Editorial directory · Updated 7 November 2026
AI Expertise in Norway
144 professionals across 25 fields. Research, practice and society — in Norway and with Norwegian connections.
Editorial researchDisclaimer and methodological caveat
This is an editorial preliminary selection, not an officially approved national expert register. A number of names and subject areas have been checked against institutional directories, but not all current roles, publications or individual expert qualifications have been fully validated. The order does not indicate quality or ranking.
The directory combines an initial submitted selection with additions drawn from public professional sources. Not all entries have been fully rechecked. A profile link does not confirm a current role, expert qualifications or consent. Inclusion does not imply endorsement by the people listed.
This directory is provided for general information only, not as a certification, recommendation or guarantee of expertise or suitability for a particular task. It is not exhaustive, and information may be incomplete or outdated. Please verify current affiliations and relevant qualifications directly before relying on an entry.
Expert criteria ↓All caveats and sources ↓What counts as AI expertise here?
An expert has demonstrable, field-specific knowledge or practical competence relevant to artificial intelligence. Expertise may be technical, scientific, legal, ethical, educational, theological or organisational; it is not a claim of competence in every area of AI.
The following editorial criteria guide review of existing entries and new nominations:
- Documented AI relevance. Public evidence must connect the person’s work directly to AI, its development, application, governance or societal consequences. A neighbouring discipline alone is not enough.
- Substantive contribution. Evidence should show relevant research publications, technical systems or implementations, professional practice, policy or standards work, or sustained legal, ethical or educational analysis of AI.
- Verifiable evidence. Sources should identify the individual and their contribution, such as institutional profiles, publications or documented projects. A job title, LinkedIn profile, media visibility or self-description alone does not establish expertise.
- Clear scope and current information. Each review should identify the specific area of expertise, check the reported affiliation and distinguish current activity from earlier contributions.
- Equal treatment. The same evidence standard applies to all entries, including the editor. Seniority, popularity and personal connections are not substitutes for documented competence.
These are review criteria, not a certification already awarded to everyone listed. Individual evidence reviews are not yet complete. People working in adjacent fields should be understood as AI-related professionals unless their specific AI expertise is documented.
To nominate someone or suggest a correction, use the contact page. Please include their name, relevant field and public sources documenting their work. Nominations are reviewed against the same criteria and do not guarantee inclusion.
144 of 144 entries
Machine learning and foundational AI
15 entriesMorten Goodwin
UiA
Deep learning, applied AI
Helge Langseth
NTNU
Bayesian networks, decision support
Filippo Maria Bianchi
UiT
Machine learning, graph models, time series
Pål Grønås Drange
UiB
Algorithms and machine learning
Pinar Heggernes
UiB
Algorithms and AI research leadership
Pekka Parviainen
UiB
Machine learning and data science
Hans Julius Skaug
UiB
Statistics and machine learning
Fabian Andsem Harang
BI · SURE-AI
Mathematics for machine learning, signature methods and time-evolving data; research leadership in sustainable and ethical AI
Ole-Christoffer Granmo
UiA · CAIR
Tsetlin machines, machine learning, reinforcement learning and interpretable AI
Anders Kofod-Petersen
NTNU
Case-based reasoning, machine learning and intelligent systems
Anis Yazidi
OsloMet
Applied artificial intelligence and trustworthy AI
Jianhua Zhang
OsloMet
Machine learning, computational intelligence and neurocomputing
Mehak Khan
