This is a list of artificial intelligence (A) labs in Norway. However, this list is not exclusively restricted to explicated ‘labs’, as it also includes research groups and centres. The aim is to map out central actors in the field of artificial intelligence to make it easier for you to navigate. If you feel your lab or group should have been on this list please contact email@example.com. You can also contact us if there are entities in this list you believe should not be included.
BigInsight is a center for research-based innovation, started in April 2015 as one of the third generation Norwegian Centres for Research-based Innovation. It is funded by the Research Council of Norway and by fifteen partners and will operate until 2023. One of their innovation objectives is oriented towards explaining AI and was started in 2018.
The Biomedicial Informatics research group (BMI) in the Section for Machine Learning (ML) at the Department of Informatics (IFI) focuses on computational and statistical applications in the medical and biological sciences. Combined, the two research areas bioinformatics and statistical genomics cover most of our activities.
The Centre for Artificial Intelligence Research (CAIR) is hosted by the Department of ICT at the University of Agder. CAIR opened 2nd of March 2017 and conducts fundamental artificial intelligence research. Artificial morality and causality, making machines that reason and act morally on the basis of causation rather than mere correlation. Machines that explore, experiment and learn, using deep reinforcement learning to optimize hydropower production and other complex systems. Deep information understanding and reasoning, mining knowledge from medical records and other big data.
Data Science is about drawing useful knowledge from large and complex data. Advances in Artificial Intelligence are greatly dependent on Data Science. The Center for Data Science of the University of Bergen is an interdisciplinary center across several faculties focusing on research and education in central aspects of Data Science and Artificial Intelligence. Their current activity involves machine learning, algorithmic foundations, visual data science, statistics, bioinformatics, and behavioral science. CEDAS is the main contact point for NORA, the Norwegian Artificial Intelligence Research Consortium, at the University of Bergen.
dScience – Centre for Computational and Data Science – at the University of Oslo (UiO) is an interdisciplinary centre developing and supporting research within computational science and data science across UiO and together with partners in industry and public sector. In addition to hosting research programs and projects, dScience develops mechanisms collecting, managing and sharing high-quality data for academic and business development purposes in Norway and internationally. dScience focuses on basic, long-term research, creates collaboration across disciplines and sectors, offers community services and contributes to the education and supervision of students. The centre was established 1 January 2021 with premises at campus Blindern with Professor Morten Dæhlen as centre leader. The centre is a part of The Faculty of Mathematics and Natural Sciences, but includes activities from other faculties and museums at the University of Oslo.
Greiff lab is based at the Institute of Clinical Medicine (University of Oslo), Norway. Their research focuses on developing novel computational and experimental strategies for designing next-generation therapeutics, diagnostics and vaccines by combining high-throughput single-cell antibody and T-cell receptor sequencing with artificial intelligence and high-dimensional statistics. Their ultimate aim is to improve public health by decreasing the burden that infectious and autoimmune diseases and cancer impose on humanity. They aspire to (i) be consistent and excellent in research and teaching, (ii) be inclusive and global with teams within both academia and industry and (iii) attain maximal openness of our research results.
The Norwegian Open Artificial Intelligence Lab (NAIL) is a hub for research, education and innovation within AI. The center is hosted by the Faculty of Information Technology and Electrical Engineering at NTNU in Trondheim. NAIL engages in a variety of research and innovation activities, with several ongoing projects and a strong team of AI researchers. They have projects in energy, health, connectivity, mobility, oceans and digital economy.
Nordic Centre for Sustainable and Trustworthy Artificial Intelligence Research (NordSTAR) is a Centre of Research Excellence in modern Artificial Intelligence (AI). The centre aims to establish a new paradigm in AI basic research, so-called sustainable and trustworthy AI. The centre is led by Pedro Lind and Anis Yazidi, and is part of the OsloMet AI Lab and Applied Artificial Intelligence. The main goal of NordSTAR is to develop AI tools, which embed all key aspects related with trustworthiness and sustainability. To do this the centre has established five research areas: (1) Security, safety and reliability; (2) Human factors in AI; (3) Quantum AI; (4) Biologically-inspired computational systems; (5) Understandable and explainable models.
Hosted at NTNU in Trondheim, the center coordinates research and innovation activities among three universities, two research institutes and 11 companies. With its long and impressive history of research on Big Data and AI and its experience with commercializing these technologies, NTNU is well positioned to lead this center of research-based innovation (SFI).
National center for cognitive technology, aiming to raise expertise and competence in artificial intelligence, and fuel and accelerate the implementation of AI by sharing and collaborating on data, resources, competence, insight, innovation and joint projects. Norwegian Cognitive Center is a strong industry crossover initiative to build Norway as a strong European AI hub and to attract world-leading expertise. They also have an AI industry sandbox to create an ecosystem for innovation to deploy AI projects. In the short term, the center will develop a number of specific projects within industries such as aquaculture, media, finance, tourism, healthcare, real estate, infrastructure, and the public sector, as well as initiate research projects. The long-term ambition is to raise, develop and specialize competence in cognitive technologies and artificial intelligence, and to create new high competence and high-tech jobs, which is strongly demanded by the industry.
