Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .
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.
Özlem Özgöbek is an Associate Professor at the Department of Computer Technology and Informatics, Norwegian University of Science and Technology (NTNU). Her research spans artificial intelligence, machine learning, and recommender systems with a focus on privacy, fake news detection, and educational technology. NTNU - Department of Computer Technology and Informatics Her work explores multimodal fake news detection, privacy implications in recommender systems, and technology-enhanced classroom interaction. Recent publications analyze digital education trends and classroom tools. Özgöbek collaborates with international researchers and contributes to news recommendation workshops. Her projects address ethical AI, environmental sustainability, and real-time information processing.
Carlos Velasco is an Associate Professor in the Department of Marketing at BI Norwegian Business School, where he co-founded the Center for Multisensory Marketing. He holds a D.Phil. in Experimental Psychology from the University of Oxford and has established himself as a leading researcher at the intersection of psychology, marketing, and human-computer interaction. His research focuses on multisensory experiences and their underlying principles, with particular attention to crossmodal correspondences between sensory modalities. His work spans diverse areas including digital dining, food technology, customer experience management, and the application of emerging technologies like AI, VR, and the Metaverse in sensory marketing. Velasco has published extensively in top journals across multiple disciplines including Food Quality and Preference, Journal of Retailing, Journal of Business Research, Psychology and Marketing, and International Journal of Human-Computer Studies. His research reveals consistent patterns in how sensory inputs influence consumer behavior and product perception, particularly examining how visual elements, sounds, and shapes correspond with taste experiences. Velasco's work also explores the ethical dimensions of customer experience design in digital environments and investigates how cultural contexts shape multisensory food experiences globally. Velasco has authored several influential books including Multisensory experiences: Where the senses meet technology (2020 and 2025, Oxford University Press), Digital dining: New innovations in food and technology (2025, Springer Nature), and the edited collection Multisensory packaging: Designing new product experiences (2019, Palgrave Macmillan). Serves on editorial boards of Food Quality and Preference Journal of Business Research Psychology and Marketing International Journal of Gastronomy and Food Science International Journal of Food Design Currently, Velasco co-hosts the customer experience management podcast and collaborates with companies worldwide on topics including multisensory experiences, immersive technologies, Web3, food and drink, branding, and consumer research. His work bridges academic research with practical applications in marketing and product design.
Adín Ramírez Rivera is a Professor in the Digital Signal Processing and Image Analysis (DSB) group at the Department of Informatics, University of Oslo. His research focuses on representation learning and computer vision, particularly exploring machine learning methods to describe and understand visual data. He is a Senior Member of the IEEE and a member of the ELLIS Society. Education : PhD from Kyung Hee University's Image Processing Lab, South Korea; Bachelor's degree in Engineering from Universidad de San Carlos de Guatemala, majoring in Computer Science and Systems Engineering. Ramírez Rivera's research spans diverse computer vision tasks including facial analysis, object detection, image enhancement, and vision transformers. His work emphasizes self-supervised learning, fair representation learning, and novel neural network architectures for image segmentation and classification. Recent publications highlight trends in vision transformers, crowd counting, facial expression recognition, and fair representation learning. His articles frequently address statistical modeling, feature extraction, and deep learning techniques for visual tasks. Scientific Awards : Senior Member of the IEEE, Member of the ELLIS Society. He collaborates with researchers across institutions, contributing to projects involving anomaly detection, multilingual translation, and astrophysical modeling. His lab affiliations include the Digital Signal Processing and Image Analysis group and the Section for Machine Learning at the University of Oslo.
