Find Academic Supervisors

• Digital Journalism
• Fact-checking
• Media Platforms
• +7 more

Oscar Westlund serves as Professor at the Department of Journalism and Media Studies within the Faculty of Social Sciences at Oslo Metropolitan University (OsloMet), where he co-leads the OsloMet Digital Journalism Research Group. He maintains a secondary appointment at the University of Gothenburg and acts as Editor-in-Chief of Digital Journalism . His research spans digital journalism, fact-checking, platform dynamics, media management, news consumption, and mobile media. Westlund's scholarly focus centers on journalism safety in digital environments, sociotechnical dimensions of misinformation combat, and platform-induced challenges for news organizations. His work examines professional fragilities of journalists, epistemological foundations of data journalism, and legitimacy paradoxes in public service media-platform relationships. Current projects address disinformation countermeasures through the SCAM initiative (Source Criticism And Mediated Disinformation). Analysis of his 2022-2024 publications reveals dominant themes: journalism safety frameworks (33%), platform-journalism tensions (27%), and fact-checking as sociotechnical practice (23%). Key methodological approaches include cross-national comparative studies, epistemological analysis, and practice theory applied to digital news production. Westlund actively contributes to academic discourse through editorial leadership at Digital Journalism and special issue guest editing. His research group coordinates interdisciplinary collaboration on digital journalism studies, while the SCAM project develops practical methodologies for disinformation detection in democratic contexts. Recent work demonstrates increasing emphasis on mobile news ecosystems and journalist safety cultures. He co-leads the OsloMet Digital Journalism Research Group, which investigates platform impacts on news production, mobile journalism evolution, and epistemological shifts in data-driven reporting. The group maintains strong international partnerships, particularly with Swedish institutions through his University of Gothenburg affiliation.

• Machine Learning
• Deep Learning
• Neural Networks
• +7 more

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.

• Documentation Studies
• Document Theory
• Paratext
• +12 more

Roswitha Skare is a Professor of Documentation Science at the Department of Language and Culture, UiT The Arctic University of Norway, within the Faculty of Humanities, Social Sciences and Teacher Education. She is actively engaged in research and teaching, focusing on documentation studies, public libraries, archives, museums (LAM sector), digitalization, and film history. Her research interests include: Documentation and document theory Paratext and digital documents Public libraries and their role in society Libraries and social media Migration and refugee services in libraries Film history, especially silent films and early documentaries Cultural memory and Sámi cultural resilience Institutional convergence in cultural policy Her recent publications (2019–2025) reveal a strong focus on public libraries during and after the Covid-19 pandemic, the role of libraries in supporting immigrants and refugees, theoretical developments in document studies, and historical film analysis—particularly Robert Flaherty’s Nanook of the North . She frequently collaborates with scholars such as Andreas Vårheim, Noah Lenstra, and Sigrid Stokstad. Her work appears in journals like Journal of Documentation , Library & Information Science Research , and Proceedings from the Document Academy . Roswitha Skare teaches courses such as: MDV-1001: Multimediale dokumenter: Historie, teori og analyse MDV-1203: Bibliotek og formidling MDV-1207: Dokumentinstitusjoner og digitalisering MDV-1206: Prosjektoppgave i bibliotek- og dokumentasjonsvitenskap She supervises bachelor’s, project, and master’s students in library and documentation science. She is a member of the research group Engaging Conflicts in a Digital Era (ENCODE) and participates in projects such as LAMCOM – Libraries, archives, and museums in the community and SAMCOM - Sámi cultural centers as community and cultural resilience infrastructure , which explore the societal roles of cultural institutions and Indigenous resilience. No scientific awards are listed in the provided text.