The main objective of the centre is the development of responsible media technology, in particular leveraging AI technology, for the media sector. AI technology has shown to be of great value in many different application domains; however, it has also raised significant ethical issues, including, e.g., the creation of echo chambers in online media systems, and caused political polarisation and controversial or questionable election outcomes. To address these challenges, we established a world-class research centre named “MediaFutures: Research Centre for Responsible Media Technology & Innovation” in Bergen’s Media City. The centre is a consortium of the most important media players in Norway. The University of Bergen is the host of the centre. User partners include NRK and TV 2, the two main TV broadcasters in Norway, Schibsted, including Bergens Tidende (BT), and Amedia, the two largest news media houses in Scandinavia/Norway, as well as the world-renowned Norwegian media tech companies Vizrt, Vimond, Highsoft, Fonn and the global tech and media player IBM. The centre collaborates with renowned national research institutions including the University of Oslo, the University of Stavanger and NORCE, and works together with high-profile international research institutions.
The Mohn Medical Imaging and Visualization Centre (MMIV) has been established in collaboration between the University of Bergen and the Haukeland University Hospital through financial support from the Bergen Research Foundation (BFS) to promote cross-disciplinary research activities related to state-of-the-art imaging equipment such as preclinical and clinical high field MRI, CT and hybrid PET/CT/MR. The aim of the Centre is to research new methods in quantitative imaging and interactive visualization to predict changes in health and disease across spatial and temporal scales. This encompassed research in tissue feature detection, feature extraction and feature prediction.
OsloMet AI Lab administers research and student projects in artificial intelligence, both applied and basic research, including theory and the use of machine learning in different areas. OsloMet AI Lab administers research and student projects in artificial intelligence, both applied and basic research, including theory and the use of machine learning in different areas. OsloMet Artificial Intelligence Lab (AI Lab) is a joint research centre for OsloMet – Oslo Metropolitan University and SimulaMet (simulamet.no) located in the heart of Oslo. The Department of Computer Science is the host of the centre located in Pilestredet 52 in Oslo. The Applied Artificial Intelligence research group (AAI) took the initiative to the lab, which has members from many research groups at OsloMet and SimulaMet, and is at the forefront of artificial intelligence in Norway.
Simula@BI is a new research centre at BI Norwegian Business School. The purpose of Simula@BI is to facilitate collaboration on research and teaching in data science between BI Norwegian Business School and Simula Research Laboratory. The purpose of Simula@BI is to facilitate collaboration on research and teaching in data science between BI Norwegian Business School and Simula Research Laboratory. Simula@BI is a research center that focuses on applied and fundamental research in data science, with focus on applications in the intersection between business and data science. The center is a collaboration between Simula and BI, and aims to facilitate collaboration in the extended Norwegian data science community.
Erlend Aune is the head of the research center. Johannes Langguth from Simula is engaged as an adjunct researcher at BI Norwegian Business School. We will engage other researchers in 2021.
At Simula Metropolitan Center for Digital Engineering, the focus of the Machine Intelligence department is to advance frontiers of machine learning and data mining by developing novel methodologies and algorithmic solutions for the analysis of complex systems and high-dimensional data in science and industry. Our research activities span three general areas: statistical learning and regularization theory; data mining with a focus on the matrix and tensor factorization; and deep learning applications.
At SINTEF research is a part of the rapid and ongoing development of artificial intelligence. The objective of AI research done by their scientists is to collaborate with our partners to build world-leading competence and to enable clients to be part of the progress. AI@SINTEF is their laboratory for building, testing and achieving those goals. SINTEF is one of Europe's largest independent research organisations. Every year they carry out several thousand projects for customers large and small.
Stavanger AI Lab connects researchers, educators and students at University of Stavanger with partners in industry, business and public sector with the focus on artificial intelligence (AI) research and development. The research activity ranges from fundamental to applied research, with machine learning, deep learning and robot technology as the main focus or tool. Innovation will be one of the goals, where involvement of industry partners and creative student projects are essential.
Visual Intelligence is researching the next generation of deep learning methodology for visual data and producing solutions for our consortium partners across innovation areas in medicine and health, marine science, energy, and earth observation. Visual Intelligence shall be the lead provider of cutting-edge solutions for complex image analysis by leveraging deep learning to answer innovation needs shared across a consortium of corporate and public user partners from different business areas. They all rely on complex image data for sustainable value creation, posing shared research challenges. This enables crucial cross-fertilization in the research and innovation.