Robert Jenssen is a Professor in the Machine Learning Research Group at UiT The Arctic University of Norway and serves as the Director of Visual Intelligence , an 8-year Research Council of Norway-funded SFI center. His research focuses on solving societal challenges in healthcare, marine mapping, energy, and Earth observation through collaborations with industry and public stakeholders. Director, Visual Intelligence (SFI) Center Professor, UiT Adjunct Professor, Pioneer Centre for AI (University of Copenhagen) and Norwegian Computing Center His methodological expertise spans neural networks, information-theoretic learning, self-learning, and explainable AI (XAI). Recent work emphasizes multimodal learning, uncertainty estimation, and medical image analysis. Scientific awards include: Best Paper, Pattern Recognition Letters (2024) Dissertation Award, Norwegian AI Society (2023) Best Paper, Color and Visual Computing Symposium (2022) IEEE GRS Society Letters Prize (2013) Prize for Young Researchers, University of Tromsø (2007) He contributes to international leadership as a member of the Scientific Advisory Board (SAB) for the Max Planck Institute for Intelligent Systems, France's SequoIA AI Excellence Cluster, and Denmark's DIREC center.
Johan Gustav Bellika is a Professor at the Department of Clinical Medicine, UiT The Arctic University of Norway, based in Tromsø. His work bridges clinical medicine with health informatics, focusing on practical applications that improve healthcare delivery and patient outcomes. Current Position: Professor, Department of Clinical Medicine Institution: UiT The Arctic University of Norway Location: Tromsø, Norway Contact: johan.gustav.bellika@uit.no Professor Bellika's research spans several critical areas in modern healthcare. His primary focus is on health informatics with particular emphasis on medical data privacy, electronic health records, and the application of artificial intelligence in clinical settings. He has made significant contributions to understanding chronic pain management through technology, primary care research networks, and patient-centered care models. His work often involves large population studies such as the Tromsø Study, examining how digital health tools impact healthcare utilization and patient outcomes. His research demonstrates a consistent thread connecting technological innovation with practical clinical applications. Bellika has been instrumental in developing privacy-preserving architectures for healthcare data analysis, which enable researchers to gain insights from sensitive health information without compromising patient privacy. His work on federated learning frameworks represents cutting-edge approaches to analyzing medical data while maintaining strict privacy controls. Health Informatics and Medical Data Privacy Chronic Pain Management through Technology Primary Care Research Networks (PraksisNett) Electronic Health Records and Clinical Decision Support Patient-Centered Digital Health Solutions Federated Learning Applications in Healthcare Professor Bellika's publication record shows a strong trend toward interdisciplinary research that combines clinical medicine, computer science, and public health. His recent work increasingly focuses on the intersection of artificial intelligence and healthcare, particularly how machine learning can be applied to chronic conditions while maintaining rigorous privacy standards. The geographical scope of his research extends across Norway with particular emphasis on Northern Norwegian populations, providing valuable insights into healthcare delivery in Arctic and remote regions. His collaborative approach is evident through numerous co-authored publications with researchers across multiple institutions and disciplines. While specific awards aren't detailed in the available information, his extensive publication record in reputable journals suggests recognition within his field. Professor Bellika has been actively involved in several major research initiatives including the Tromsø Study and PraksisNett, Norway's nationwide practice-based research network. His work on privacy-preserving architectures for healthcare data has significant implications for how medical research can be conducted while respecting patient confidentiality. He appears to be particularly focused on translating research findings into practical tools for clinicians, as evidenced by his work on audit and feedback systems for antibiotic prescribing.