• Computer Vision
• Machine Learning
• Deep Learning
• +7 more

Habib Ullah is an Associate Professor in Data Science at the Norwegian University of Life Sciences (NMBU), Norway, where he conducts research at the intersection of computer vision and machine learning. He is affiliated with the Institute of Data Science under the Faculty of Science and Technology. He has previously held academic positions at COMSATS University Islamabad, Pakistan, and the University of Ha'il, Saudi Arabia, and served as a postdoctoral researcher at The Arctic University of Norway. Educational Background: PhD in Information and Communication Technology (Computer Vision), University of Trento, Italy (2011–2015) MSc in Electronics and Computer Engineering, Hanyang University, South Korea (2007–2009) BSc in Computer Systems Engineering, NWFP University of Engineering and Technology, Pakistan (2002–2006) Habib Ullah's research is primarily focused on computer vision and machine learning, with applications in aquaculture, agriculture, and human behavior analysis. He investigates underwater fish feeding sounds using audio classification, develops zero-shot learning models for recognizing unseen classes, and applies deep learning to detect stress in salmon via skin dot patterns. He also explores AI-driven controlled environment agriculture, leveraging sensors and automation for optimal crop growth. His work emphasizes practical AI solutions for real-world challenges in environmental and biological domains. The recent publications highlight a strong trend in leveraging deep learning for zero-shot and semi-supervised learning, particularly in computer vision tasks such as sea ice classification, crowd anomaly detection, and agricultural monitoring. His research spans remote sensing, biomedical signal processing, and human activity recognition, demonstrating interdisciplinary versatility. The keywords reflect a focus on robust feature representation, knowledge transfer, and model generalization. Scientific Awards and Funding: Industrial PhD grant 'Advancing Controlled Environment Agriculture AI' from The Research Council of Norway (Project number 354125, 2 million NOK, 2024) Team member (Coordinator-Participant) in the Battery Cell Assembly Twin (BatCAT) project funded by Horizon Europe (7 mEuro, 2023–2027) Development of an AI-Based Image Analysis System for Monitoring Plant Status (Funding: 1.8 mNOK, starting 2025) Habib Ullah actively supervises PhD projects and contributes to academic service through editorial and organizational roles. He has served as an Associate Editor for IEEE Access, Guest Editor for MDPI Remote Sensing, and Editor of the Springer book Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition, and Support (ML-SHEARS) . He has also been a Track Chair and Program Committee Member for several international conferences, reflecting his leadership in the academic community. His research is supported by significant grants and collaborative projects, indicating strong institutional and international engagement. He is involved in multiple research teams and projects, including the BatCAT project on battery manufacturing and AI applications in controlled environment agriculture with RIFT LABS AS. His lab work integrates deep learning, sensor fusion, and data analytics for environmental and biological monitoring systems.

• Artificial Intelligence
• Machine Learning
• AI Alignment
• +2 more

Michael Riegler is a Researcher at the AI Department, Simula Research Laboratory , focusing on interdisciplinary applications of Artificial Intelligence in healthcare, sports analytics, and multimedia systems. His work bridges Machine Learning , AI Alignment , and Applied AI across clinical and real-world domains. Key Affiliations: Simula Research Laboratory (AI Department Head) Research Themes: Explainable AI in medicine, multimodal data analysis, and AI-driven health monitoring Research Interests include: Developing AI/ML algorithms for medical imaging (e.g., polyp detection, embryo analysis) Addressing missing data challenges in healthcare through novel imputation techniques Creating multimodal virtual avatars for investigative interview training Designing edge AI systems for sports analytics and sustainable fishing Recent Publications highlight collaborations with institutions in Norway and globally, with a focus on: Medical Applications: Polyp segmentation, ECG analysis, and explainable models for disease detection Sports Analytics: Athlete performance prediction and soccer video processing Data Infrastructure: Lifelogging datasets (ScopeSense), semantic representation frameworks Labs & Teams include leadership in Simula’s AI Department and participation in projects like Medico Multimedia Task , ImageCLEF , and MediaEval workshops. His work emphasizes responsible AI innovation in public sectors and privacy-preserving systems for edge environments.

