جستجوی استاد راهنمای دانشگاهی

Luis Emilio Bruniمشاهده پروفایل

دانشیار

• Narrative Cognition
• Extended Reality
• Cognitive Processes
• +۶ مورد دیگر

Luis Emilio Bruni is an Associate Professor at Aalborg University’s Department of Architecture, Design and Media Technology, within The Technical Faculty of IT and Design. He leads the Media Cognition and Interactive Systems (MeCIS) research group and coordinates the Master of Science in Medialogy. Bruni is also the founder and director of the Augmented Cognition Lab, focusing on perception, cognition, and immersive technologies. His academic roles include PI on multiple interdisciplinary projects and board memberships in international associations like the Nordic Association for Semiotic Studies (2011–2017) and the International Society for Biosemiotic Studies (founding member, 2005). Academically, Bruni holds a Ph.D. in Molecular Biology and Theory of Science (University of Copenhagen), M.Sc. in International and Global Relations (Universidad Central de Venezuela), and B.Sc. in Environmental Engineering (Pennsylvania State University). His research spans narrative cognition, extended reality, biosemiotics, and the interplay between technology, cognition, and culture. He has conducted projects on neurocinematic analysis, interactive storytelling, and the psychological impact of digital media. Key research contributions include studies on EEG responses to branded advertising, functional connectivity in psychiatric disorders, and the role of narrative in immersive technologies. Bruni’s work bridges cognitive science, computer science, and semiotics, with applications in healthcare (e.g., pediatric counseling tools) and cultural engagement (e.g., citizen curation systems). Over 80+ publications and active participation in conferences and media discussions highlight his interdisciplinary impact.

Farshad Moradiمشاهده پروفایل

استاد

• Neuromorphic Computing
• Spintronics
• Biomedical Engineering
• +۵ مورد دیگر

Farshad Moradi is a Professor at the Department of Electrical and Computer Engineering at Aarhus University, specializing in neuromorphic engineering, spintronics, and biomedical device design. His work focuses on integrating advanced materials and circuits for applications in neural interfaces, energy-efficient computing, and wireless biomedical systems. Research Interests include: Spintronic-based neuromorphic computing architectures Ultra-low power analog/mixed-signal integrated circuits Ultrasonically powered implantable medical devices Neural signal processing and seizure detection systems Wireless energy transfer and structural health monitoring Key Projects (2016-2026): SPICE: Spintronic-Photonic Integrated Circuit Platform PHOTON-NeuroCom: Photonic-assisted Neuromorphic Computing Neuro-Sense: Flexible bioinspired neuroprostheses CorroSense: Self-powered corrosion monitoring HERMES: Hybrid Enhanced Regenerative Medicine Systems Recent innovations include: Ultrasonically powered optogenetic implants Low-power neural amplifiers for deep-brain interfaces Spin-torque nano-oscillator-based neuromorphic hardware Energy harvesting systems for structural monitoring

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +۷ مورد دیگر

Luka Radic is a Researcher in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His work bridges theoretical and applied research in machine learning, with a focus on quantum machine learning , large language models , and fairness in AI systems.

Mostafa Mohammadiمشاهده پروفایل

استادیار

• Neurorehabilitation Robotics
• Human-Computer Interaction
• Telerehabilitation Technologies
• +۵ مورد دیگر

Mostafa Mohammadi is an Assistant Professor at the Department of Health Science and Technology, Aalborg University, affiliated with the Faculty of Medicine and Center for Rehabilitation Robotics. His research focuses on neurorehabilitation robotics, human-computer interaction, and telerehabilitation technologies for individuals with disabilities. Ph.D. in Biomedical Engineering (Aalborg University, 2018-2022) M.Sc. in Biomedical Engineering (Polytechnic University of Milan, 2015-2017) B.Sc. in Mechanical Engineering (Sharif University of Technology, 2011-2015) His work spans exoskeleton design, assistive robotics, and innovative interfaces like tongue-computer interfacing. Recent projects include the eMotivo digital health solution funded by Innovation Fund Denmark and intelligent tendon-driven exoskeletons for severe disabilities. Research outputs (33 total) emphasize adaptive robotics, motor impairment solutions, and wearable technologies. Collaborations span robotics, biomedical engineering, and clinical disciplines. Teaching includes courses in rehabilitation robotics, human-computer interaction, and digital systems for biomedical engineering. Scientific activities align with UN Sustainable Development Goals for quality education and reduced inequalities. Notable contributions include advancements in myoelectric interfaces and neurorehabilitation technologies.

