Find Academic Supervisors

• Artificial Intelligence
• Human-Computer Interaction
• Medical Imaging
• +5 more

Hubert Dariusz Zajac serves as a Research Fellow at the Department of Computer Science within the Faculty of Science , University of Copenhagen. His work focuses on Human-Centred Computing , particularly the intersection of artificial intelligence and healthcare systems. Email: hdz@di.ku.dk Location: Sigurdsgade 41, 2200 København N. Zajac's research interests span Artificial Intelligence , Human-Computer Interaction , and Medical Imaging . His recent publications examine sociotechnical challenges in clinical AI integration, dataset curation for medical imaging, and context-specific adaptations of AI systems across global healthcare environments. Key research trends include: Global health disparities in AI adoption Ethical considerations in medical AI Collaborative design methodologies Diagnostic workflow optimization Radiology practice standardization Clinician-AI interaction patterns Zajac's work contributes to understanding how AI systems can be effectively integrated into clinical environments while respecting human factors and contextual variability.

• Quality of Life Technologies
• mobile computing
• ubiquitous computing
• +7 more

Katarzyna Wac is a Visiting Professor at the Department of Computer Science, University of Copenhagen, leading the Quality of Life Technologies lab. Her research focuses on leveraging mobile and wearable technologies for context-rich, privacy-preserving assessment of behavior, health, and quality of life . Key research areas include digital phenotyping , human-centered AI , and behavioral modeling . She holds a PhD in Information Systems (2009) from University of Geneva, MSc in Telematics (2004) from University of Twente, and BSc/MSc in Computer Science (2003) from Wroclaw University of Technology. Research outputs highlight collaborations in digital health , chronic disease management , and ubiquitous computing . Recent publications emphasize transformer-based models for health data analysis , Alzheimer’s screening via wearables , and stress assessment through peer-based methodologies . She received the Best Student Paper Award (2019) and contributes to interdisciplinary frameworks for digital behavior change interventions and human-smartphone interaction analysis . Labs/teams: Quality of Life Technologies Lab Human-Centred Computing Section, University of Copenhagen

• Machine Learning
• Computer Science
• Natural Language Processing
• +3 more

Mikolaj Tymon Mazurczyk is a Research Fellow at the Department of Computer Science, University of Copenhagen. His research intersects with machine learning and computer science, focusing on areas such as natural language processing, medical image analysis, and biological data modeling. The Machine Learning Section at DIKU explores both theoretical and applied aspects, including information retrieval, medical data analysis, remote sensing, and sustainability. They participate in the SCIENCE AI Centre and collaborate with various research groups. Dr. Mazurczyk's recent publications highlight advancements in optical neural networks, sustainable AI, and quantum computing applications. His work also addresses fairness in recommender systems and interpretability in large language models, as well as clinical informatics and biomedical data analysis.

Mostafa Mehdipour GhaziView profile

Assistant Professor

• Machine Learning
• Deep Learning
• Artificial Intelligence
• +13 more

Mostafa Mehdipour Ghazi is an Assistant Professor at the Department of Computer Science , University of Copenhagen , and a member of the Pioneer AI (P1AI) research group. His work bridges machine learning, medical imaging, and neuroscience to address challenges in healthcare. Education : PhD in Medical Imaging with Deep Learning from University College London. Languages : Azerbaijani, Turkish, Persian, English, Danish. Research Interests : Machine Learning and Deep Learning Medical Imaging Analysis (MRI, CBCT) Robust Representation Learning for Heterogeneous Data Bias, Fairness, and Privacy in Generative Models Domain Adaptation and Transfer Learning Brain Disease Modeling (Alzheimer's, Stroke, Tumors) Article Trends : Recent work focuses on multimodal AI for disease prediction, deep generative models in neuroimaging, and domain adaptation techniques. Applications span Alzheimer's diagnosis, cerebral microbleeds in COVID-19, and adaptive segmentation tools like RARE-UNet and FAST-AID.