Anne H Schistad SolbergView profile

Professor

• Machine Learning
• Deep Learning
• Image Analysis
• +6 more

Anne H Schistad Solberg is a Professor in the Department of Informatics at the University of Oslo's Faculty of Mathematics and Natural Sciences. She leads research in digital signal processing and image analysis, with a focus on machine learning applications across multiple domains. As co-director of SFI Visual Intelligence, she oversees research on interpretable deep learning models, uncertainty quantification, contextual learning, and self-supervised learning approaches. Her research spans medical imaging (particularly cardiovascular ultrasound), environmental monitoring using satellite imagery, and seabed mapping with sonar technology. Professor Solberg's work demonstrates a consistent trajectory from foundational signal processing techniques to cutting-edge deep learning applications. Her recent publications show increasing specialization in medical image analysis, particularly in echocardiography enhancement and cardiac structure segmentation, while maintaining strong contributions to remote sensing and geophysical applications. She teaches several popular courses including IN2070, IN3310, and IN5400 (Machine Learning for Image Analysis), which is noted as the most popular master's/PhD course on deep learning at the University of Oslo. Professor Solberg serves as principal investigator for the Intelligent Cardiovascular Ultrasound Scanner (INCUS) project, collaborating with GE Vingmed Ultrasound to develop AI-enhanced cardiac imaging systems that improve diagnostic accuracy and productivity in echocardiography. Co-director of SFI Visual Intelligence research center Principal Investigator for the INCUS project (Intelligent Cardiovascular Ultrasound Scanner) Member of the Digital Signal Processing and Image Analysis (DSB) research group Member of the Strategic Research Initiative: Multimodal Medical Imaging and Image Analysis (MEDIMA) Her research group develops algorithms that address real-world challenges in medical diagnostics and environmental monitoring, with a particular emphasis on making deep learning models more interpretable and reliable for critical applications. The INCUS project, funded through User-driven Research-based Innovation (BIA), aims to reduce the time wasted during cardiac ultrasound examinations by implementing intelligent algorithms that learn from expert users and historical data.

• Biomechanics
• Human Kinetics
• Biomedical Engineering
• +3 more

Dr. Ryan B Graham is an Associate Professor in the School of Human Kinetics at the University of Ottawa , with cross-appointments to the Ottawa-Carleton Institute for Biomedical Engineering . He holds Adjunct Assistant Professor positions at Queen's University and University of Waterloo , reflecting his interdisciplinary collaborations in biomechanics and biomedical engineering. His research focuses on spine movement analysis , motion capture validation , and sensor technology applications in clinical and military contexts. Recent work includes developing markerless motion capture systems, assessing movement reliability, and modeling spine dynamics for injury prevention. Editorial Contributions: Associate Editor for Biomechanics and Control of Human Movement at Frontiers in Sports and Active Living Dr. Graham's academic network includes collaborations with institutions in Canada, the UK, and the Netherlands, with a focus on advancing biomechanical methodologies and their clinical translation.

• Combustion Engineering
• Alternative Fuels
• Hydrogen Energy
• +5 more

Terese Løvås serves as Vice Dean of Research and Innovation at the Faculty of Engineering, Norwegian University of Science and Technology (NTNU), where she leads strategic development of research and innovation activities. She concurrently holds the position of Professor of Combustion and Thermodynamics within the Department of Energy and Process Engineering. Her leadership responsibilities include oversight of Centers of Excellence, Horizon Europe projects, and PhD researcher training. Her research focuses on combustion engineering and alternative fuel technologies , particularly investigating ammonia and hydrogen combustion for zero-emission engines, biomass gasification processes, and reactive multiphase flow modeling. She heads the Engine Lab at NTNU and teaches Thermodynamics, Heat, and Combustion courses. Her work bridges theoretical modeling with experimental validation in sustainable energy systems. Løvås actively contributes to major research initiatives including LowEmission (SFI center), ACTIVATE (ammonia-powered agricultural vehicles), AMAZE (ammonia zero-emission), and CAHEMA (marine ammonia/hydrogen engines). Her publications reveal strong trends in ammonia combustion chemistry , emissions reduction , and advanced computational modeling for sustainable fuel systems, with increasing focus on nitrogen oxide formation mechanisms and dual-fuel strategies. Member of the Board of Directors, Combustion Institute (2022–present) Joint Editor, Proceedings of the Combustion Institute (2019–present) Alumni Fellow in Engineering, Churchill College, Cambridge University As Vice Dean, she manages NTNU's Research and Innovation Committee and represents the faculty in NTNU's Research and Innovation Committee. She supervises multiple PhD candidates and leads international collaborations through projects funded by the Norwegian Research Council, Nordic Energy Research, and EU programs. Her laboratory work focuses on optical engine diagnostics and advanced combustion testing. Løvås maintains active industry engagement through her leadership in the ComKin Research Group and membership in the Institute of Physics and Scandinavian-Nordic Section of the Combustion Institute. Her current work emphasizes practical implementation of ammonia-fueled engine technologies for marine and agricultural applications.