Tuukka Ruotsaloمشاهده پروفایل

دانشیار

• Brain-Computer Interfaces
• Human-Information Interaction
• Recommender Systems
• +۴ مورد دیگر

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

• Machine Learning
• Artificial Intelligence
• Quantum Computing
• +۵ مورد دیگر

Sophia Natasha Wilson is a Research Fellow in the Department of Computer Science (DIKU) at the University of Copenhagen, specializing in machine learning applications across interdisciplinary domains. She is affiliated with the SCIENCE AI Centre and holds a cross-departmental position at the Niels Bohr Institute . Her research bridges theoretical machine learning with practical implementations in healthcare, quantum computing, and environmental sustainability. University of Copenhagen Department of Computer Science (DIKU) Niels Bohr Institute SCIENCE AI Centre Her research focuses include: Quantum-enhanced machine learning algorithms Explainable AI for healthcare applications Environmental sustainability in computing Emotion-aware language models Quantum computing hardware optimization Public health risk modeling Her recent publications demonstrate cross-disciplinary work in quantum machine learning (hybrid optical processors, qubit stabilization), health informatics (hypothyroidism analysis, nursing values evaluation), and ethical AI (sustainable AI, fairness in recommender systems). Technical work also appears in non-Euclidean generative models and real-time adaptive systems . Current projects include quantum dot array simulation (QDarts platform) and federated learning for personalized medicine . She contributes to the TreeSense center for remote sensing of global tree resources and works on climate-aware AI frameworks.

Henrik Jeldtoft Jensenمشاهده پروفایل

استاد

• Complexity Science
• Statistical Mechanics
• Mathematical Physics
• +۷ مورد دیگر

Henrik Jeldtoft Jensen is a Professor of Mathematical Physics and leads the Centre for Complexity Science at Imperial College London. His work spans multiple disciplines, focusing on the statistical mechanics of complex systems, with applications in physics, biology, neuroscience, and finance. Professor, Mathematical Physics Leader, Centre for Complexity Science Institution: Imperial College London His research interests lie at the intersection of theoretical physics and complex systems. He is best known for developing the Tangled Nature Model of evolving ecosystems, which has been extended into financial modeling through the Tangled Finance approach. His work in brain dynamics involves analyzing fMRI and EEG data using tools from statistical physics. He has made significant contributions to self-organized criticality and stochastic dynamics of complex systems, particularly in condensed matter and evolutionary contexts. The recent publications reflect a strong trend toward interdisciplinary complexity science, integrating concepts from physics, biology, economics, and neuroscience. Keywords across these works include complexity, statistical mechanics, dynamical systems, and network theory, with subfields ranging from neural avalanches to financial instability and biodiversity modeling. Henrik Jensen is the author of two influential books: Self-Organized Criticality and Stochastic Dynamics of Complex Systems (with Paolo Sibani), which have been widely cited across disciplines. He has supervised numerous PhD and postdoctoral researchers through the Centre for Complexity Science, though specific names are not listed. His research has been supported by grants from UK research councils and international collaborations, particularly in interdisciplinary complexity projects. He is affiliated with the Centre for Complexity Science, a multidisciplinary research hub at Imperial College London that brings together physicists, mathematicians, biologists, and social scientists to study complex adaptive systems.

Rasmus Leck Kæselerمشاهده پروفایل

استادیار

• Biomedical Engineering
• Robotics
• Machine Learning
• +۳ مورد دیگر

Rasmus Leck Kæseler is an Assistant Professor in the Department of Health Science and Technology at Aalborg University, affiliated with The Faculty of Medicine. His work focuses on neurorehabilitation robotics, particularly developing assistive technologies for severely disabled individuals through innovative interfaces like tongue-computer systems and brain-computer interfaces. Key projects include the CRERoB initiative (Center for Rehabilitation Robotics - phase II) and the MultiRob project, which explore multimodal control systems for robotic arms. He collaborates extensively on interdisciplinary research involving mechanical engineering, electrical engineering, and clinical applications. Research interests span neural signal processing (e.g., SSVEP classification), adaptive exoskeleton design, and user-centered interface development for individuals with spinal cord injuries or ALS. Recent publications emphasize improving assistive robotic systems through semi-automation and studying long-term user adaptation patterns. Rasmus participates in academic activities such as the 'Forskningens Døgn' public engagement event and workshops on generative AI in education. He holds positions in the Center for Rehabilitation Robotics and contributes to conferences like the IEEE Engineering in Medicine and Biology Society.

