جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Natural Language Processing
• Health Informatics
• +۳ مورد دیگر

Maher Harring Kassem serves as a Guest Researcher within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His position falls under the research staff category, reporting to Head of Section Professor Yevgeny Seldin, and contributes to the department's mission in theoretical and applied machine learning research. His research spans Machine Learning , Natural Language Processing , Health Informatics , Sustainable AI , Quantum Machine Learning , and Cross-Cultural Computing . This interdisciplinary profile integrates computational methods with real-world applications in mental health analysis, culinary adaptation systems, emotion recognition, and environmental sustainability, reflecting the department's focus on domains like medical data analysis and biological modeling. Analysis of his 2024-2025 publications reveals a distinct trend toward high-impact interdisciplinary work. Key themes include sustainable AI development (addressing energy consumption in models), quantum-biomolecular applications (free energy calculations), cross-cultural NLP systems (recipe adaptation), and clinical AI (nursing values evaluation). His output demonstrates technical depth across optical neural hardware, EEG-based semantic relevance, and fairness-aware recommender systems, while consistently tackling societal challenges like climate impact and healthcare equity. No scientific awards or fellowships were documented in the available materials. As a Guest Researcher, Kassem leverages the department's powerful compute cluster and participates in initiatives like the SCIENCE AI Centre and TreeSense project for remote sensing of global tree resources. His collaborative work spans medical imaging analysis, quantum computing applications, and sustainable AI development, utilizing the university's infrastructure for large-scale computational tasks in domains ranging from wetland conservation to quantum photonic computing.

• Machine Learning
• Quantum Machine Learning
• Neural Networks
• +۶ مورد دیگر

Sebastian Bugge Loeschcke is a PhD Fellow at the Machine Learning Section of the Department of Computer Science (DIKU), University of Copenhagen . His research spans theoretical and applied machine learning with focus on quantum machine learning, language modeling, and sustainability. Current affiliation: Machine Learning Section, DIKU Key research areas: Quantum-classical hybrid models, neural language processing, geospatial analysis Collaborative initiatives: SCIENCE AI Centre, TreeSense Centre Loeschcke's recent work includes Coarse-To-Fine Tensor Trains for compact representations and LoQT: Low-Rank Adapters for Quantized Pretraining , reflecting his focus on efficient neural architectures and quantum-inspired methods. His publications address cross-disciplinary challenges in climate modeling, healthcare, and quantum computing. Scientific contributions include: 2024: Tensor train compression methods for visual representations 2024: Low-rank adapter techniques for quantized models 2025: Quantum computing applications in molecular binding energy calculation 2025: Ethical frameworks for sustainable AI development 2025: Quantum dot array simulation tools (QDarts) Loeschcke contributes to interdisciplinary projects involving: TreeSense (remote sensing of global tree resources) Quantum computing optimization with Danish research consortia

• Machine Learning
• Quantum Computing
• Medical Data Analysis
• +۳ مورد دیگر

Thomas Vecchiato is a Guest Researcher at the Department of Computer Science , University of Copenhagen , specializing in Machine Learning . His work intersects theoretical foundations with applications in quantum computing, sustainability, and biomedical data analysis. His research focuses on: Quantum-inspired machine learning architectures Ethical and sustainable AI development Medical imaging and clinical data analysis Language models for emotion recognition and healthcare applications Recent publications highlight advancements in: Optical neural network hardware Quantum biomolecular energy calculations Federated learning for personalized medicine Explainability techniques for AI models

• Algorithms
• Machine Learning
• Computational Complexity
• +۲ مورد دیگر

Benjamin Bogø is a Research Fellow at the Department of Computer Science, University of Copenhagen. His work bridges algorithmic complexity, machine learning, and quantum computing, with a focus on sustainable AI and cross-cultural applications. He is affiliated with the SCIENCE AI Centre and contributes to the department's compute cluster initiatives. Benjamin's research interests include: Quantum computing applications in neural networks AI explainability and ethical frameworks Algorithm optimization for complex systems Climate-aware machine learning Interdisciplinary biomedical and cultural data analysis His recent publications analyze: Quantum-classical hybrid systems (15% of articles) Large language model interpretability (20% of articles) Medical and ecological applications (30% of articles) Quantum hardware optimization (25% of articles) Algorithmic fairness in recommender systems (10% of articles)

• Machine Learning
• Computer Science
• Quantum Computing
• +۳ مورد دیگر

Mathias Nygaard Larsen is an Instructor at the Department of Mathematical Sciences and Department of Computer Science (DIKU) at the University of Copenhagen. His research spans interdisciplinary domains including Machine Learning , Quantum Computing , and Computational Modeling , reflecting collaborations between mathematical and computer science communities. His publications highlight innovative approaches in Quantum-enhanced computational methods Explainable AI systems Biomedical data analysis Cross-cultural algorithmic frameworks Current work focuses on environmentally sustainable AI practices and quantum-classical hybrid models for biomolecular simulations, utilizing Copenhagen's advanced compute infrastructure.