Gabriele de SetaView profile

Researcher

• Digital ethnography
• Chinese internet culture
• Algorithmic folklore
• +4 more

Gabriele de Seta is a researcher at the University of Bergen's Department of Linguistic, Literary and Aesthetic Studies, leading the ALGOFOLK project funded by the Trond Mohn Foundation (2024-2028). A sociologist by training with a PhD from Hong Kong Polytechnic University, he previously served as postdoctoral fellow at Academia Sinica (Taipei) and on the ERC-funded Machine Vision in Everyday Life project. Department of Ethnology, Academia Sinica (postdoctoral fellow) Department of Linguistic, Literary and Aesthetic Studies, University of Bergen (researcher) His research focuses on algorithmic folklore, synthetic ethnography, and Chinese digital culture. He examines how digital technologies and creative practices mutually shape each other, particularly in China's sociotechnical landscape. Key areas include platform governance, machine vision, algorithmic accountability, and digital vernaculars. Recent publications analyze TikTok/Douyin's infrastructural role, deepfakes, QR codes as globalized gateways, and Chinese internet vulgarity. His work combines theoretical frameworks from STS, media studies, and digital anthropology with fieldwork on Chinese digital practices. Trond Mohn Foundation Starting Grant ERC-funded research As educator, he designed the Machine Vision module for Bergen's Critical Approaches to Technology and Society course and taught Key Theories in Digital Culture. He supervises multiple MA/PhD students including co-supervision of Hanna Lauvli. Through his blog and podcast, he promotes public engagement with digital research.

Thomas Michael SattichView profile

Associate Professor

• Geopolitics
• Sustainability Transition
• Energy Policy
• +4 more

Thomas Michael Sattich is an Associate Professor at the University of Stavanger , affiliated with the Faculty of Social Sciences and Department of Media and Social Studies . His research focuses on geopolitical implications of sustainability transitions, particularly energy policy interdependence and EU-China relations. PhD in Political Science and Economics Expertise in qualitative methods, mixed methods (cluster analysis), and data visualization Lead researcher on EU-funded digital climate negotiation simulation projects His recent publications examine renewable energy geopolitics, industrial policy competition, and sustainability education frameworks. Methodologically, he specializes in Qualitative Comparative Analysis (QCA) and network analysis, contributing to debates on energy security and regional cooperation.

Jørgen BakkeView profile

Associate Professor

• Art History
• Classical Archaeology
• Byzantine Studies
• +4 more

Jørgen Bakke is an Associate Professor in History of Art at the Department of Linguistic, Literary and Aesthetic Studies, University of Bergen. His academic work spans classical archaeology, Byzantine studies, and visual culture with a particular focus on ancient Greek art, landscape archaeology, and the cultural history of the Mediterranean region. Bakke has been actively involved in archaeological research in Greece, particularly in the Tegea region of Arcadia. His research interests encompass a broad range of topics in art history and classical studies. Bakke specializes in visual culture of ancient Greece, Byzantine garden traditions, landscape archaeology, and the intersection of art with memory and knowledge representation. His work often bridges disciplines, connecting classical literature with visual analysis and exploring how ancient visual culture functioned within historical and religious contexts. Bakke's research demonstrates particular expertise in the interpretation of ancient texts related to art (ekphrasis), the visual poetics of ancient Greek culture, and the reception of classical themes in later periods. Bakke's scholarly output reveals a consistent focus on Mediterranean cultural landscapes, particularly examining the Tegea region through multiple historical periods from classical antiquity through the Byzantine era and into the Ottoman period. His work shows a progression from early studies on ancient Greek visual culture toward more specialized research on Byzantine visual traditions and garden culture. A notable thread throughout his publications is the examination of how visual culture functions within religious and devotional contexts across different historical periods. His recent work increasingly engages with digital humanities approaches to art historical analysis. Bakke is actively involved in multiple research groups at the University of Bergen, including the Images of Knowledge Research Group, the Antiquity and the Classical Tradition Research Group, and the Literature & Religion Research Group. These affiliations reflect the interdisciplinary nature of his work, which bridges art history, classical studies, religious studies, and literary analysis. His research demonstrates how visual culture serves as a critical lens for understanding historical, religious, and philosophical developments across different eras.

