Charlotte Fooks is a Research Assistant at the Centre for Industrial Electronics , Institute of Mechanical and Electrical Engineering, University of Southern Denmark. Her work focuses on biosignal analysis, vibroacoustic stimulation, and stress assessment. Research Output: 2 peer-reviewed publications (2024) investigating vibroacoustic therapy's effects on stress metrics using speech and physiological signals Key Tools: Electrocardiogram (ECG), electroencephalogram (EEG), Perceived Stress Scale, parasympathetic activity measurements Her research combines biomedical signal processing with human stress assessment to evaluate non-invasive wellness interventions. Recent studies analyze vibroacoustic sound massage through speech biosignals and quantify its impact on physiological stress markers. Collaborative work with Dr. Niebuhr demonstrates measurable improvements in stress parameters through vibroacoustic interventions, contributing to emerging physiological monitoring and stress management technologies.
Jamie Yam Auxillos is an Assistant Professor at the University of Copenhagen, affiliated with both the Biotech Research & Innovation Centre (BRIC) and the Department of Biology, where she leads research in Computational and RNA Biology. Her work bridges molecular biology, synthetic biology, and cutting-edge sequencing technologies. Education: PhD in Cell and Molecular Biology (2020), Centre for Systems and Synthetic Biology, University of Edinburgh MSc in Systems and Synthetic Biology (2015), University of Edinburgh BSc Honours in Biomedical Sciences with Medical Microbiology (2014), Newcastle University Dr. Auxillos' research focuses on Molecular Biology, Synthetic Biology, and Biotechnology , with particular expertise in Sequencing Methods Development, Spatial Transcriptomics, and Nanopore long read sequencing. Her work combines computational approaches with experimental techniques to develop new methods for RNA analysis and to understand complex biological systems, particularly in cancer biology and synthetic yeast engineering. Her recent publications reveal a strong trend toward developing innovative sequencing methodologies and applying them to cancer research, with significant contributions to spatial transcriptomics and tumor microenvironment analysis. She has also made important contributions to synthetic biology tools, particularly for yeast engineering and CRISPR-based technologies. Dr. Auxillos has established collaborative networks across multiple countries and institutions, with significant research output including journal articles, reviews, and book chapters that have garnered substantial attention across academic and social media platforms. Her research has been shared widely, with publications posted by numerous X (Twitter) users, featured on Facebook pages, discussed on Reddit, referenced in policy sources and patents, and read by hundreds of researchers on Mendeley.
Thomas Kronborg Larsen is an Associate Professor and Head of Research Group at the Department of Health Science and Technology, Aalborg University (Faculty of Medicine). His research focuses on diabetes management, telemedicine, and AI-driven healthcare solutions. He leads the ADAPT-T2D project (2019–2025), exploring cloud-based personalized treatments for Type 2 Diabetes. Key interests include insulin adherence, remote patient monitoring, and machine learning applications in clinical settings. Education: Not explicitly listed in the text. Research interests span AI in nursing, glucose monitoring accuracy, and telemonitoring systems. Recent work emphasizes data-driven methodologies for insulin therapy adherence and missing data imputation strategies. Collaborations involve multidisciplinary teams addressing diabetes challenges through innovative technologies. His lab, Medical Informatics and Image Analysis, contributes to AI for the People initiatives, aiming to improve patient care through transparent AI systems. Media highlights include articles on insulin adherence and transparent AI for diabetics (2021–2022).
Gert Frølund Pedersen is a Professor at the Department of Electronic Systems , Aalborg University , within the Technical Faculty of IT and Design . His research focuses on antennas, propagation, and millimeter-wave systems. He leads projects like DRONES (30 million DKK from Innovationsfonden) for drone-based electromagnetic signature analysis and EcoSurf6G for energy-efficient reconfigurable surfaces in 6G networks. With over 758 research outputs and 21 PhD students supervised, he contributes extensively to wireless communication advancements. Antenna Engineering Millimeter-Wave Systems Reconfigurable Intelligent Surfaces Deep Learning in Antenna Design His recent work emphasizes millimeter-wave IoT applications , UWB propagation channels , and 5G/6G antenna arrays . Publications highlight innovations in transmitarray antennas , liquid crystal polarization control , and metasurface design using AI. His research spans from fundamental electromagnetic safety to cutting-edge wireless infrastructure. Notable awards include Best Reading Paper of the Issue (IEEE Transactions on Microwave Theory and Techniques, 2020), ESI Highly Cited Paper (2019), and Ridder af Dannebrog (2021). He frequently engages with media to address public concerns about mobilstråling (mobile radiation) and its safety.