Jonas Bakken is a Professor of Norwegian Didactics at the Department of Teacher Education and School Research, University of Oslo. His work bridges rhetoric, children's literature, and sustainable development education through innovative didactic approaches. As academic director of the Associate Professorship Program, he shapes teacher education and curriculum design. Research Interests: Norwegian language arts, rhetoric integration in education, ecocriticism, multicultural narratives, and bilingual pedagogy. Projects: Evaluation of bilingual education (ETOS), Linking Instruction and Student Experiences (LISE), Scandinavian Narratives of Guilt and Privilege (Scanguilt), Minority Literary Voices in Scandinavia. Publications span textbook analysis, rhetorical strategies in Sámi literature, CLIL education equity, and oral creativity pedagogy. His recent works focus on task culture conflicts and curriculum renewal in Norwegian language arts.
Anis Yazidi is a Professor at Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design and the Department of Information Technology. His research focuses on Artificial Intelligence, Machine Learning, Medical Technology, and IoT Security, with a particular emphasis on Applications of AI in Healthcare, EEG Signal Processing, and Digital Transformation. Active research projects include AI Mind (dementia diagnostics), Glycopathology in dry eyes, and Pain and mental distress analysis Completed projects: Digital hate speech analysis, AI in reproductive technology, Nano-antibiotics development His recent publications (2023-2025) demonstrate expertise in: Tsetlin Automaton algorithms for concept learning EEG classification using visibility graphs and vision transformers AI ethics frameworks for medical practice Deepfake detection methodologies Collaborative work spans institutions in Norway, Czech Republic, and international AI research communities.
Gaute Barlindhaug serves as an Assistant Professor in the Department of Language and Culture at UiT The Arctic University of Norway, within the Faculty of Humanities, Social Sciences and Teacher Education. His academic work bridges artistic practice with scholarly research in sonic arts and cultural documentation. His research interests span Sonic Arts , Sound Studies , Music Technology , and Digital Humanities , with particular focus on the ontological status of sound recordings, the intersection of traditional and digital sound technologies, and the preservation of cultural heritage through both artistic and technological approaches. His work often examines how sonic mediations transform aesthetic experiences and cultural expressions. Analysis of his publications reveals a consistent trajectory exploring the relationship between technology and sonic expression, with recent work incorporating artificial intelligence applications in document preservation. His research demonstrates an interdisciplinary approach that combines artistic practice with scholarly inquiry, particularly evident in his contributions to the Journal for Artistic Research. Barlindhaug is actively involved in multiple research initiatives: Engaging Conflicts in a Digital Era (ENCODE) Worlding Northern Art LAMCOM – Libraries, archives, and museums in the community His scholarly output includes both traditional academic publications and creative works, reflecting his position at the intersection of artistic practice and academic research. His contact information is available through the university directory at gaute.barlindhaug@uit.no.
Pouria Akbarighatar is a PhD Research Fellow in Responsible Data Science at the Department of Information Systems , University of Agder, Norway, and a visiting PhD researcher at the Centre for Information Resilience (CIRES) , University of Queensland Business School. He holds a BSc in Industrial Engineering and an MSc in Information Systems from the University of Tehran. His research focuses on Responsible AI , including maturity models , fairness frameworks , and ethical implementation in sociotechnical systems. His work combines Fuzzy mathematics , decision science , and data science to address uncertainty and complexity in AI systems. Recent publications explore responsible AI principles in practitioner contexts, operationalizing AI ethics , and credibility assessment in online reviews . He contributes to journals like AI and Ethics , IEEE Access , and Expert Systems with Applications , alongside conferences such as ECIS , AMCIS , and PACIS . He teaches courses in Data Science Applications , Algorithmic and Data Structures , and Data Science Applications II . He is affiliated with the Human-Centered AI (HCAI) research group.