Michael Riegler is a Researcher at the AI Department, Simula Research Laboratory , focusing on interdisciplinary applications of Artificial Intelligence in healthcare, sports analytics, and multimedia systems. His work bridges Machine Learning , AI Alignment , and Applied AI across clinical and real-world domains. Key Affiliations: Simula Research Laboratory (AI Department Head) Research Themes: Explainable AI in medicine, multimodal data analysis, and AI-driven health monitoring Research Interests include: Developing AI/ML algorithms for medical imaging (e.g., polyp detection, embryo analysis) Addressing missing data challenges in healthcare through novel imputation techniques Creating multimodal virtual avatars for investigative interview training Designing edge AI systems for sports analytics and sustainable fishing Recent Publications highlight collaborations with institutions in Norway and globally, with a focus on: Medical Applications: Polyp segmentation, ECG analysis, and explainable models for disease detection Sports Analytics: Athlete performance prediction and soccer video processing Data Infrastructure: Lifelogging datasets (ScopeSense), semantic representation frameworks Labs & Teams include leadership in Simula’s AI Department and participation in projects like Medico Multimedia Task , ImageCLEF , and MediaEval workshops. His work emphasizes responsible AI innovation in public sectors and privacy-preserving systems for edge environments.
Erik Velldal is a Professor in the Language Technology Group (LTG) at the Section for Machine Learning , Department of Informatics, University of Oslo . With over 25 years of experience in machine learning and natural language processing (NLP), he leads the SANT project focused on sentiment analysis and contributes to major research initiatives including MediaFutures , NorwAI , and Integreat (Norwegian Center for AI Research). His work bridges linguistic theory and computational methods, emphasizing semantic modeling and uncertainty detection. Research interests include sentiment analysis , language modeling , event extraction , and machine learning applications to NLP. Recent publications address cross-domain sentiment classification , generative event analysis , and multilingual model adaptation . He co-developed the Norwegian Review Corpus (NoReC) and Norwegian Anaphora Resolution Corpus (NARC) , foundational resources for Norwegian NLP. His projects often involve collaboration with international institutions, reflected in publications at venues like ACL, COLING, and EMNLP. Current efforts focus on entity-level sentiment analysis , diagnostic datasets for Norwegian , and evaluating compositional generalization in language models. No public record of scientific awards or part-time appointments exists.
Søren Holm is a Professor at the Center for Medical Ethics , University of Oslo. His work spans medical ethics, bioethics, and research ethics , with a focus on artificial intelligence in healthcare, pandemic ethics, and organ transplantation . Primary Affiliation: University of Oslo, Faculty of Medicine Research Themes: AI diagnostics, informed consent, research integrity, end-of-life ethics Key Collaborations: Thomas Ploug, Bjørn Hofmann, Daniel Warrington Recent Publications (2023-2025) analyze ethical challenges in AI-driven healthcare regulation, pandemic research ethics, and data governance . Notable topics include contestable AI diagnostics , equipoise in clinical trials , and conflict of interest disclosure . Contact: Email via soren.holm@medisin.uio.no . No scientific awards or student advisement details explicitly mentioned in the scraped text.
Erlend Hem is a Professor II at the Department of Behavioral Medicine , University of Oslo. He is also affiliated with the Department of Health Management and Health Economics as a student. His research focuses on suicide epidemiology, mental health among healthcare professionals, and mortality statistics. University of Oslo Department of Behavioral Medicine Department of Health Management and Health Economics (student) His work includes analyzing suicide rates in physicians and veterinarians, psychological distress in intensive care workers during the pandemic, and disparities in cancer outcomes. Studies like the NORVET survey and methodological research on mortality recording highlight his interdisciplinary approach. Recent publications address English language barriers in medical literature comprehension and historical medical practices. Scientific contributions span journals like Tidsskrift for Den norske legeforening , BMC Psychiatry , and BMJ Open . Collaborative projects involve teams from Norwegian public health and emergency medicine sectors.