• Machine Learning
• Natural Language Processing
• Medical Image Analysis
• +۵ مورد دیگر

Nicolai Braad Pedersen is an Instructor at the Department of Computer Science and the Department of Mathematical Sciences at the University of Copenhagen. His work intersects machine learning, quantum computing, and biomedical applications. Department of Computer Science, University of Copenhagen Department of Mathematical Sciences, University of Copenhagen His research focuses on machine learning and its theoretical foundations, with applications spanning natural language processing , medical data analysis , biological modeling , and quantum machine learning . He contributes to the University of Copenhagen's SCIENCE AI Centre and Machine Learning Section , exploring topics like sustainable AI and quantum-inspired neural networks . Nicolai's recent work includes: Quantum computing applications for biomolecular free energy calculations Environmental sustainability in AI development Neural network architectures for optical and quantum systems Reinforcement learning optimization under entropic risk He utilizes the department's powerful compute cluster and collaborates with initiatives like the TreeSense center for remote sensing and deep learning of global tree resources.

• Machine Learning
• Artificial Intelligence
• Data Analysis
• +۳ مورد دیگر

Nadja Petersen is an Instructor at the Department of Computer Science , University of Copenhagen. Her work is affiliated with the Machine Learning Section and the SCIENCE AI Centre, focusing on theoretical foundations and applied research in domains like healthcare, environmental sustainability, and quantum computing. Email: nape@di.ku.dk Research Interests: Nadja contributes to areas including neural network hardware, sustainable AI practices, emotion recognition in conversational systems, and quantum computing applications for biomolecular analysis. Her work intersects machine learning with interdisciplinary challenges such as climate modeling, medical diagnostics, and computational biology. Recent Publications: Her research spans optical neural network processors, sustainable AI frameworks, and quantum-enhanced molecular simulations. Key trends include AI interpretability, cross-cultural recipe generation, and brain-computer interface applications. Labs & Teams: She collaborates with the Machine Learning Section at DIKU, a hub for foundational and applied research connected to the SCIENCE AI Centre. The section explores quantum machine learning, medical imaging, and environmental data analysis.

Strahinja Dosenمشاهده پروفایل

استاد

• Rehabilitation Engineering
• Robotics
• Myoelectric Control
• +۶ مورد دیگر

Strahinja Dosen is a Professor and Head of Research Group in the Department of Health Science and Technology at Aalborg University's Faculty of Medicine. His research focuses on neurorehabilitation systems, particularly in rehabilitation engineering, robotics, and human-machine interfaces. He holds a PhD in Biomedical Engineering from Aalborg University (2009) and serves as a Visiting Professor at the University of Novi Sad. His work addresses cutting-edge topics like myoelectric control, brain-machine interfaces, artificial sensory feedback, and functional electrical stimulation. Key projects include the development of closed-loop robotic prostheses and sensory feedback systems for amputees. Dosen has led over 17 research projects, including the PERSONIFY initiative on powered ankle prosthesis control and the DexterHand bionic prosthetics platform. With 216+ publications, his research emphasizes improving prosthetic control through electrotactile/haptic feedback, 5G-enabled bionic limbs, and stroke rehabilitation robotics. He collaborates internationally on neurorehabilitation technologies and has been featured in media for innovations like thought-controlled prosthetics and robotic rehabilitation systems. Grants and collaborations include EU-funded projects and industry partnerships. His team's work contributes to UN Sustainable Development Goals related to health and innovation. Dosen advises on 6 PhD students and actively participates in academic workshops and editorial roles in haptics and prosthetics.

Mads Rovsing Jochumsenمشاهده پروفایل

دانشیار

• Neurorehabilitation
• Brain-Computer Interfaces
• Signal Processing
• +۳ مورد دیگر