Runar Hilleren Lie is a Postdoctoral Research Fellow at the Department of Public and International Law, Faculty of Law, University of Oslo. He is actively engaged in interdisciplinary research at the intersection of law, technology, and international relations, contributing to major projects such as COPIID, NoRDASIL, and CLEANUP. His research interests span International Investment Law , Computational Legal Studies , International Economic Law , Energy Law , and Legal Technology . He employs data-driven and computational methodologies to analyze legal texts, arbitrator behavior, treaty development, and institutional dynamics in international dispute settlement. The most recent publications reveal a strong trend toward empirical and computational analysis of international investment law, particularly focusing on influence networks, authorship prediction, compliance politics, and the evolving role of legal actors in arbitration. His work bridges traditional legal scholarship with cutting-edge data science techniques. He teaches JUS5080 – Programming for Lawyers and JUS5671 – Legal Technology: Artificial Intelligence and Law , reflecting his commitment to integrating technological literacy into legal education. Email: r.h.lie@jus.uio.no, rhlie@jus.uio.no Phone: +47 22859431 Visiting Address: Domus Juridica, 7th floor, Kristian Augusts gate 17, 0164 Oslo Postal Address: Postboks 6706 St. Olavs plass, 0130 Oslo He is affiliated with the Law and Technology (JOT) research group and the Research Group on International Law . His current research projects include: COPIID : Compliance Politics and International Investment Disputes NoRDASIL : Advancing Data Science in Migration Law (NORDFORSK) CLEANUP : Machine Learning for the Anonymisation of Unstructured Personal Data (Research Council of Norway, 2020–2023)
Roar Bakken Stovner is an Associate Professor at the Department of Primary and Secondary Teacher Education within the Faculty of Education and International Studies at Oslo Metropolitan University (OsloMet), where he also serves as Head of Studies - Area of Responsibility 2. His academic career at OsloMet began as an Assistant Professor (2021-2023) before his promotion to Associate Professor in 2023. Prior to his university position, he worked as a teacher in lower and upper secondary schools in Oslo (2012-2018) and completed his PhD at the University of Oslo (2016-2020). He holds a Master of Science and Technology from NTNU (2007-2012) with a thesis on applied computational topology. Stovner's research spans several interconnected domains within educational science: Developing methodologies for describing and measuring teaching quality across multiple classrooms, with special emphasis on mathematics education Metascience research examining how citation practices distort findings and confer unwarranted authority to claims in educational research Creating programming tools for educational research, including the gptworkr package for text analysis in R using ChatGPT His scholarly work focuses on classroom research, mathematics education, mathematical competencies, metascience, and citation analysis. He actively participates in research groups focused on Classroom Research and Task Design in Mathematics Education, and leads significant involvement in the Teacher Education Panel Study (TEPS), a comprehensive longitudinal study examining teacher education implementation in Norway. Stovner's recent publications demonstrate substantial engagement with contemporary issues in educational research methodology, AI applications in education, and critical examination of scientific practices. His work on the EDUCATE project has produced influential reports on algorithmic thinking in mathematics education across different grade levels and exploratory teaching approaches in upper secondary education. His contributions to educational discourse include conference presentations, book chapters, and practical resources for teacher education, such as "Bedre masterskriving – en bok for lærerstudenter" (Better Master's Writing - A Book for Teacher Students), which supports academic writing development among future educators.
Anders Nes is a Professor in the Department of Philosophy and Religious Studies at NTNU in Trondheim. His research focuses on philosophy of mind, perception, language, and action, with notable contributions to debates on the perception-cognition distinction and the nature of conscious inference. He has held previous affiliations including Researcher at the Center for the Study of Mind in Nature (CSMN) in Oslo, and fellowships at Oxford University's Christ Church and Balliol Colleges. Nes actively participates in academic dissemination, including panel discussions on AI ethics and digitalization. He organizes the Trondheim Philosophy of Perception Circle and teaches advanced perception seminars. His work bridges analytic philosophy with cognitive science, emphasizing phenomenological and epistemological dimensions of mental processes. Research interests include philosophical aspects of artificial intelligence, non-conceptual content in utterance comprehension, and the phenomenology of thinking. Key themes in his writing address intentional processes, modular stimulus-control in perception, and the role of consciousness in inferential reasoning. Nes' recent articles explore reasons-responsive embodied processes and the epistemic roles of perception versus cognition.
