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.
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.
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.
Geir Inge Hausvik is an Associate Professor at the Department of Information Systems, University of Agder. His research focuses on digital transformation in healthcare, information quality management, and e-health services. He is affiliated with the CeDiT (Centre for Digital Transformation) and Centre for e-health research groups. Key areas of expertise include healthcare service innovation, socio-technical systems design, and the practical impact of information systems research. Research Interests: His work addresses challenges in healthcare digitalization, including online screening tools, post-COVID service innovation, and smartphone adoption among older adults. He explores theoretical frameworks such as boundary spanning and Bourdieusian analysis to understand practical impacts of research. Recent studies examine AI ethics in academic writing and mediating roles in healthcare quality assurance. Publications: Over 15 peer-reviewed articles since 2015, including studies on EHR affordances (2017), information quality lifecycle (2021), and post-pandemic digital service acceleration (2025). He co-edited conference proceedings for DESRIST 2021 and contributed to influential journals like Information Systems Journal. Affiliations: Leads academic programs in Information Systems, including B.Sc. and M.Sc. courses. Active in international conferences (e.g., Hawaii International Conference on System Sciences, AMCIS). Engaged in collaborative research initiatives like the Centre for Digital Transformation. Key Contributions: Advocates for sociotechnical systems resilience beyond crisis response, investigates smartphone usage disparities among seniors, and evaluates generative AI's implications for academic integrity.
Bjørnar Tessem is a Professor at the Department of Information and Media Studies, University of Bergen. His research focuses on artificial intelligence (AI) and machine learning applications in journalism and sustainable resource management, particularly fisheries. He leads projects like MediaFutures and collaborates with researchers on anomaly detection in fisheries data and ethical AI in automated journalism systems. His work bridges computational methods with societal challenges, emphasizing fairness, transparency, and sustainability. Research interests include AI-driven journalism frameworks, knowledge graphs for news angles, sustainable fisheries monitoring via machine learning, and ethical implications of AI in media. Key projects involve developing tools for detecting violations in fishing activities and enhancing news production through automated systems. He also contributes to public understanding through popular science articles on technology and AI. Recent articles highlight advancements in collective anomaly detection for fisheries surveillance, future technologies in journalism, and fairness in automated data journalism systems. Tessem’s research is supported by grants from the Research Council of Norway and has implications for both academic and industry applications in media and environmental sectors.
Tor-Morten Grønli serves as Professor at the Department of Technology, School of Economics, Innovation and Technology, Kristiania University College (Norway). He is also a Visiting Research Scholar at Copenhagen Business School's Department of Information Technology Management and an affiliate of the Center of Business Data Analytics (cbsDBA). Education PhD in Computer Science from Brunel University, London (2011) Master of Technology (with distinction) from Brunel University, London (2007) Research Focus Grønli leads research in context-aware systems, mobile/pervasive computing, and Internet of Things (IoT). He founded/directs the Mobile Technology Lab at Kristiania and has co-authored 70+ publications. Core expertise includes: IoT architecture and applications Machine learning for transport systems Mobile computing frameworks Blockchain-security integration Edge-cloud computing paradigms Publication Trends Recent works (2023-2025) demonstrate strong focus on converging IoT, blockchain, and AI technologies, particularly for intelligent transport and healthcare systems. Dominant themes include federated learning implementations, privacy-preserving architectures, and sustainable edge computing solutions, with increasing emphasis on real-world applications in medical diagnostics and public infrastructure. Professional Activities Founder/Director of Mobile Technology Lab General Chair: Norwegian Conference on ICT Co-organizer: International Conference on Mobile Web Editorial Board: International Journal of Pervasive Computing, Journal of Online Information Review, Computers & Electrical Engineering TPC Member for IEEE BigData, Percom, HICSS, COMPSAC Guest Editor for special issues in Future Generation Computer Systems
Dilip K. Prasad is a Professor at the Department of Informatics, UiT The Arctic University of Norway. His work bridges Artificial Intelligence and Medical Imaging , with a focus on Interpretable AI , Scalable AI , and Life Science Applications . He has contributed to Maritime Technology and Biomedical Engineering . Ph.D. and B.Tech from Nanyang Technological University and IIT Dhanbad Senior Research Fellow at NTU (2015-2019), Research Fellow at NUS (2012-2015) Industry experience at IBM, Infosys, Mediatek, Philips His research explores Image Processing , Machine Learning , and AI Applications in Biomedicine . Recent work includes Dense Video Captioning , 3D Mitochondrial Modeling , and Physics-Guided Loss Functions . Articles span Neurocomputing , Optics Express , and top AI conferences like CVPR and NeurIPS . Prasad has received the Rolls-Royce Inventor Award (2016) and Best Paper Award (IJCIE 2017) . He has reviewed for 50+ journals and 30+ conferences, serving as Area Chair for NeurIPS 2022-23 and Organizer Chair for ICCV Workshop 2023 .