Malgorzata Agnieszka Cyndecka is a Professor at the Faculty of Law, University of Bergen (UiB) , where she specializes in EU/EEA state aid law and data protection/GDPR. She is affiliated with SLATE (Centre for the Science of Learning & Technology) and serves as a member of the Norwegian Data Protection Board. Since 2019, she has been Associate Editor of the European State Aid Law Quarterly . She also holds an Associate Professor II position at the University of Oslo and contributes to interdisciplinary research on AI, privacy, and education. University: University of Bergen School: Faculty of Law Academic Rank: Professor Email: malgorzata.cyndecka@uib.no Affiliations: SLATE, Norwegian Data Protection Board, Council of Europe Expert Group on AI and Education Her research centers on EU/EEA state aid rules —particularly their application in tax, energy, and education sectors—and data protection law , with a focus on GDPR compliance in AI-driven educational technologies. She has led and contributed to major projects such as the Norwegian Data Protection Authority’s Sandbox for Responsible AI (AVT project), where she provided legal guidance on processing student data, and UiB’s DIGI courses, where she co-developed DIGI113 on Privacy and GDPR. Her work bridges legal theory with practical policy, influencing national and international frameworks on digital rights and public aid. The analysis of her recent publications reveals a strong focus on the evolution of state aid jurisprudence , especially the Market Economy Operator Principle (MEOP), burden of proof in aid cases, and sustainability in public support. Concurrently, her interdisciplinary work explores AI and privacy challenges in education , anonymization of unstructured data under GDPR, and ethical implications of algorithmic decision-making. Her contributions span legal doctrine, policy recommendations, and public commentary. Scientific Awards: European State Aid Law Quarterly PhD Award (2012–2016) for best doctoral dissertation in state aid law Advising and Grants: She supervises master’s students in EU/EEA law, data protection, and GDPR. She has been involved in externally funded projects including the Norwegian Data Protection Authority’s Sandbox for Responsible AI, the ENDO4P project (aimed at personalized endocrinology treatment via EU Horizon funding), and the Clean Up Project (Machine Learning for Anonymisation of Unstructured Personal Data) at the University of Oslo. She has also coordinated collaborations with Media City Bergen for law and technology education. Her teaching includes course leadership in JUS2302, JUS3502, JUS2303, JUS3503, and DIGI113. Labs and Teams: She is a key member of SLATE (Centre for the Science of Learning & Technology) at UiB and participates in multiple research groups including the Research Group for Information and Innovation Law. She contributes to interdisciplinary teams working on digital competence, AI ethics, and data governance in education and health. She is also active in the Academy for Young Researchers (AYF) and leads the EU and EEA Law Issues Committee in the Norwegian branch of the International Commission of Jurists (ICJ).
Bettina Sandgathe Husebø is a Professor and Head of the Center for Geriatric and Nursing Home Medicine at the Department of Global Health and Community Medicine, Faculty of Medicine, University of Bergen (UiB). She also serves as Innovation Manager at IGS, UiB since 2019. Her extensive career spans clinical practice, research, and leadership roles in geriatric and palliative care. Dr. Husebø completed her medical education at the University of Bonn, Germany in 1988, followed by specialization in Anaesthesiology and Intensive Care in 1995. Her Norwegian qualifications include Medical Specialization in Palliative Medicine (2012) and Nursing Home Medicine (2014) from UiB, along with a PhD from the Faculty of Medicine Dentistry at UiB in 2008. She further enhanced her expertise with a Postgraduate Safety, Quality, Informatics and Leadership (SQIL) Program from Harvard University in 2021. Her research focuses on critical geriatric issues including pain assessment and management in dementia patients, behavioral disturbances in dementia, palliative care in nursing homes, and digital phenotyping applications for elderly care. She has pioneered work on the relationship between pain, agitation, and neuropsychiatric symptoms in dementia patients, particularly through the COSMOS trial and LIVE@Home.Path study. Her recent publications (2023-2025) demonstrate a strong emphasis on digital health solutions for dementia care, with particular focus on activity monitoring, pain assessment through technology, and community-based interventions for aging populations. Her work bridges clinical geriatrics, technology innovation, and patient-centered care models. Among her notable recognitions are the National Dementia Award by His Majesty King Harald of Norway (2022) and multiple awards for research excellence in pain management and palliative care. Her work has significantly influenced Norwegian healthcare policy regarding dementia care and end-of-life practices. As an educator, she lectures in English, German, and Norwegian on dementia, pain in dementia, innovation technologies for older adults, symptom management at end-of-life, systematic medication review, and advance care planning. She has received teaching awards including 'Teacher of the Year' from the Faculty of Medicine and Dentistry at UiB. Dr. Husebø leads the Center for Geriatric and Nursing Home Medicine (SEFAS) and has been instrumental in establishing Norway's first palliative care ward in a nursing home. Her research group focuses on translating evidence into practice to improve quality of life for elderly patients, particularly those with dementia.
