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.
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.
Swati Aggarwal is a Professor in Artificial Intelligence at the Faculty of Logistics, Molde University College (HiMolde). Her research focuses on AI applications in healthcare, ethics, cognitive development, and neural networks. She holds a PhD in Neutrosophic Neural Networks, a Master's in Information Technology, and a Bachelor's in Computer Science and Engineering. Previously, she was a Marie Curie Postdoc Fellow at NTNU, working on AI models for cognitive assessment in infants (AIM_COACH project). Research Interests - AI in Health/Medicine - Ethics in AI and Societal Impact - EEG/BCI for Cognitive Assessment - Machine Learning and Deep Learning Publications Her recent work spans AI ethics, BCI applications, adversarial attacks, and healthcare diagnostics. Notable contributions include EEG-based infant perceptual monitoring (2025) and malaria detection via EfficientNet (2023). She also explores cross-lingual adversarial robustness and blockchain in hospitality systems. Labs/Teams - ABC-AI: Applied, Basic, and Conscientious AI Group - Virtual Technologies and Learning Research Group
Norwegian University of Science and TechnologyNorway
Marta Molinas is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). Her research spans multiple interdisciplinary domains with a focus on EEG technology and brain-computer interfaces. She actively supervises numerous Master's projects and maintains extensive international collaborations with institutions including Kavli Institute for Systems Neuroscience, RIKEN Center for Brain Science, University of Tsukuba, Juntendo University, and several European universities. Professor Molinas' research interests center on developing innovative EEG technologies, particularly her FlexEEG concept for reduced-channel EEG systems with brain imaging capabilities. Her work integrates signal processing, artificial intelligence, and neuroscience to create practical applications in mental health, sleep research, neurorehabilitation, and human-computer interaction. She specializes in EEG source imaging, machine learning for brain signal analysis, and the development of brain-computer interfaces for various applications including locked-in syndrome communication, ADHD treatment, and driver monitoring systems. Her publication portfolio demonstrates strong trends in interdisciplinary research combining neuroscience with electrical engineering and artificial intelligence. The work shows particular emphasis on developing practical EEG-based systems that minimize invasiveness while maintaining analytical power, with applications spanning healthcare, rehabilitation, and human augmentation. Her research bridges theoretical signal processing with real-world implementations through numerous student projects and international collaborations. Professor Molinas actively supervises a large team of Master's and PhD students across multiple projects, with each project typically requiring two students working collaboratively. Her research is supported through numerous international collaborations with institutions in Japan, India, and Europe, indicating substantial research funding and project leadership. She has developed a pipeline of student projects that build upon previous work, creating a cumulative knowledge base within her research group. She leads the EEG ITK research team at NTNU, which focuses on developing the FlexEEG headset prototype featuring flexible, wireless, dry electrodes designed to move across the scalp. This team works at the intersection of neuroscience, electrical engineering, and computer science, developing applications for sleep research, mental health monitoring, neurorehabilitation, and brain-computer interfaces. The team collaborates extensively with international partners including the Kavli Institute for Systems Neuroscience, the International Institute of Integrative Sleep Medicine at University of Tsukuba, and several engineering departments across Europe and Asia.
Geir Selbæk is a Professor II at the University of Oslo in the Department of Geriatric Medicine . His research focuses on dementia , neurodegenerative diseases , and aging-related mental health , with extensive work on the HUNT study —a large Norwegian population-based cohort. He investigates risk factors like depression , loneliness , metabolic health , and social determinants to understand dementia progression. Key research areas: Dementia epidemiology, geriatric mental health, neurodegenerative disease, aging, cognitive impairment Recent publications analyze AI in diagnostics, genetic risk scores, social media's role in pandemic isolation, and metabolic markers Collaborations Selbæk collaborates with international teams across Alzheimer's & Dementia , Nature Genetics , PLOS ONE , and other high-impact journals. His work integrates epidemiological data , neuropsychological testing , and molecular biology to address dementia prevention and care.
Trond Waage is a Professor in the Department of Social Sciences at UiT The Arctic University of Norway , specializing in Visual Anthropology . His research focuses on migration patterns in Sub-Saharan Africa, particularly in Cameroon, the Central African Republic, and Mali, while also exploring the intersection of visual methods with ethnographic research. Active in collaborative visual research with African communities Member of the War and Peace Dynamics research group Co-founder of the Sahel on Sahel research initiative Research Interests include: Migrant integration in urban African contexts Conflict dynamics in the Sahel region Participatory visual methods for ethnographic knowledge production His recent work has examined Boko Haram's impact on youth communities and the role of collaborative filmmaking in documenting post-conflict resilience. Professor Waage frequently collaborates with researchers across institutions in Norway and Africa to explore cultural translation and visual epistemology. He serves as: Editorial contributor to the Journal of Anthropological Films Supervisor in Master of Philosophy in Visual Anthropology program Co-developer of Visual Anthropology curricula in Niger
Dr. Mingyuan Zhang Betancourt is a socio-cultural anthropologist affiliated with the University of Oslo's Institute of Community Medicine and Global Health. Specializing in cross-cultural analysis between China and Africa, her work examines pharmaceutical supply chains and postcolonial development dynamics. PhD in Anthropology, University of Western Ontario (2018) Former Writing Fellow, University of Toronto Scarborough Her research spans multiple disciplines: Pharmaceutical Anthropology : Analyzing antibiotic shortages across India/China production networks China-Africa Relations : Investigating cultural identity formation through historic sugar plantations and Confucius Institute operations Political Ecology : Documenting resource conflicts in Malagasy agrarian systems Recent publications demonstrate: 2024 study on pharmaceutical production history 2023 comparative analysis of China-India trade disputes 2022 critique of cultural standardization in educational programs 2021 pandemic discourse analysis She actively explores: Global antibiotic accessibility Postcolonial development paradigms Transnational identity politics
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.