HVL
Machine learning, deep learning, graph learning and explainable AI
Anders Malthe-Sørenssen
UiO
Brain-inspired machine learning and AI applications in materials science
Stefano Nichele
OsloMet / Østfold University College
Biologically inspired AI, artificial life, neural systems and adaptive computation
Computer vision and image analysis
8 entriesRobert Jenssen
UiT
Deep learning, visual intelligence
Michael Kampffmeyer
UiT
Explainable AI, medical image analysis
Anne Solberg
UiO
Machine learning and image analysis
Line Eikvil
Norwegian Computing Center
Image analysis, applied machine learning
Adín Ramírez Rivera
UiO
Computer vision, representation learning
Arnt-Børre Salberg
Norwegian Computing Center
Remote sensing and image analysis
Anders Ueland Waldeland
Norwegian Computing Center
Image analysis in the energy sector
Kiran Raja
NTNU
Biometrics, machine learning, generative AI and computer vision
Language models, NLP and knowledge representation
7 entriesSamia Touileb
UiB
NLP, automated text analysis
Thomas Ågotnes
UiB
Logic, multi-agent systems
Bjørnar Tessem
UiB
AI algorithms and knowledge-based systems
Benjamin Ricaud
UiT
Graph-based machine learning, generative AI
Jon Atle Gulla
NTNU · NorwAI
Large language models, semantics, language technology and AI innovation
Pinar Øztürk
NTNU
Knowledge representation, case-based reasoning, multi-agent systems and AI fairness
Heri Ramampiaro
NTNU
Text analysis, information retrieval and machine learning
Robotics and autonomous systems
6 entriesJim Tørresen
UiO
Robotics and intelligent systems
Lei Jiao
UiA
Tsetlin machines and learning automata
Linga Reddy Cenkeramaddi
UiA
Autonomous systems and sensor technology
Kai Olav Ellefsen
UiO
Robotics and machine learning
Adil Rasheed
NTNU
AI, digital twins and drones
Puneet Sharma
UiT
AI, automation and image analysis
AI ethics, explainability and responsible AI
8 entriesInga Strümke
NTNU
Explainable AI and AI ethics
Marija Slavkovik
UiB
Machine ethics, logic and normative systems
Miria Grisot
UiO
Responsible AI and data practices
Tone Bratteteig
UiO
Human-centred AI and system design
Maja van der Velden
UiO
Critical AI studies, technology ethics
Kristoffer Wickstrøm
UiT
Explainable AI and model uncertainty
Fred Godtliebsen
UiT
Statistical methods and uncertainty analysis
Hugo Hammer
OsloMet / SimulaMet
Machine learning reliability, interpretability, uncertainty and reinforcement learning
AI in health and medicine
8 entriesHelge Ræder
UiB
AI in medicine
Bettina Husebø
UiB
AI in elder care and dementia
Michael Riegler
Simula
Medical AI and analysis
Klas Pettersen
Simula
AI and computational health research
Ole Christian Lingjærde
UiO
Medical informatics and machine learning
Karl Øyvind Mikalsen
UiT
AI in clinical medicine
Samuel Kuttner
UiT/UNN
Medical imaging, machine learning
Noeska Natasja Smit
UiB
Medical visualisation
Life sciences, bioinformatics and research data
6 entriesGeir Kjetil Sandve
UiO
Machine learning, biomedical data
Inge Jonassen
UiB
Bioinformatics and algorithms
Lars Ailo Bongo
UiT
Health data and computing infrastructure
Marit Bakke
UiB
AI in biomedical research
Torbjørn Rognes
UiO
Bioinformatics and sequence analysis
Elisabeth Wetzer
UiT
Machine learning and medical image analysis
AI in education, learning and human formation
7 entriesBarbara Wasson
UiB
AI in education, learning analytics
Mohammad Khalil
UiB
AI in education, synthetic data
Kine Maridatter Dørum Maxwell
UiT
Generative AI in higher education
Marko Lukic
UiT
AI in teaching and learning
Monika Nerland
UiO
Professional learning and digital knowledge practices
Guri Verne
UiO
Human–AI interaction
Jo Herstad
UiO
AI, human–computer interaction
AI law, regulation and privacy
6 entriesTobias Mahler
UiO
AI regulation, robotics law
Samson Yoseph Esayas
UiO
AI regulation, privacy and competition law
Malgorzata Cyndecka
UiB
EU/EEA law, privacy
Bjørn Aslak Juliussen
UiT
AI regulation and data security law
Mona Naomi Lintvedt
UiO
AI, privacy and robotics law
Vibeke Blaker Strand
UiO
Anti-discrimination law and emerging technology
AI, philosophy, society and human autonomy
9 entriesJill Walker Rettberg
UiB
AI, digital culture and narratives
Lars Nyre