Joao Carlos Amaro Ferreira is a Professor at the Faculty of Logistics, Molde University College (HiMolde), Norway. He holds PhDs in Computer Engineering and Industrial Engineering from the Technical University of Lisbon and the University of Minho, respectively. His research focuses on Artificial Intelligence (AI) applications in healthcare, energy, transportation, IoT, blockchain, and smart cities. He has led over 40 projects, including 6 as Principal Investigator, and contributed to international conferences like OAIR and INTSYS. He served as IEEE CIS President (2016-2018) and is an IEEE Senior Member since 2015. His academic contributions span AI-driven solutions for public sector informatics, healthcare data quality, and cybersecurity. He actively participates in European projects such as e-Hospital4Future and explores blockchain applications in supply chains and medical records. Ferreira leads the ABC-AI research group, emphasizing ethical and applied AI. His work bridges academia and industry through projects like gamification systems for eco-driving and AI in fisheries traceability. Recent publications highlight AI's role in cardiovascular disease detection, emergency department optimization, and blockchain-enhanced healthcare interoperability. He collaborates internationally, co-editing journals like Applied Sciences , and has authored patents in edge computing for maritime monitoring.
Bjørg Dale is a Professor at the Department of Health and Nursing Sciences at the University of Agder, Norway. She is affiliated with the Center for Care Research, South and holds a PhD in Nursing Science from the University of Oslo (2009) for her work on compensatory care in older adults. Education: PhD in Nursing Science (2009), University of Oslo Clinical experience: Nurse and leader in municipal and specialist health services since 1978 Research Focus includes ageing research, elderly care, municipal health services, and holistic patient processes. Her work emphasizes transitions between hospital and home care, nursing competence, and self-care among older adults. Publication Trends show a focus on nursing competence in municipal acute care, psychometric validation of healthcare instruments, telemedicine applications, and quality of life in elderly populations. Key methodologies include cross-sectional and qualitative studies. Collaborations span institutions like the University of Oslo and South Eastern Norway Regional Health Authority. She contributes to nursing education reform and policy discussions on elderly care challenges. Contact: Email bjorg.dale@uia.no | Office: C4060, Jon Lilletuns vei 9, 4879 Grimstad, Norway
Elisabeth Wetzer is an Associate Professor in Machine Learning at the Department of Physics and Technology, UiT The Arctic University of Norway. Her research bridges artificial intelligence with healthcare applications, focusing on multimodal image registration, bias mitigation in AI, and physics-informed learning models. Current Role: Associate Professor, Machine Learning Group Research Themes: AI ethics, medical imaging, cross-modal representations, algorithmic fairness Her recent work explores technical challenges in PET imaging analysis and societal implications of AI bias. Collaborative projects span medicine, mathematics, and computer science disciplines. Key scientific contributions include: Physics-informed deep learning for PET image data Studies on multi-task learning efficacy in medical classification Research on gender bias in algorithmic systems She actively participates in diversity initiatives and public outreach, including presentations at Nobel laureate conferences and media engagements on AI ethics.
Norwegian University of Science And TechnologyNorway
Neil Martin Davies is a Researcher at the Department of Public Health and Nursing , Norwegian University of Science and Technology (NTNU) . His work bridges epidemiology, genetics, and public health, with a focus on causal inference, Mendelian randomization, and socioeconomic health disparities. His research explores the intersection of genetic epidemiology , developmental psychology , and clinical outcomes . Key themes include the impacts of antiseizure medications in pregnancy , cardiometabolic risks in psychiatric populations , and health policy implications of Mendelian randomization . Recent publications highlight methodological advancements in directed acyclic graphs (DAGs) , instrumental variable analysis , and family-based sampling . His work frequently addresses parental education effects , sleep patterns , and genetic correlations in large cohorts like UK Biobank. Neil Martin Davies contributes to scientific reporting standards , co-authoring the STROBE-MR guidelines for Mendelian randomization studies. His collaborations span neurology , mental health , and health economics , emphasizing causal relationships over correlational findings.