Mads Rovsing Jochumsen is an Associate Professor at Aalborg University's Department of Health Science and Technology, within the Faculty of Medicine. He leads the Laboratory of Brain-Computer Interfaces and EEG, and serves as Semester Coordinator for the 3rd semester in medicine and medicine with industrial specialization. His expertise spans neurorehabilitation, brain-computer interface (BCI) technology, and assistive robotics for individuals with motor impairments. Education: PhD in Biomedical Engineering (2015), Aalborg University MSc in Biomedical Engineering (2012) BSc in Biomedical Engineering (2010) Research Focus: Jochumsen’s work centers on BCI systems for stroke, cerebral palsy, and multiple sclerosis rehabilitation. He explores signal processing, neuroplasticity induction, and gamified rehabilitation tools. His research also addresses telerehabilitation and neurological condition assessment using electrophysiological signals. Awards: Elite Research Travel Scholarship (2014) Annual Meeting Prize at Danish Biomedical Engineering Society (2015) Grants & Projects: He leads initiatives like 'Gamified BCI Training for Cerebral Palsy' (Elsass Foundation) and 'Brain-Controlled Exoskeletons for Stroke Rehabilitation' (VELUX FONDEN). Current collaborations include the Center for Rehabilitation Robotics, advancing hybrid exoskeletons for severely disabled individuals. Labs & Teams: Active in the Neural Engineering and Neurophysiology Center and the Center for Rehabilitation Robotics, focusing on interdisciplinary innovation in assistive technologies.

Juwairiya Siraj Khanمشاهده پروفایل

پژوهشگر

• Neurorehabilitation Robotics
• Biomedical Engineering
• Human-Robot Interaction
• +۳ مورد دیگر

Juwairiya Siraj Khan is a Researcher at the Department of Health Science and Technology, part of Aalborg University's Faculty of Medicine. Their work focuses on neurorehabilitation robotics, biomedical engineering, and assistive technologies. They are affiliated with the Neurorehabilitation Robotics and Engineering Center and the Center for Rehabilitation Robotics. Research interests include exoskeleton design optimization, human-robot interaction, cardiac health monitoring using AI, and biomechanics. Notable projects include participation in the CRERoB initiative funded by Louis-Hansen fonden, focusing on advancing rehabilitation robotics technologies. Publications span topics from adaptive exoskeleton systems to AI-based cardiac diagnostics, reflecting a multidisciplinary approach. Recent work emphasizes user-centric design in assistive technologies and improving clinical outcomes for individuals with motor impairments. Key collaborations include interdisciplinary teams at Aalborg University and participation in international symposiums on rehabilitation robotics. Their research bridges engineering innovation with clinical applications, aiming to enhance mobility and healthcare through advanced technological solutions.

• Biomedical Engineering
• Rehabilitation Robotics
• Exoskeletons
• +۷ مورد دیگر

Lotte N. S. Andreasen Struijk is a Professor and Director at Aalborg University's Department of Health Science and Technology (HST), within the Faculty of Medicine. She leads the Center for Rehabilitation Robotics and the Neurorehabilitation Robotics and Engineering Research group. Her work focuses on enhancing quality of life for individuals with severe disabilities through rehabilitation engineering and robotics innovations, including the iTongue system and EXOTIC exoskeleton projects. Roles: Director of Center for Rehabilitation Robotics, Head of Research Group, and Professor at AAU. Administrative roles: Member of AAU's Academic Council, HST Diversity Board, and various national committees like the Danish Society of Engineers' Think Tank on Welfare Technology. Research Interests: Her expertise spans biomedical engineering, rehabilitation robotics, exoskeletons, and neurorehabilitation technologies. Key projects include developing assistive robotic arms, tongue-based interfaces, and clinical methods for ALS assessment. She has supervised 9 PhD students as main supervisor and 5 as co-supervisor since 2006. Awards: Honorary Professorship at Amity University, Vanførefondens Forskerpris, and recognition from IEEE and Sigma Xi. Grants/Projects: Lead PI on multiple grants, including the CRERoB project (2024-2027) and a clinical ALS biomarker study (2023–ongoing). Over 30 projects funded by institutions like the Independent Research Fund Denmark. Labs/Teams: Heads the Rehabilitation Engineering and Robotics Lab and Biorobotics Lab. Collaborates internationally on exoskeletons and neural interfaces.

Naveed Ur Rehmanمشاهده پروفایل

دانشیار

• Signal Processing
• Machine Learning
• Biomedical Signal Processing
• +۳ مورد دیگر

Naveed Ur Rehman is an Associate Professor at Aarhus University's Department of Electrical and Computer Engineering, specializing in Signal Processing and Machine Learning. His research bridges mathematical methodologies with real-world applications in biomedical systems and environmental forecasting. His primary interests include: Multivariate signal analysis using Mahalanobis distance and detrended fluctuation analysis Graph signal processing for spatial-temporal data modeling Biomedical signal processing for clinical applications (e.g., IRRAflow® system evaluation) Machine learning integration with signal decomposition techniques Environmental monitoring systems for air quality forecasting Recent publications demonstrate his focus on developing adaptive signal processing frameworks that address both theoretical challenges and practical implementations. This includes: Time-varying graph processing methodologies Hybrid machine learning/signal decomposition techniques Statistical validation approaches for denoising algorithms Biomedical device performance analysis Multi-scale functional connectivity modeling His work spans interdisciplinary collaborations, particularly with medical researchers for intracranial pressure management systems and environmental scientists for air quality modeling.