Kaare Mikkelsen is an Associate Professor in the Department of Electrical and Computer Engineering at the Faculty of Technical Sciences, Aarhus University, specializing in biomedical engineering with a focus on ear-EEG technology for sleep and auditory neuroscience applications. His research pioneers non-invasive monitoring systems using ear-centered EEG sensors, developing machine learning frameworks for automatic sleep staging and auditory attention decoding. Key contributions include personalized sleep scoring algorithms that adapt to individual physiological variations and deep learning models for decoding brain responses to natural speech, enabling applications in hearing assistance and brain-computer interfaces. Recent publications (2022-2025) demonstrate a cohesive research trajectory centered on overcoming real-world challenges in wearable EEG: improving long-term reliability through electrode configuration studies, developing standardized data pipelines, and validating ear-EEG against clinical polysomnography. His work bridges engineering innovation with clinical sleep medicine, emphasizing at-home deployment and user-specific adaptation. Dr. Mikkelsen leads significant research projects including: Event based attention detection (2021-2024) Ear-EEG sleep monitoring (2015-present) His work receives funding from Danish research councils and involves collaborations with clinical partners for validation studies in naturalistic settings. As part of Aarhus University's Biomedical Engineering group, he utilizes advanced laboratories for sensor development and signal processing, contributing to the department's strategic focus on healthcare technology innovation.
Celia Kjærby is an Associate Professor at the Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, where she also leads the Division of Sleep-Arousal State Transitions at the Center for Translational Neuromedicine. Her research focuses on understanding sleep micro-structures and their role in cognitive performance and brain health. Education: PhD, Graduate School of Health and Medical Sciences, University of Copenhagen (2012) M.Sc. (human biology), Faculty of Health and Medical Sciences, University of Copenhagen (2007) Bachelor of Science (biology), Faculty of Sciences, University of Copenhagen (2004) Kjærby's research investigates how sleep-arousal transitions impact restorative sleep processes related to memory consolidation and waste clearance. Her work is particularly relevant for understanding neurodegenerative and neuropsychiatric disorders where sleep disturbances play a significant role. She examines the complex micro-structures of sleep and how frequent short arousals contribute to normal sleep function. Her recent publications (2024-2025) reveal a strong focus on the glymphatic system, cerebral blood flow regulation during sleep, and the relationship between sleep disturbances and neurodegenerative conditions like Alzheimer's disease. Her research integrates advanced techniques including CRISPR/Cas9, fluorescent imaging, and machine learning approaches to analyze sleep patterns. Scientific Recognition: Member of Lundbeck Foundation Investigator Network (LFIN) (2022) Cover feature in Nature Neuroscience (August 2022) Kjærby has secured significant research funding including the Lundbeck Foundation Fellow award (2023), Lundbeck Foundation Seed Grant (2023), and an Inge Lehmann independent grant from the Independent Research Fund Denmark (2022). She serves on the editorial board of Frontiers in Neural Circuits and reviews for prestigious journals including Nature and Neuron. She is also active in scientific outreach, regularly participating in public lectures and media interviews about sleep science. She leads the research group focused on Sleep-Arousal State Transitions and has been instrumental in organizing neuroscience events including the monthly 'DIM the Brain' forum for students and postdocs at the University of Copenhagen since 2016.