Rune Johan Krumsvik is a Professor of Education at the University of Bergen (UiB) and Professor II at Volda University College. He founded the Digital Learning Communities (DLC) research group (2007) and the Western Norway Graduate School of Educational Research II (WNGER II). His affiliations include editorial roles at the Nordic Journal of Digital Literacy (Editor-in-Chief) and Frontiers in Pediatrics (Associate Editor). Professor, Department of Education, UiB (2010–) Professor II, Volda University College (2003–) Honorary Research Fellow, University of Bristol His research spans artificial intelligence , doctoral education , ICT in schools , formative assessment , and classroom management in technology-dense environments. He explores connections between AI, social media, mental health, and digital competence, with recent work focusing on large language models (LLMs) in education and healthcare. Scientific publications show a focus on AI applications ( 76 peer-reviewed articles , h-index 31). Key trends include: EdTech implementation in Norwegian primary/secondary schools AI in formative/summative assessment Digital competence frameworks Classroom technology management Teacher education digital skills Mental health impacts of screen time Scientific awards: Teaching Award , UiB Faculty of Psychology (2012) Excellent Teaching Practitioner accreditation (2020) Supervision includes: Main supervisor for 12 PhD candidates (11 completed) Co-supervisor for 6 PhD candidates Supervisor for 14 master’s and 12 bachelor’s students He leads the Digital Learning Communities Artificial Intelligence Centre (DLCAIC), focusing on AI research in education/healthcare, societal impacts of AI, and digital competence development.
Marcos Caballero serves as Associate Professor at both the University of Oslo's Center for Computing in Science Education and Michigan State University. His work bridges physics education research with computational science instruction across educational levels from high school to graduate programs. His educational background includes: B.S. in Physics from University of Texas at Austin (2004) M.S. in Physics from Georgia Institute of Technology (opto-microfluidics research) Ph.D. in Physics Education Research from Georgia Tech (2011, first PER-focused doctorate there) Postdoctoral research at University of Colorado Boulder Caballero's research investigates how computational tools and science practices shape physics learning, employing both cognitive and sociocultural theoretical frameworks. Key projects examine measurement uncertainty assessment, computational literacy development, and equity in graduate admissions. His work spans micro-level analyses of student coding comprehension to macro-level studies of computing's impact across degree programs, with significant contributions to transforming upper-division physics curricula toward active learning environments. His recent publications (2021-2024) reveal concentrated focus on measurement uncertainty assessment instruments , computational thinking frameworks , and holistic graduate admissions reform . These works demonstrate increasing methodological sophistication through NLP applications and large-scale educational data analysis, while maintaining practical relevance for physics classroom transformation. Caballero co-founded Georgia Tech's Physics Education Research group and currently leads UiO's Center for Computing in Science Education and Michigan State's Physics Education Research Lab . His international partnership for computing in science education drives cross-institutional curriculum development, focusing particularly on integrating computational practices into core physics instruction while addressing equity challenges in STEM education.
Ove Edvard Hatlevik is a Professor at the Faculty of Education and International Studies , Department of Primary and Secondary Teacher Education at Oslo Metropolitan University. His research focuses on Teacher Professional Digital Competence , ICT integration in education , Psychometrics , and Critical Health Literacy . He leads the Teacher Education for a Future in Flux (TEFF Academy) and Teacher Education Panel Study (TEPS) projects, while previously managing initiatives such as Developing ICT in Teacher Education (DiCTE) and Literacies for Health and Life Skills . Email : ove-edvard.hatlevik@oslomet.no Office : Pilestredet 42, Oslo (Q6007) His recent publications explore: AI applications in thesis categorization (2025) Gender differences in early childhood education outcomes (2025) Job satisfaction dynamics in teaching (2024) Digital distraction management in teacher training (2024) Professional digital competence in technology-rich classrooms (2024) Systematic reviews on digital competence dimensions (2023) Key thematic areas include: Algorithmic thinking in mathematics education Long-term impacts of ECEC quality Digital divide in adult education Assessment of critical health literacy ICT access barriers in education centers Psychometric properties of educational tools
