ebbehøj, and M. T. Steffensen. His work integrates experimental modal analysis, structural dynamics, and nonlinear systems. Notable contributions include methods for damping estimation in nonstationary systems, uncertainty quantification in modal parameters, and vibration-based assessment of bolted joints. Projects like the Vibrations for Estimating Bolted Joint Integrity (VEBJI) highlight his applied engineering focus. His research spans theoretical developments and industrial applications in mechanical systems and renewable energy. Key collaborations include work on piezoelectric excitation for bolt tension measurement and high-frequency excitation effects in metamaterials. His lab develops novel techniques for structural health monitoring and vibration control, leveraging both experimental and computational methods.
Paul Kempen is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Health Technology and the National Centre for Nano Fabrication and Characterization. His research focuses on nanotechnology applications in drug delivery, biomedical engineering, and materials science, with a particular emphasis on liposomes, gold nanoparticles, and nanozymes. He supervises multiple PhD students and has contributed over 60 peer-reviewed publications. His research interests span the development of nanocarriers for targeted drug delivery, characterization of biomaterials, and the design of sustainable nanotechnologies. Collaborations include studies on phycosphere microbiomes, ammonia electrosynthesis, and MRI tattoo interactions. He leads projects such as 'R2R ProBac' and 'Nanofluidic Electron Diffraction,' exploring biofilm formation and advanced microscopy techniques. Key achievements include the creation of cost-effective wound dressings using nanogels and advancements in mRNA lipid nanoparticle delivery via gastrointestinal devices. His work aligns with UN Sustainable Development Goals, particularly in affordable and clean energy and good health and well-being. Paul advises PhD students in nanofluidics, polymer surface engineering, and electron microscopy applications. His lab, Nanolab , specializes in nanocharacterization and fabrication. Future directions include expanding nanomedicine applications and sustainable nanomaterials.
Neeti Kalyani is a postdoctoral researcher at the Department of Biotechnology and Biomedicine, Technical University of Denmark. Her work focuses on digital microfluidics, biosensor development, and nanostructured materials for diagnostics. She actively contributes to advancing antifouling surfaces, point-of-care testing, and optical sensing technologies. Research Areas: Digital microfluidics, surface science, food safety, spinal cord injury diagnostics, environmental pollutant detection. Projects: Developing a handheld sensor for acute circulatory failure diagnosis (2024–2027). Supervision: Mentors PhD students and supervised multiple projects on microneedle biosensors, paper-based sensors, and resistive switching RAM. Her research bridges Nanotechnology , Biomedical Engineering , and Environmental Health , with trends in articles emphasizing point-of-care devices and antifouling innovations . Scientific Recognition Distinction in Doctoral Research (2022) She contributes to UN Sustainable Development Goals 3 (Health and Well-being) and 9 (Industry Innovation), with collaborations spanning Denmark and international institutions.
Adelina Rogowska-Wrzesinska is an Associate Professor at the Department of Biochemistry and Molecular Biology, University of Southern Denmark. Specializing in Biomedical Mass Spectrometry and Systems Biology , her research spans proteomics, oxidative stress, protein oxidation, and 3D cell culture models. Affiliation : Department of Biochemistry and Molecular Biology, University of Southern Denmark Academic Role : Teaching and research leadership Her research interests focus on: Redox biology and protein oxidative modifications 3D spheroid models for disease and toxicity studies Mass spectrometry-based proteomics and lipidomics Oxidative stress in cellular senescence and disease Plant stress responses and proteomics Scientific Trends : Recent publications highlight advancements in 3D culture modeling (NAFLD, genotoxicity), redox proteomics (glutathionylation, disulfide bonds), and multi-omics integration (chromatin proteomics, lipidome mapping). Teaching and Supervision : She has supervised multiple PhD students (e.g., Christina Erika Hagensen, Helle Frandsen) and taught courses like Basic Biochemistry (BMB530) and Fundamental Molecular Biology (BMB504) .
Martin Bach Jensen is a Professor at the Center for General Medicine within Aalborg University's Faculty of Health Sciences. With a parallel clinical and academic career spanning decades, his work bridges medical practice and research innovation. Current affiliations: Aalborg University, Faculty of Health Sciences, Center for General Medicine Expertise: Musculoskeletal disorders, Artificial Intelligence in healthcare, Ultrasound applications Research Focus : • Technology integration in general practice (AI, ultrasound) • Musculoskeletal pain management in primary care • Clinical decision support systems development • Medical education innovation Recent Work Trends : His 15 most recent publications reveal deep engagement with AI applications in diabetic retinopathy screening Ultrasound training programs for GPs Adolescent knee pain management tools Registry research methodology Academic Leadership : Active in Principal investigator roles in AI and ultrasound projects Co-investigator in musculoskeletal trials Medical curriculum development Teaching & Supervision : Continuous medical educator since medical school days, mentoring Medical students Physiotherapy candidates General practitioners PhD supervisees With a focus on technology-enhanced clinical education and course development.
Vinay Chakravarthi Gogineni is an Assistant Professor at The Maersk Mc-Kinney Moller Institute , University of Southern Denmark (SDU), specializing in SDU Applied AI and Data Science . His research integrates advanced AI techniques into healthcare, industrial IoT, and fusion energy systems, with a strong focus on federated learning, privacy-preserving AI, and ethical machine learning practices. Education: Ph.D. in Distributed Machine Learning, Indian Institute of Technology Kharagpur (Aug 2019) Research Interests: Dr. Gogineni's work spans Deep Learning , Federated Learning , and Graph Data Analysis . He develops personalized AI models for healthcare applications, including cervical cancer screening, colorectal cancer detection, and dementia prediction. His innovations in Machine Unlearning ensure compliance with GDPR and the EU AI Act, while his work on Physics-Informed Neural Networks enhances predictive accuracy in fusion energy systems. Key areas include self-supervised learning, continual learning, and fairness-aware AI. Scientific Awards: HC Ørsted Research Talent Award (2024, Denmark) ERCIM Alain Bensoussan Fellowship (2019) Best Paper Award , APSIPA ASC-2021, Tokyo Professional Roles: IEEE Senior Member and editorial board member of IEEE Sensors Journal . He teaches courses on AI for Healthcare Data and Calculus and Linear Algebra , fostering interdisciplinary education in applied AI.