• Machine Learning
• Information Retrieval
• Medical Data Analysis
• +۳ مورد دیگر

Ingemar Johansson Cox serves as a Professor within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His research bridges theoretical machine learning foundations with practical applications across medical data analysis, information retrieval, remote sensing, and sustainability initiatives. His research portfolio emphasizes machine learning applications in high-impact domains, particularly medical data analysis (e.g., early detection of gynecological malignancy using online search activity) and sustainability (e.g., reducing AI's carbon footprint). The Machine Learning section actively contributes to the university's SCIENCE AI Centre, focusing on both algorithmic innovation and real-world problem-solving in biological modeling and environmental monitoring. Recent publication trends reveal expanding work in quantum computing applications for biomolecular modeling, sustainable AI frameworks, and cross-cultural NLP systems. His 2024-2025 output demonstrates strong interdisciplinary collaboration, especially in medical informatics and climate-related AI research. Professor Cox operates within the Department of Computer Science's robust research ecosystem, which includes dedicated compute clusters and specialized initiatives like TreeSense for global tree resource monitoring through remote sensing and deep learning. The department's infrastructure supports large-scale machine learning projects requiring significant computational resources.

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +۴ مورد دیگر

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

Frederik Marinus Trudslevمشاهده پروفایل

پژوهشگر ارشد

• Privacy Metrics
• Synthetic Data Generation
• Metagenomics
• +۳ مورد دیگر

Frederik Marinus Trudslev is a PhD Fellow at the Department of Computer Science, The Technical Faculty of IT and Design, Aalborg University, Denmark, focusing on critical challenges at the intersection of data privacy and bioinformatics. His research bridges computer science and computational biology through innovative work in synthetic data generation and genomic analysis. Trudslev's primary research domains include privacy-preserving synthetic data, where he develops rigorous metrics and evaluation frameworks to balance data utility with individual privacy protection. In bioinformatics, he pioneers ensemble methods for metagenomic binning, significantly improving microbial genome reconstruction from complex environmental samples through advanced clustering techniques. His 2023-2025 publications reveal a strategic pivot toward privacy-enhancing technologies, evolving from metagenomic binning (BinChill, 2023) to comprehensive privacy metric frameworks (2025 review) and practical evaluation tools (PrivEval, 2025). This progression demonstrates increasing specialization in synthetic data validation while maintaining cross-disciplinary relevance. As a key participant in the HEREDITARY project (2024-2027) on gut-brain interplay data integration, Trudslev collaborates with international researchers including Dell'Aglio and Lissandrini. Though no student advising is documented, his project leadership in this major EU-funded initiative highlights significant research impact. His work shows strong potential for future applications in healthcare data sharing and microbiome research.

Kaare Mikkelsenمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Sleep Science
• Wearable EEG Systems
• +۳ مورد دیگر

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.

Rune W. Bergمشاهده پروفایل

دانشیار

• Functional Neuronal Networks
• Sensory and Motor processing
• Complex physics
• +۳ مورد دیگر

Rune W. Berg is an Associate Professor in the Promotion Programme at the Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen. He leads the Berg Lab with research focused on Neuronal Signalling and maintains an active research profile with 66 publications to date. Dr. Berg's educational background includes a Ph.D. in Biophysics from the University of California, San Diego (2003), an M.S. in Physics from UC San Diego (2000), and Cand. Scient. and B.Sc. degrees in Biophysics from the Niels Bohr Institute at the University of Copenhagen (2000 and 1997 respectively). His research interests span Functional Neuronal Networks, Sensory and Motor processing, and Complex physics. The Berg Lab investigates neural signaling mechanisms with a strong emphasis on developing novel technologies for neural interfacing and brain research. Recent work demonstrates an interdisciplinary approach combining neuroscience, physics, and engineering to create advanced tools for neural monitoring and modulation. Analysis of Dr. Berg's recent publications reveals a strong focus on neural engineering technologies, particularly optical and electromagnetic approaches for brain research. His work bridges fundamental neuroscience with practical engineering solutions for neural interfaces, with applications in understanding brain function and developing neural prosthetics. The research spans from molecular-level interactions to circuit-level neural dynamics. Dr. Berg has participated in specialized training workshops including 'Construction of the brain' at Kristineberg Marine research station, 'Neurophysics' at the Institute of Theoretical Physics in Santa Barbara, and 'Neuron as a nonlinear oscillator' at the Salk Institute. His professional experience includes continuous work since January 2004 as a Post Doctoral member of Jorn Hounsgaard's Lab at the University of Copenhagen, following a Visiting Post Doctoral fellowship at Taipei Veterans General Hospital and National Yang-Ming University in Taiwan (September-December 2003).

• Human Factors
• Human-Computer Interaction
• E-Health
• +۶ مورد دیگر

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.

Hans Martin Kjerمشاهده پروفایل

دانشیار

• Ultrasound Imaging
• Super-Resolution Imaging
• Biomedical Image Analysis
• +۷ مورد دیگر

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.