Marco Pizzolato is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing with a focus on Magnetic Resonance Imaging (MRI), particularly diffusion MRI and biophysical modeling. He is also affiliated with the inter-departmental Microstructure & Plasticity (MAP) research group and has held visiting positions at the University of Verona, EPFL, and DRCMR. His educational background includes a PhD in Signal and Image Processing from INRIA Sophia Antipolis, a Master’s in Bioengineering from the University of Padua, and a Bachelor’s in Biomedical Engineering from the same institution. He previously served as an Assistant Professor at DTU and was a postdoctoral researcher under the Marie Curie COFUND Eurotech programme. Dr. Pizzolato's research centers on image and signal denoising, inverse problems, optimization, diffusion MRI, tractography, and Monte Carlo simulations. He actively contributes to the development of microstructural models for brain imaging, with applications in neurodegenerative diseases and brain connectivity. His work aligns with UN Sustainable Development Goals, particularly in advancing education and health through imaging technology. The recent publications reflect a strong trend in advancing diffusion MRI techniques, including ACID imaging, microscopic propagator modeling, myelin integrity mapping, and multi-scale white matter organization. These works emphasize biophysical accuracy, model validation, and integration across imaging modalities and species. Magna Cum Laude , ISMRM 2020 Magna Cum Laude , ISMRM 2022 First Place , Macaque Validation Challenge at ISBI 2018 First Place (Overall and HCP) , IronTrack Challenge 2019 (MICCAI) MICCAI Student Travel Award 2015 He has supervised PhD students such as Thøgersen, T. L. and Corral Bolaños, M. in projects related to microstructure MR imaging and myelin mapping. He has also been involved in significant grants and collaborative projects, including the Multimodal Microstructure-Informed Connectivity (MMINCARAV) initiative between Inria and EPFL, and the Sinergia consortium for Brain Communication Pathways . He co-organized multiple international events, including the MICCAI CDMRI workshops and challenges (2019–2021), and the ESMRMB Leaps in Microstructure Imaging workshop (2024). Dr. Pizzolato is an active member of the scientific community, serving as an editor for MICCAI workshop proceedings, a reviewer for major journals and conferences, and an invited speaker at ISMRM 2025. He leads and participates in several ongoing research projects at DTU focused on quantitative imaging, myelin mapping, and MRI-based connectivity, demonstrating sustained research leadership and external funding success.
John Paulin Hansen is a Professor at the Technical University of Denmark (DTU), affiliated with the Department of Technology, Management and Economics under the Technology and Business Studies school. His research focuses on human factors, human-computer interaction, and assistive technologies, particularly in gaze interaction and rehabilitation robotics. He holds a Ph.D. from Aarhus University (1992) and has led research groups at institutions like Risø National Laboratory and the IT University of Copenhagen. His work emphasizes improving quality of life for individuals with motor disabilities through innovations like The Eye Tribe and GazeIT lab initiatives. Research Interests include: Eye-tracking technology and gaze interaction systems Exoskeletons and AR interfaces for stroke rehabilitation Human digital twins in healthcare Telepresence robotics accessibility Brain-computer interfaces (BCI) Key Achievements: Founded EU’s COGAIN network, co-created The Eye Tribe startup (acquired by Facebook/Oculus), and leads the GazeIT lab supported by the Bevica Foundation. His projects address sustainable development goals through inclusive technology solutions. Awards: Vanførefondens Forskerpris 2018 Multiple Best Paper Awards (2019–2022) Reviewers' Favourite Best Paper Award at DESIGN2022 Advising & Grants: Mentor to startups like The Eye Tribe and Orbital (acquired by GN Audio). Current projects include EU Horizon 2020 Rehyb initiative for AR exoskeleton interfaces and Human Digital Twin applications in rehabilitation. Labs/Teams: GazeIT lab pioneers assistive tech innovations, collaborating with LEGO and Serious Games Interactive. Active in developing inclusive design pedagogy and digital twin methodologies for healthcare.
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.
Mohammad Naser Sabet Jahromi is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University, Denmark. He is affiliated with the Visual Analysis and Perception Centre for AI Ethics, Law and Policy. His research focuses on explainable AI (XAI), biometrics, machine learning, and ethical AI applications in legal and medical domains. He actively participates in interdisciplinary projects like REPAI: Responsible AI for Value Creation (2023-2027), which explores AI ethics, computational discourse analysis, and value-driven AI systems. His educational background is not explicitly detailed in the provided text, but his research trajectory indicates strong expertise in computer science and AI systems. Key research interests include interpretable machine learning models, privacy-preserving biometric systems, and AI applications in asylum adjudication and educational assessment. Recent work emphasizes developing XAI frameworks like SIDU-TXT for NLP, verifying machine unlearning mechanisms, and automating large-classroom assessments. His projects bridge technical AI advancements with societal implications through collaborations with legal and ethical scholars. Notable contributions include datasets evaluating XAI methods in medicine and methodologies for transparent AI decision-making. He has participated in conferences such as ICPR 2024 and JURISIN 2023, showcasing interdisciplinary research impact.