UiB
Philosophy of technology and human–machine relations
Gabriele de Seta
UiB
Algorithms and digital culture
Scott Rettberg
UiB
Digital narratives and generative AI
Erik Knudsen
UiB
AI, political communication and media
Silvia Masiero
UiO
Digital identity, inclusion and technological justice
Herman Cappelen
The University of Hong Kong · formerly University of Oslo
Philosophy of AI, AI interpretation and communication; Director of the AI & Humanity Lab
Kari Steen-Johnsen
Norwegian Institute for Social Research
Generative AI, political knowledge, democratic participation and public debate; KnowAI researcher
Einar Duenger Bøhn
UiA
Philosophy of artificial consciousness and AI ethics, including the Moral Turing Test
AI and theology/religion
5 entriesÅke Elden
NLA University College
AI-mediated knowledge, human answerability and theological anthropology
Atle Ottesen Søvik
MF Norwegian School of Theology, Religion and Society
AI ethics, philosophy of religion and conceptions of human nature
Asle Eikrem
MF Norwegian School of Theology, Religion and Society
Ethics of artificial intelligence, systematic theology and human nature
Clemens Cavallin
NLA University College
AI and trust; generative AI, Christian imagination and Christian film production
Simon Simchai Hansen
OsloMet
Doctoral research on AI as a pedagogical dialogue partner in religious education (KIDU/AIDE)
AI in media, communication and creative expression
6 entriesChristoph Trattner
UiB/MediaFutures
Responsible AI and recommender systems
Duc Tien Dang Nguyen
UiB
Multimedia verification and analysis
Jason Nelson
UiB
AI and digital art
Alinta Kiri Krauth
UiB
AI and digital art
David Jhave Johnston
UiB
AI-based storytelling
Viktoria Stray
UiO
Generative AI in software development and collaboration
AI strategy, leadership and commercialisation
7 entriesVegard Kolbjørnsrud
BI
AI and organisational design
Silvija Seres
Technology consulting
AI strategy and digital transformation
Elin Hauge
Independent advisor
AI strategy and business
Lars Rinnan
Technology industry
AI business development
Anita Schjøll Brede
Iris.ai / technology industry
AI entrepreneurship
Peder Inge Furseth
BI
Technology-driven innovation
Morten Irgens
Academia and AI networks
AI policy and research strategy
Public sector, AI governance and implementation
6 entriesCathrine Pihl Lyngstad
NAV / AI collaboration
Data and public-sector AI implementation
Alex Moltzau
AI policy and research networks
Responsible AI and public policy
Alexander Moltubakk Kempton
UiO
AI and change in public administration
Arild Waaler
UiO
Industrial digitalisation and interoperability
Malcolm Langford
UiO / TRUST
Trustworthy AI in institutions and the legal system
Øystein Flø Baste
UiO
AI, education law and digital administration
Industrial AI, energy and the environment
8 entriesSigne Riemer-Sørensen
SINTEF
Industrial and applied AI
Michail Spitieris
SINTEF
Probabilistic and physics-informed AI
Felix Kohler
SINTEF
AI and industrial analysis systems
Katarzyna Michalowska
SINTEF
Analytics and industrial AI
Giulia Robbiani
SINTEF
Applied AI and analytics
Alexander Johannes Stasik
SINTEF
Machine learning and industrial systems
Yngve Birkelund
UiT
AI and wind power forecasting
Yan Zhang
UiO
Edge intelligence, federated learning and AI-enabled wireless networks and Internet of Things
AI safety, robustness and cybersecurity
6 entriesAli Ramezani-Kebrya
UiO
Robust and secure deep learning
Olav Lysne
Simula
Digital systems security
Lillian Røstad
Simula
Cybersecurity and digital trust
Jostein Jensen
Simula
Cybersecurity
Audun Jøsang
UiO
Information security and trust models
Vasileios Mavroeidis
UiO
Cyber threat intelligence and security analysis
AI and working life
3 entriesLene Pettersen
UiO
AI in knowledge work, digital workplaces, organisational collaboration and professional learning
Inger Marie Hagen
OsloMet · Work Research Institute
AI, digital management, hiring and workplace democracy; research on the Norwegian model of working life
Christin Thea Wathne
OsloMet · Work Research Institute
AI in policing, professional work and organisational change; AGOPOL research on algorithmic governance
AI in finance and economics