Siri Øyslebø Sørensen is a Professor and Head of the Center for Gender Research at the Norwegian University of Science and Technology (NTNU), where she is affiliated with the Department of Interdisciplinary Cultural Studies in the Faculty of Humanities. She also holds an adjunct position (professor II) at the University of Bergen, working with the GenderAct project. Her academic background spans sociology, gender studies, and technology and science studies (STS). Dr. Sørensen's research focuses on gender, power, and inequality across various domains including organizations, politics, and contemporary culture. She has conducted extensive research on gender equality and inclusion in academia, currently leading the KARMA project (2024-2026), which develops tools for qualitative mapping of diversity, funded by the Research Council of Norway. She is also involved in the BIAS project investigating how artificial intelligence in hiring processes affects inclusion and exclusion in working life. Her methodological expertise includes action research, qualitative interview studies, microphenomenology, situational analysis, and discourse and narrative analysis. Her scholarly work reveals consistent engagement with feminist theory, organizational sociology, and critical perspectives on diversity and inclusion. Through projects like "Mann ombord" with Trondheim Municipality, she explores masculinity as a social phenomenon, examining how norms of masculinity, power, and marginalization are produced. Her publications demonstrate expertise in gender equality policy, academic careers, organizational dynamics, and the intersection of technology with gender issues. Dr. Sørensen has served as editor of Tidsskrift for kjønnsforskning (2022-24) and book review editor of NORA – Nordic Journal of Feminist and Gender Research (2016-18). She has co-edited several academic anthologies including "Bodies, Symbols and Organizational Practice" (Routledge, 2018) and "Reproduction, gender and equality in modern Norway" (Fagbokforlaget, 2016), as well as a special issue of Gender Work and Organization (2021). She currently serves on the editorial board of the Journal of Organizational Sociology. She coordinates the research group for gender, equality and diversity at NTNU and is actively engaged in developing practical tools for improving gender balance in academic institutions. Her commitment to translating research into practice is further demonstrated through her ongoing collaboration with Trondheim Municipality and local health and welfare services on initiatives to prevent exclusion among young men.
Tor Ole Bigton Odden is an Associate Professor at the Center for Computing in Science Education (CCSE) , University of Oslo, specializing in physics education research. His work bridges physics, computation, and educational theory to enhance student learning. Current roles: Research, teaching, and mentorship at CCSE Research focus: Computational literacy, epistemic agency, and AI in science education Education PhD in Physics Education, University of Wisconsin-Madison MSc in Physics, University of Wisconsin-Madison BSc in Physics, St. Olaf College Research Interests Tor Ole develops computational tools to empower students in physics learning. His research explores: Programming and creative ownership in physics Machine learning for large-scale qualitative analysis Epistemic agency and sensemaking Training teaching assistants Article Trends His publications emphasize computational essays, AI applications, and sensemaking frameworks. Key subfields include computational literacy, NLP in educational analysis, and simulation-based learning. Labs & Projects He contributes to the IMPEL project (Interactive Engagement in Physics) and collaborates with the Section for Physics Didactics at the University of Oslo.