Dan Stieper Karbing is an Associate Professor in the Department of Health Science and Technology at the Faculty of Medicine, Aalborg University, Denmark. His research focuses on respiratory and critical care, with a strong emphasis on AI-driven decision support systems for mechanical ventilation. Ph.D. in Biomedical Science and Engineering (2009) M.Sc. in Biomedical Engineering, specializing in Biomedical Signals and Systems (2006) His research interests include biomedical engineering, mechanical ventilation, gas exchange modeling, decision support systems, AI in healthcare, and cardiorespiratory monitoring . He applies engineering principles to solve clinical challenges in intensive care, particularly in optimizing ventilator therapy and patient monitoring. The recent trend in his publications centers on AI-enabled clinical decision tools, non-invasive monitoring using wearable sensors, respiratory rate estimation, cardiorespiratory fitness assessment, and rehabilitation in critically ill patients . His work bridges engineering and medicine, aiming to improve patient outcomes through data-driven, personalized care. He is actively involved in research projects such as The Beacon Caresystem and CoRESCUE AAU Pandemic Ventilator, and his work has been featured in media outlets discussing AI in hospitals, customized ventilator treatment, and pandemic preparedness. He supervises PhD students and collaborates internationally on clinical and engineering research. He also serves on the board of Aw Technologies ApS, linking academia with industry innovation.
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.
Barbara Guerra is an Associate Professor in the Department of Biochemistry and Molecular Biology at the University of Southern Denmark, Faculty of Science. She leads the Barbara Guerra Lab, which is part of the Translational Biology research section, focusing on the role of protein kinases in human disease, particularly cancer. She also serves as Head of the PhD School at the Faculty of Science since 2020, demonstrating strong leadership in academic training and research supervision. Her research expertise lies in protein kinase CK2, a key regulator of cell survival, growth, and differentiation. Her laboratory investigates CK2-mediated signaling pathways in cancer, DNA damage response, lipid metabolism, and cell cycle regulation. She has contributed extensively to understanding CK2's role in oncogenesis and its potential as a therapeutic target. Her recent publications reveal a consistent focus on CK2 in cancer metabolism, hypoxia signaling (e.g., HIF-1α), autophagy, and the development of kinase inhibitors. Themes include pharmacological targeting of CK2, regulation of metabolic enzymes like SCD-1, and modulation of tumor suppressors such as p27KIP1. She frequently collaborates on interdisciplinary studies involving drug delivery systems and natural product-based inhibitors. Barbara Guerra has received recognition for her teaching excellence, including a Faculty of Natural Science teaching prize in 2006. She serves on the editorial boards of Oncology Reports and Pharmaceuticals , contributing to scientific peer review and dissemination. She has supervised over 100 undergraduate, Master’s, and PhD students, as well as six postdoctoral researchers, indicating a strong commitment to mentoring the next generation of scientists. Her research is supported by numerous projects and she plays a central role in PhD education at the university level. Her lab is actively involved in translational research, bridging basic molecular mechanisms with potential clinical applications in oncology and metabolic disorders.
Frank Kjeldsen is a Professor and group leader in the Protein Research group at the Department of Biochemistry and Molecular Biology , University of Southern Denmark . His research focuses on proteomics, mass spectrometry, and the biological effects of nanoparticles, with a strong emphasis on method development in negative ion mode and ultrafast proteomic platforms. His research interests span: Proteomics and systems biology Nanoparticle-biological system interactions Development of novel mass spectrometry and chemical biology methods Fundamental gas-phase peptide chemistry Metabolomics and multi-omics integration Recent publications (2023–2025) highlight trends in ultrafast proteomics , multi-omics for environmental and biomedical applications, nanoplastic toxicity , and neuroprotection . His work frequently involves advanced LC-MS/MS techniques, ion mobility, and software development for data analysis. Scientific recognition includes: 2 prizes (as noted in his CV profile) He actively supervises research and collaborates on multiple interdisciplinary projects. His lab, the Frank Kjeldsen Lab , is part of the Biomedical Mass Spectrometry research section. He has contributed to numerous grants and collaborative research efforts in toxicology, cancer, and environmental science.
Hans Magnus Henrik Lundell is an Associate Professor at the Department of Health Technology, Technical University of Denmark , specializing in Magnetic Resonance research. His work bridges biomedical engineering and neuroscience through advanced imaging techniques. Active in diffusion MRI and neurodegeneration research Current supervisor of two PhD students in multi-modal imaging projects Contributor to 11 publications with international collaborations Focus on tumor microstructure and cerebellar imaging applications His research on Diffusion-weighted MRS and time-dependent diffusion imaging has applications in glioblastoma diagnostics and neurodegenerative disease studies. Recent work explores clinical MRI-Linac integration for radiotherapy monitoring and extracellular diffusion dynamics in human tissue.