3 entriesPetter Eilif de Lange
NTNU
Machine learning and explainable AI for credit-default modelling, credit ratings and financial risk
Ranik Raaen Wahlstrøm
NTNU
Business analytics, deep learning in finance and explainable machine-learning models
Morten Risstad
NTNU
Machine learning for credit-default prediction and financial forecasting
AI and defence/security policy
3 entriesJohanne Jensen Skeie
Norwegian Defence University College · IFS
Doctoral research on military AI, state–technology-company relations and international security policy
Stian Kjeksrud
Norwegian Defence University College
International security, hybrid warfare and research on AI and virtual reality in military education
Ingebjørg Kåsen
Norwegian Defence Research Establishment (FFI)
AI research leadership, defence-sector AI strategy and responsible AI in NATO; documented in an FFI interview
AI and climate/sustainability
3 entriesRituka Jaiswal
NTNU
AI for smart grids, energy optimisation, fault detection and wind-farm integration
Xiangping Hu
NTNU · Industrial Ecology Programme
Machine learning and AI methods in environmental analysis and climate-change mitigation research
Stefan Pieter Sobolowski
UiB · Bjerknes Centre for Climate Research
Generative AI for local-scale climate information and explainable AI for climate prediction and attribution
AI and psychology/mental health
3 entriesKerstin Bach
NTNU
Machine learning and data-driven decision support; AI research in e-health projects including mental health
E. F. Haghish
UiB · Faculty of Psychology
AI and psychometrics in youth mental-health research, including risk and protective factors for suicidality
Torhild Tønnesen Haugnes
Modum Bad · doctoral research affiliated with UiO
Doctoral research on AI-based patient matching and machine-learning prediction of psychotherapy outcomes
AI and language technology for smaller languages
4 entriesErik Velldal
UiO
Norwegian language technology, NLP and machine learning
Trond Trosterud
UiT
Sámi language technology
Sjur Nørstebø Moshagen
UiT · Divvun
Sámi and indigenous-language technology, language tools and research on low-resource language technology in the age of machine learning
Ronny Paul
UiT
Co-authored research on large language models for Sámi and ultra-low-resource languages; documented contribution, not a claim of broad AI specialisation
AI and art/music
4 entriesAlexander Refsum Jensenius
UiO · RITMO / MishMash
Music technology, human–machine interaction and AI in creative practice; Director of MishMash
Kyrre Glette
UiO · RITMO
Machine learning for musical interaction and performance, including neural models for predicting performer actions
Daniel Nordgård
UiA · MishMash
AI in music industries, creative-sector policy and digitalisation; deputy director of the Centre for AI and Creativity
Çağrı Erdem
UiO · MishMash
Embodied interaction, human–AI co-creativity and shared control in interactive music performance
AI and sport
2 entriesIngrid Eir Thorp Eythorsdottir
Norwegian School of Sport Sciences (NIH)
Doctoral research using machine learning to interpret physiological data in elite sport; documented AI work in sport and sport education
Dag Johansen
UiT · Department of Computer Science
Machine-learning systems for sports performance analysis, including cross-country skiing and AI applications in football
Adjacent expertise in education and society
1 entriesAstrid Marie Jorde Sandsør
UiO · CREATE
Economics of education, educational inequality and causal policy evaluation. Adjacent expertise; direct AI specialisation has not been established by the sources reviewed.
About the AI professionals directory
This directory is an independent editorial initiative developed by Åke Elden. Its purpose is to highlight the breadth of Norwegian expertise in artificial intelligence, from technical research and implementation to ethics, philosophy, theology and religion, law, health, education and the social sciences.
The selection draws on publicly available information about professional activities, publications and documented expertise. The list is not a ranking, and inclusion does not mean that the person has approved or endorsed the project.