Eric Bartley Jul is a Professor in the Department of Informatics at the University of Oslo, specializing in Programming Technology within the Faculty of Mathematics and Natural Sciences. His research spans multiple domains of computer science with a focus on practical applications in medical imaging, distributed systems, and mobile computing. Professor Jul's research interests encompass a broad spectrum of computer science disciplines. His expertise lies particularly in Object-Oriented Programming, Distributed Computing, and Design Patterns, with expanding work in Cloud Computing and Security. His recent publications demonstrate a significant shift toward applying computer vision and deep learning techniques to medical diagnostics and healthcare applications, particularly in microcirculation analysis and reproductive medicine. This interdisciplinary approach bridges traditional computer science with cutting-edge medical research. His recent publication record shows a strong trend toward medical applications of computer vision and mobile sensor technologies. The 2024 papers reveal sophisticated applications of AI in reproductive medicine (sperm detection) and transportation monitoring (flight detection), while the 2022 publications establish his foundational work in medical imaging systems like CapillaryNet for blood flow analysis. This trajectory demonstrates a consistent focus on applying programming technology to solve complex real-world problems, particularly at the intersection of computing and healthcare. Professor Jul leads research within the Programming Technology group at the University of Oslo and is involved in several significant projects including A Modern Approach to Teaching Classes at the University Level in Theoretical Computer Science , Leveraging Energy-Aware Programming (LEAP) , and Reliable models of computation for concurrent and distributed problems . His work demonstrates strong collaborative efforts with researchers across multiple institutions, particularly with Paulo Ferreira and other colleagues at the University of Oslo.
Professor Sule Yildirim Yayilgan is a distinguished academic at the Department of Information Security and Communication Technology (IIK) within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. She has held the position of Professor since 2020, following her tenure as Associate Professor from 2016-2020. Dr. Yayilgan previously served as Head of Department between 2005-2009 at HIHM (now part of NTNU). Her academic journey spans over 30 years in teaching and research, with significant contributions to interdisciplinary fields bridging AI, cybersecurity, and privacy. Her educational background includes a MSc in Computer Engineering (1995) and a PhD in Artificial Intelligence and Computer Science (2002). Dr. Yayilgan has led and participated in numerous international research projects funded by EU Horizon 2020, Eurostars, Erasmus+, and various Norwegian research councils. She currently leads the MR PET (Multidisciplinary Research group on Privacy and data protEcTion) research group and serves on the scientific board of NTNU's strategic area in Data Science. Dr. Yayilgan's research spans multiple domains with a unifying focus on ethical, legal, and privacy-preserving AI systems. Her work addresses critical challenges in health, energy, education, and security sectors through advanced AI methodologies. She has published over 100 journal and conference papers, with recent work focusing on hate speech detection, border security technology acceptance, smart grid security, and explainable AI applications. Her publications demonstrate a strong emphasis on practical implementations that balance technical innovation with societal considerations. As an active research leader, she currently oversees several significant projects including VIPA-DELF (vineyard disease detection using federated learning), METICOS (border control technology monitoring), CINELDI (intelligent electricity distribution), and AQMA (air quality monitoring). She also serves on multiple ethics boards and research integrity committees, reflecting her commitment to responsible innovation. Dr. Yayilgan has supervised numerous graduate students throughout her career, advising 41+2 (in progress) MSc students and 3+2 (periods) +6 (in progress) PhD candidates. Her administrative contributions include membership in NTNU's Research Integrity Committee, the Trondheim ACM Women Chapter, and various project management boards for EU-funded initiatives. She maintains active professional affiliations with IEEE, the International Association for Pattern Recognition, and COST Actions focused on language technologies and security research.
Tomasz Wiktorski is a Professor at the Faculty of Science and Technology , University of Stavanger , where he serves as Study Program Manager for MSc and PhD programs in Computer Science and Data Science. His research integrates conventional time series analysis with deep learning for applications in biomedical data (e.g., wearable devices), oil and gas drilling automation, energy systems prediction, and cloud infrastructure optimization. Education : Not explicitly detailed in the text. Research interests span data-intensive system modeling, focusing on: Biomedical time series analysis (wearables, ECG signal correction) Drilling process optimization via transfer learning and temporal models Energy systems prediction using machine learning Cloud infrastructure monitoring Curriculum development in data science education Scientific trends reveal expertise in recurrent neural networks, support vector machines, and hybrid data modeling for sensor networks across domains like health, petroleum, and cloud computing. Leadership includes designing data science programs and contributing to the EDISON Data Science Framework for global standards.