• Machine Learning
• Computational Biology
• Protein Engineering
• +3 more

Richard Michael is a PhD Fellow and Guest Researcher at the Machine Learning section of the Department of Computer Science , University of Copenhagen. His work focuses on bridging machine learning with computational biology, particularly in protein engineering and optimization of discrete sequences. Research Interests High-dimensional Bayesian optimization for discrete sequences Regression models in biomolecular design Continuous relaxation techniques for discrete problems Fitness landscape analysis in protein engineering Gaussian processes for predictive modeling Publication Trends Recent work highlights interdisciplinary approaches combining machine learning with computational biology. Key areas include optimization of discrete sequences (e.g., proteins or DNA), systematic benchmarking of regression models for biomolecular tasks, and development of novel computational frameworks for high-dimensional problems. His publications span both conference proceedings (e.g., NeurIPS) and peer-reviewed journals (e.g., PLOS Computational Biology). Contact Email: richard.michael@di.ku.dk

• Machine Learning
• Natural Language Processing
• Medical Data Analysis
• +4 more

Rasmus Mikelsons serves as a Lecturer at the Department of Computer Science , University of Copenhagen . His email contact is rami@di.ku.dk . He is affiliated with the Machine Learning section and participates in the SCIENCE AI Centre, focusing on both theoretical and applied machine learning research. Research Interests Machine Learning Natural Language Processing Medical Data Analysis Remote Sensing Sustainability Computational Biology The Machine Learning section conducts research ranging from theoretical foundations to applications in domains such as information retrieval, medical imaging, and biological data modeling. Recent publications highlight trends in quantum machine learning, sustainable AI, and multimodal applications. Labs and Teams He is part of the Machine Learning section at the Department of Computer Science, which has access to a dedicated compute cluster and participates in initiatives like TreeSense, a center for remote sensing and deep learning of global tree resources.

• Computer Science
• Machine Learning
• Natural Language Processing
• +3 more

Zeb Harris Buus Nielsen is an Instructor (mapped to Lecturer) at the Department of Computer Science , University of Copenhagen. His role involves teaching and academic engagement within the department’s diverse research areas, including algorithms, machine learning, and computational modeling. Contact: Universitetsparken 1, DK-2100 Copenhagen Ø | Phone: +4535324731 | Email: zeb.nielsen@di.ku.dk Research Interests span core aspects of computer science, with implicit alignment to the department’s focus on: Machine Learning Natural Language Processing Software Development Data Science Algorithm Design

• Natural Language Processing
• Computer Science
• Machine Learning
• +3 more

Siddhesh Milind Pawar is a Research Fellow in the Natural Language Processing group at the Department of Computer Science , University of Copenhagen. His work is part of the Software, Data, People & Society (SDPS) section, which focuses on software systems, data management, and interdisciplinary research aligned with societal needs through collaborations with industry. Current Position: Research Fellow, Department of Computer Science, University of Copenhagen Research Focus: Natural Language Processing, Machine Learning, and Software Systems Contact: Email sipa@di.ku.dk

• Algorithms and Complexity
• Human-Centred Computing
• Image Analysis
• +11 more

Andreas Peder Agerskov Pedersen is an Instructor affiliated with both the Department of Computer Science (DIKU) and the Department of Economics at the University of Copenhagen . His work spans multiple research sections, including Algorithms and Complexity, Machine Learning, and Human-Centred Computing. Research Interests His research focuses on interdisciplinary areas within computer science and economics, particularly: Algorithm design and complexity analysis Human-computer interaction and user-centered systems Computational modeling for economic and social systems Machine learning applications in data-intensive domains Programming language theory and software engineering

• Machine Learning
• Quantum Computing
• Artificial Intelligence
• +7 more

Jonatan Ruiz-Molsgaard is an Instructor at the Department of Computer Science , University of Copenhagen. His research spans interdisciplinary applications of machine learning in quantum computing , medical data analysis , and environmentally sustainable AI . Research trends include: Quantum-inspired algorithms for biomolecular modeling Interpretability techniques for large language models Fairness frameworks in recommender systems Neural network applications in healthcare and climate science

• Algorithms and Complexity
• Theoretical Computer Science
• Data Structures
• +3 more

Nikolaus Alexander Schrack is a Lecturer at the Department of Computer Science (DIKU) of the University of Copenhagen. His work is associated with the Algorithms and Complexity (AC) section, which focuses on theoretical computer science, including data structures, graph algorithms, computational complexity, and algorithmic paradigms with applications in machine learning. Research Interests: His research aligns with the AC section's exploration of efficient computation, combinatorial problem-solving, and theoretical foundations impacting real-world challenges. Key areas include algorithm design for massive data, optimization, and interdisciplinary applications. Publications: A 2022 publication in the Findings of the Association for Computational Linguistics investigates the use of Abstract Meaning Representation (AMR) for legal and logical reasoning tasks. Contact: Email: nikolaus.schrack@di.ku.dk Address: Universitetsparken 1, DK-2100 Copenhagen Ø