Jeroen Bergmannمشاهده پروفایل

استاد

• Prosthetics Engineering
• Mouth Protector
• Sensor Network Engineering
• +۱۰ مورد دیگر

Jeroen Bergmann serves as Head of Department in the Department of Technology and Innovation at the University of Southern Denmark (SDU). His research spans multiple interdisciplinary fields at the intersection of biomedical engineering, medical devices, and regulatory science. As department head, he leads academic initiatives focused on translating engineering innovations into practical healthcare solutions while navigating complex regulatory landscapes. Dr. Bergmann's research portfolio demonstrates expertise across several interconnected domains: Prosthetics and sensor technologies for medical applications Temperature monitoring and thermal behavior in biomedical contexts Medical device regulatory affairs and compliance frameworks Wearable biosensors and electronic skin technologies Sleep apnea diagnostics and home testing solutions Inertial measurement and position tracking systems Medical device software and AI applications in healthcare His work consistently bridges technical innovation with practical healthcare implementation, as evidenced by his fingerprint showing strong connections between engineering disciplines and clinical applications. Analysis of Dr. Bergmann's recent publications reveals a strategic dual trajectory: advancing biomedical sensing technologies while simultaneously developing frameworks for medical device regulation. His research shows increasing focus on AI-driven regulatory decision-making, particularly examining cross-jurisdictional compliance frameworks through approaches like RAG-based systems. Concurrently, his biomedical engineering work continues to refine oral cavity-based monitoring systems, temperature estimation methods, and sleep disorder diagnostics. The integration of physiological monitoring with environmental factors represents a novel approach in his recent work, suggesting movement toward more holistic health assessment systems that consider both internal and external variables. Dr. Bergmann's leadership role as Head of Department suggests significant administrative responsibilities alongside his research activities. His involvement in Health Innovation Day 2025 demonstrates engagement with broader healthcare innovation initiatives, while his international collaborations suggest a global research network. The department under his leadership appears to focus on technology innovation with direct healthcare applications, particularly in medical devices and regulatory science, positioning it at the critical intersection of engineering advancement and healthcare implementation.

• Neurosurgery
• Neuro-oncology
• Neurocritical Care
• +۴ مورد دیگر

Kåre Fugleholm Buch serves as a Clinical Associate Professor in the Department of Neurosurgery within the Department of Clinical Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. His clinical and research activities are centered at Rigshospitalet (Copenhagen University Hospital) in Copenhagen N, Denmark, where he maintains an active neurosurgical practice. His research focuses on neurosurgical conditions with emphasis on chronic subdural hematoma pathophysiology and management, meningioma biology and treatment resistance, and advanced neurosurgical techniques. Current work includes multicenter clinical trials like the DRAIN TIME 2 study published in The Lancet Neurology , innovative approaches to neurosurgical imaging, and nationwide epidemiological investigations into inflammatory mechanisms in neurosurgical disorders. Analysis of his recent publications reveals strong specialization in translational neurosurgery with recurring themes in biomarker discovery, surgical outcomes optimization, and methodological innovation in neurocritical care. His work frequently addresses clinical challenges in skull base tumors and postoperative management protocols. Buch maintains extensive national and international collaborations across neurosurgery, neuro-oncology, and critical care disciplines. His research group participates in multicenter trials and contributes to clinical guideline development, as evidenced by citations in clinical guideline sources. Current projects involve advanced imaging techniques for intraoperative navigation and large-scale studies on treatment-refractory intracranial tumors.

Milad Zamaniمشاهده پروفایل

استادیار

• Integrated Circuits
• Biomedical Engineering
• Wireless Power Systems
• +۳ مورد دیگر

Milad Zamani is a Tenure Track Assistant Professor in the Department of Electrical and Computer Engineering at Aarhus University. His research focuses on integrated circuits, biomedical engineering, and wireless power systems with applications in neural engineering and sensor systems. He leads projects such as DONUT (European Doctoral Network for Neural Prostheses and Brain Research) and CorroSense (Self-powered corrosion monitoring). His work spans topics like bio-impedance sensing for wearables, ultrasonic energy transfer for implants, and high-precision analog circuits. Recent projects include thermally-powered leakage detection systems and optogenetic implantable devices. Zamani collaborates on advanced sensor technologies, neuromorphic hardware, and biomedical device miniaturization. His lab develops low-power circuits for medical applications, combining signal processing with cutting-edge microelectronic design.