Hege Bjøkne Wathne is an Associate Professor in Intensive Care Nursing at the Department of Care and Ethics, University of Agder. She is affiliated with the NFR project "eHealth from Hospital 2 Home" and the research program area "HevHelse". Her primary research focuses on eHealth interventions to improve health services post-hospital discharge, particularly for patients with chronic illnesses and non-communicable diseases. She holds a PhD candidate status in Health Sciences (2020–), a Master in Health Sciences (2011–2013), and certifications in Intensive Care Nursing (2006–2007) and Nursing Education (1996–1999). Her work emphasizes nurse-assisted remote monitoring systems, usability of digital health tools, and patient self-management strategies. Key publications explore eHealth feasibility in colorectal cancer care, heart failure management, and chronic illness recruitment strategies. She has presented at conferences like the Nordic Conference in Nursing Research and participated in interdisciplinary collaborations to design patient-centered digital health solutions. Current projects aim to bridge gaps between hospital and home care through innovative technology. Wathne’s contributions include protocol development for randomized controlled trials and co-creation methodologies involving patients in eHealth design. Her research aligns with broader goals of enhancing healthcare accessibility and continuity through technology-driven interventions.
Jim Tørresen is a Professor of Computer Science at the Department of Informatics, University of Oslo, where he has been employed since 1999 (Associate Professor 1999-2005, Professor since 2006). He serves as group leader for the Robotics and Intelligent Systems (ROBIN) research group and is also a Principal Investigator at the Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO). His academic career includes visiting positions at Cornell University's Creative Machines Lab (2010-2011) and Kyoto University in Japan (1993-1994). His educational background includes a Dr.ing. (Ph.D.) in Computer Architecture from the Norwegian University of Science and Technology (1996) and an M.Sc. in Computer Architecture from the same institution (1991). Before his academic career, he worked in industry at Navia Aviation (1998-1999) and NERA Telecommunications (1996-1998). Tørresen's research spans artificial intelligence, robotics, and bio-inspired computing. His work focuses on biology-inspired algorithms, programmable logic (FPGA), robotics (simulation, prototyping, control), and human-robot interaction. He has made significant contributions to areas including evolutionary computing, reconfigurable hardware, and adaptive systems. His research often bridges theoretical computer science with practical applications in healthcare, music, and industrial settings. His recent publications demonstrate a strong focus on human-robot interaction, particularly in healthcare contexts for elderly care, as well as applications in sports science, musical robotics, and geological engineering. His work shows a consistent pattern of interdisciplinary research that combines machine learning techniques with domain-specific challenges. Tørresen has also authored a popular science book on artificial intelligence in the "what is" series by Universitetsforlaget, which discusses fundamental concepts, methods, future perspectives, and ethical aspects of AI. He has been active in academic leadership, serving as General Chair for the 22nd International Conference on Field Programmable Logic and Applications (FPL) in 2012 and the 9th Joint IEEE International Conference of Developmental Learning and Epigenetic Robotics in 2019. As group leader of ROBIN, he oversees research on intelligent systems that operate in dynamic environments requiring runtime adaptation. The group works at both fundamental and applied levels, using evolutionary algorithms for robot learning and machine learning techniques for classification and recognition tasks in various application domains.
Kristin Braa is a Professor at the Department of Informatics, University of Oslo, and serves as Director of the HISP Center. Her career includes an 8-year tenure as Research Director at Telenor, where she established a Research and Innovation Center in Malaysia. Academic Roles: Vice Head of Department of Informatics, head of Information Systems (IS) research group Research Focus: Mobile extensions of open-source DHIS2 software for low-resource settings, action research methods, sustainable health information systems Research Themes: She investigates innovative approaches to support rural healthcare workers and underserved populations, emphasizing long-term engagement in national health systems. Her projects include MobiHealth (2010–2014) and NORAD-funded initiatives (2010–2014) for health information systems in developing countries. Scientific Awards: 2023 AIS Impact Award (with Jørn Braa) 2020 Roux Prize (with Jørn Braa) 2013 University of Oslo Innovation Prize 2013 Researcher of the Year (Faculty of Mathematics and Natural Sciences, UiO) 2011 ICT and Energy Researcher of the Year 2011 Rosing Prize Finalist for rural Bangladesh health initiative Collaborations: Active in the IS research group and Climate Health Network. She advocates for sustainable, community-empowering information systems through participatory design and sociotechnical approaches.