Stefan Horst SommerView profile

Professor

• Machine Learning
• Riemannian Geometry
• Stochastic Processes
• +3 more

Stefan Horst Sommer is a Professor at the Department of Computer Science (DIKU), University of Copenhagen . He leads the Pioneer AI (P1AI) section, serves as Head of Studies for Machine Learning and Data Science, and co-founded the Center for Computational Evolutionary Morphometry (CCEM) with Rasmus Nielsen. His work bridges stochastic processes , geometric statistics , and machine learning with applications in computational anatomy and diffusion modeling . Key Roles : Head of Pioneer AI, Head of MLDS Studies, CCEM PI Labs : Applied Geometry Lab, CCEM Research focuses on Riemannian geometry , anisotropic diffusion , and stochastic shape analysis . Current projects include geometric machine learning for aerodynamic modeling and probabilistic image registration with applications in medical imaging and evolutionary biology . His 96+ publications emphasize manifold-valued processes and geometric deep learning . Collaborations span computational anatomy , stochastic mechanics , and AI-driven scientific computing . He co-organizes international workshops on geometric statistics and maintains active GitHub repositories for open-source research tools.

Birthe DinesenView profile

Professor

• Telehealth
• Telerehabilitation
• Welfare Technology
• +7 more

Birthe Dinesen is a Professor at Aalborg University's Department of Medicine and Health Technology within the Faculty of Health Sciences. Her work centers on the Center for Sensory-Motor Interaction and ExerciseTech, with extensive contributions to telehealth implementation across cardiac, respiratory, and mental health domains. PhD in Health Technology (specific institution not stated) Extensive international clinical trial experience Focus on technology transfer from research to clinical practice Professor Dinesen's research spans telehealth , telerehabilitation , and welfare technology with particular emphasis on gamification and user-driven innovation . Her fingerprint analysis shows dominant work in Telerehabilitation (100%), Heart Failure management (46%), and Rehabilitation Engineering (45%). Current projects integrate machine learning for sleep apnea screening and AI for emergency department imaging analysis, reflecting her commitment to translating technology into practical healthcare solutions. Publication trends reveal consistent output since 2003 with significant acceleration after 2011. Her 211 publications demonstrate specialization in cardiac telerehabilitation (particularly atrial fibrillation and heart failure), COPD management, and stroke rehabilitation using digital tools. Recent work increasingly incorporates machine learning and social robotics. Best poster award 2023 (Klinisk Kvalitet) Professor Dinesen has secured 8 major research projects including the Velux Foundation-funded 'Brain-controlled exoskeletons for stroke rehabilitation' and the Heart Association's 'The Patient of the Future' atrial fibrillation study. She has supervised 3 PhD students and maintains 231 press/media appearances highlighting her role as a public health technology advocate. Her datasets on COPD telerehabilitation have been widely shared through Figshare. Current leadership includes the 'Future Patient: Telerehabilitation and Gamification' project (2019-2022) and active development of AI applications for emergency radiology. Her ExerciseTech lab focuses on sensor-based rehabilitation systems with international clinical validation studies.

Jens Brøndum FrøkjærView profile

Clinical Professor

• Magnetic Resonance Imaging (MRI)
• Chronic Pancreatitis
• Diabetic Neuropathy
• +5 more

Jens Brøndum Frøkjær is a Clinical Professor at Aalborg University Hospital under the Faculty of Health Sciences . He works in the Diagnostic Imaging Department , focusing on imaging-based biomarkers for early disease detection, classification, and treatment monitoring. His research spans neuropathy , neuroplasticity , chronic pain , and visceral organ pathologies , particularly chronic pancreatitis . He leads the Radiology Research Center , an interdisciplinary hub integrating radiology , biomedical engineering , and translational medicine . Core research: MRI acquisition/analysis, neuromodulation therapies Key collaborations: European Pancreatic Exocrine Insufficiency Multidisciplinary Group , University of Aalborg , international consortia Recent publications emphasize AI-driven radiomics in CT imaging , pancreas segmentation , and neuropathic pain mechanisms in diabetes . His work bridges clinical implementation of imaging diagnostics and multidisciplinary research networks .

Waheed Akbar BhattiView profile

Associate Professor

• Knowledge Exchange in Relationships
• Role of Technology in Business Processes
• Consumer Experience
• +4 more

Waheed Akbar Bhatti is an Associate Professor and Part-Time Lecturer at Aalborg University Business School, Faculty of Social Sciences and Humanities. He is affiliated with the Marketing and Market Processes Research Group and the MIX - Center for Displacement, Migration, and Integration. His academic work intersects business, technology, and sustainability, with a focus on international collaboration and industry transformation.