Tine Kristin Jensen is a Professor of Clinical Psychology at the University of Oslo's Department of Psychology, with a part-time affiliation at the Norwegian Centre for Violence and Traumatic Stress Studies. She specializes in child trauma, PTSD treatment, and developmental psychology, focusing on interventions for youth exposed to violence, disasters, and terrorism. Dr. Jensen co-leads major trauma-focused cognitive behavioral therapy (TF-CBT) implementation projects across Europe and conducts research on unaccompanied refugee minors and digital mental health interventions for war-affected children. Education: Cand. psychol. (University of Oslo, 1986) Approved specialist in clinical psychology (Norwegian Psychological Association, 1996) Dr. Psychol. (PhD, University of Oslo, 2005; thesis: Suspicions of Child Sexual Abuse) Her research interests span trauma treatment efficacy, post-traumatic stress symptom dynamics, and cultural influences on psychological recovery. She has pioneered studies on parental experiences of terrorism (e.g., Utøya attack survivors) and developed digital tools like apps to complement TF-CBT for adolescents. Dr. Jensen also addresses systemic challenges in child mental health services, including therapist burnout and resource allocation. Recent work explores social media literacy's role in youth mental health and evaluates stepped-care models for trauma survivors. She collaborates internationally with institutions like Drexel University and Denver University, contributing to global PTSD treatment guidelines. Key projects include: Implementation of TF-CBT in Norwegian child mental health clinics Treatment outcomes for unaccompanied asylum-seeking minors Longitudinal studies on terror survivors' mental health Development of trauma-focused interventions for online abuse victims Dr. Jensen actively contributes to Nordic psychology policy as a journal editor and sits on scientific committees for organizations like ECOTS. Her work bridges clinical practice, research, and public health policy to improve care for traumatized children and families.
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
Sebastien Nicolas Gros is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His research focuses on safe reinforcement learning (RL) and data-driven model predictive control (MPC), with applications in energy systems, biomedical engineering, and autonomous vehicles. Institution: Norwegian University of Science and Technology Department: Engineering Cybernetics His work emphasizes AI-driven optimization for domestic energy storage, battery integration, and smart building management. Collaborations include Equinor, DNV, Kongsberg, Volvo, and CorPower Ocean. Key themes in his publications include: Control theory for renewable energy systems (wave energy converters, buildings) Biomedical applications (artificial pancreas, glucose monitoring) Transportation systems (electric vehicles, autonomous ships) Machine learning integration with physical models He supervises 6 PhD students and co-supervises projects on multi-rotor wind turbines and industrial PhD collaborations. The articles demonstrate a convergence of RL, MPC, and uncertainty quantification across energy, biomedical, and transportation domains.
Tom Roar Eikebrokk is a Professor at the Department of Information Systems , University of Agder , Norway. He contributes to the Center for Digital Transformation (CeDiT) research group and has over two decades of academic and practical experience in digitalization, business process management, and collaborative innovation. Research Focus : Digital transformation, co-creation frameworks, e-health innovation, IT service management (ITIL), and remote work dynamics. Methodologies : Empirical studies, mixed-method research, case analysis, and Delphi studies. Recent Publications (2024–2025) explore reciprocal relationships between BPM and digitalization, generative AI for sustainable co-creation, and open innovation workspaces in specialized industries. His 2018–2021 work on co-creation in SME networks, worklife ergonomics in digital environments, and robotic process automation impacts remains influential. Collaborative Networks : Frequently co-authors with Dag Håkon Olsen , Niels Frederik Garmann-Johnsen , and Jon Iden , focusing on cross-municipal healthcare systems, digital governance, and IT competence frameworks.
Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.
Synnøve Kristine Nepstad Bendixsen is a Professor and Head of Department at the Department of Social Anthropology, University of Bergen (UiB), Faculty of Social Sciences. She is a leading scholar in migration, bordering, and welfare state dynamics, with extensive research on irregular migration, humanitarianism, and belonging in Nordic and European contexts. Her research interests include: Migration and bordering practices Welfare state exclusion and inclusion Irregular migrants' access to healthcare Humanitarian governance and encampment Transnational kinship and mobility Gender, religion, and identity among migrants Digitalization of welfare and borders Her recent publications (2022–2024) reflect a strong focus on the Nordic welfare model’s role in controlling migration through bordering practices, the moral economies of healthcare for irregular migrants, and the lived experiences of displacement. Themes across her work include precarity, slow violence, deservingness, and the paradoxes of egalitarian societies producing hierarchical belonging. Scientific contributions and outreach include: Keynote speaker at international conferences (e.g., University of Iceland, EASA) Invited lectures at Princeton, Oxford (COMPAS), Humboldt University, and others Public engagement through op-eds (Bergens Tidende, Morgenbladet), podcasts, and media interviews Documentary film co-creation: Birthdayparents (2018) She has advised PhD candidates such as Elina Niinivaara and Signe Aarvik and has led major research projects including: PrecaNord (2022–2025): Tackling Precarious and Informal Work in the Nordic Countries EQUALPART (2021–2025): Migrant Women’s Participation in Labour Supercamp (2019–2022): Genealogies of Humanitarian Containment Energethics (2015–2019): Norwegian Energy Companies Abroad She has organized academic events such as the Bergen Summer Research School and participates in public discourse on deep sea mining, inclusion, and migration policy. Her work bridges academic research, policy critique, and public anthropology.