We aim to keep the information accurate and up to date. Reports of factual errors, updates or objections can be sent to the editor via the website’s contact page.
Sources and quality assurance
The categories are editorial. The safety category also includes researchers with expertise in related areas of cybersecurity, while the strategy and public-sector categories include people with implementation or policy expertise. The entries do not all represent the same depth of expertise in technical AI research. Norwegian connections may include nationality or research collaboration; inclusion does not necessarily mean a person is currently based in Norway.
The AI and theology/religion field covers documented work on AI in relation to theological anthropology, religious belief and practice, ethics, and religious education. It does not imply technical AI expertise. A background in theology or religious studies alone is not sufficient for inclusion in this field; related expertise without documented AI work is identified separately.
The working-life, finance, defence, climate, mental-health, smaller-language and art/music fields identify specific applications or consequences of AI, not interchangeable qualifications. Defence-policy analysis is distinct from cybersecurity engineering; mental-health AI research does not imply clinical qualifications or validated therapy; language technology includes both neural and rule-based approaches. Entries describe the documented contribution rather than competence across the entire field.
The AI and sport field covers documented machine-learning, computer-vision and data-analysis contributions to sport. Inclusion does not imply clinical qualifications, validated injury prediction, guaranteed performance improvements or endorsement by athletes or sporting organisations.
Reported source basis
The initial selection draws largely on the organisations listed below and their published expert and researcher directories. Complete source addresses and individual evidence records are not yet available for every entry.
- University of Bergen — interdisciplinary AI expertise in computer science, health, ethics and society.
- Visual Intelligence — machine learning, image analysis and explainable AI.
- University of Oslo, Department of Informatics — AI, robotics, responsible technology and information systems.
- UiT The Arctic University of Norway — machine learning, autonomy, language technology and regulation.
- Centre for Artificial Intelligence Research (CAIR), UiA — applied AI, intelligent systems and robotics.
- SINTEF — industrial AI, machine learning and technology applications.
- Simula — AI, data science, health technology and cybersecurity.
- TRUST – Norwegian Centre for Trustworthy AI — AI regulation, accountability and interdisciplinary research.
Verification status
This is not a validated national expert register. Full validation requires checks of current institutional affiliation, specific evidence of each person’s AI expertise, and consent to publication of profiles and contact information. These checks have not been completed for every entry, and approval by the people listed has not been documented.
A field is not the same as a type of expertise
AI-related expertise takes several forms. These distinctions help readers understand its scope; they are not yet individually verified labels attached to each person:
- F – Scientific research and publications
- T – Technical development and implementation
- S – Strategy, governance and organisational leadership
- J – Legal, ethical and social-scientific analysis
Media visibility and organisational positions are not, on their own, evidence of expertise in any of these areas.
Review, nominations and corrections
Individual profile review is a priority. Some entries represent adjacent disciplines, and the available evidence does not establish an equally clear AI specialisation for everyone listed. Readers should take this limitation into account when using the directory.
Nominations, factual corrections, updated sources and objections are welcome via the contact page. Evidence-based review helps broaden the selection and makes editorial decisions open to scrutiny.
Profile links in the initial selection were checked on 4 November 2026; sources for the latest additions were reviewed on 7 November 2026. These are source-review dates, not confirmation that every person’s expertise or affiliation has been fully verified.
Editorial transparency
Åke Elden develops and edits this directory and is also included in it. His entry is subject to the same evidence and review criteria as every other entry. Inclusion is an editorial decision, not an independent accreditation or an endorsement by the people listed.
Conclusion
The directory is a standing part of akeelden.com and will be kept and developed further. The aim is for it to grow, over time, into a national reference resource for Norwegian expertise in artificial intelligence.
That role is earned, not assumed: it depends on the individual quality assurance, openness to nominations and corrections, and regular updates described above. Until those steps are completed, this page should be read as an editorial preliminary selection.
The project also touches one of the site’s own research themes in practice: who is granted epistemic authority, on what grounds, and who decides who is counted as an expert?