Behzad AlaeiView profile

Associate Professor

• Structural Geology
• Sedimentary Basin Analysis
• Fault Zone Architecture
• +6 more

Behzad Alaei serves as an Associate Professor in the Section for Study of Sedimentary Basins within the Department of Geosciences at the University of Oslo's Faculty of Mathematics and Natural Sciences. His office is located in room K38 of the Geology Building at Sem Sælands vei 1, 0371 Oslo, with a professional email contact at behzad.alaei@geo.uio.no. Dr. Alaei maintains an active research profile with publications spanning from 2005 to the present, demonstrating his ongoing contributions to geological sciences. Dr. Alaei's research spans multiple critical areas within structural geology and sedimentary basin analysis, with particular expertise in fault zone architecture, seismic interpretation techniques, and CO2 storage site assessment. His work bridges theoretical geological concepts with practical applications in petroleum geology and carbon sequestration. A significant portion of his research focuses on the Norwegian Barents Sea region, where he has conducted extensive studies on normal fault systems and their geometric characteristics. His recent work increasingly integrates machine learning and deep learning approaches with traditional geological analysis, reflecting the evolving nature of geoscience research methodology. The analysis of Dr. Alaei's publication record from 2018-2024 reveals a strong thematic continuity in fault characterization research, with progressive incorporation of advanced computational methods. Early publications focused primarily on traditional structural analysis of fault systems in sedimentary basins, while more recent work demonstrates increasing integration of machine learning techniques for fault detection and characterization. A notable trend is the application of these geological insights to practical challenges in carbon capture and storage, particularly regarding fault risk assessment for CO2 storage sites in the North Sea region. His collaborative work with Anita Torabi appears consistently throughout this period, suggesting a strong research partnership. Dr. Alaei maintains an active research program with multiple ongoing projects related to sedimentary basin analysis and fault characterization. His work appears to involve significant collaboration with both academic and industry partners, particularly in the context of CO2 storage research. While specific grant details aren't provided in the available information, his consistent publication record across multiple high-impact journals suggests successful funding of his research activities over the past two decades.

• Sociology
• Consumer Behavior
• Food Culture
• +5 more

Annechen Bahr Bugge is a sociologist and Researcher I at Consumption Research Norway (SIFO), Oslo Metropolitan University. Her work focuses on food culture, culinary heritage, and sustainable consumption patterns, with particular emphasis on Norwegian dietary traditions and their evolution from the 16th century to present day. PhD in Sociology (2005) from Norwegian University of Science and Technology (NTNU) Current leader of FoodStories project (2025-2028) examining Norwegian food heritage Previously led FoodLessons project (2021-2024) connecting culinary history with future food development Her research explores: dietary transitions, plant-based diets, food policy interventions, and the sociocultural dimensions of food consumption. She has published extensively on Norwegian food culture, including the book Fattigmenn, tilslørte bondepiker og rike riddere (2019) and upcoming Food Cultures of Norway: Cuisines, Customs, and Issues (2025, co-authored with Henry Notaker). Recent publications focus on: food heritage revitalization, sustainable diets, retail interventions for healthier choices, and digital marketing influences on youth consumption patterns. Her work combines historical analysis with contemporary food challenges to inform future sustainable food systems. For a complete overview of her research and publications, see her Cristin profile: Cristin Profile

Ali Ramezani-KebryaView profile

Associate Professor

• Machine Learning
• Deep Learning
• Federated Learning
• +9 more

Ali Ramezani-Kebrya is an Associate Professor with tenure in the Department of Informatics at the University of Oslo (UiO), where he leads research in machine learning theory. He holds dual Principal Investigator roles at the Norwegian Center for Knowledge-driven Machine Learning (Integreat) and SFI Visual Intelligence, and is an active member of the European Laboratory for Learning and Intelligent Systems (ELLIS) Society. His service includes Area Chair positions for NeurIPS and AISTATS, and Action Editor for Transactions on Machine Learning Research. His research focuses on theoretical foundations of deep learning with emphasis on understanding input data distribution encoding in neural network layers. Key themes include minimizing statistical risk under resource constraints, addressing distribution shifts in distributed settings, and developing practical tools for robust federated learning. Current applications span emotion recognition, marine data analysis, and neuroscience, reflecting his commitment to real-world machine learning challenges as evidenced by his FRIPRO-funded Machine Learning in Real World (MLReal) project. Recent publication trends reveal three dominant threads: (1) label/covariate shift mitigation in distributed systems through entropy regularization and density ratio estimation; (2) communication-efficient optimization via layer-wise quantization and adaptive compression techniques achieving 150% speedups; and (3) robustness guarantees against tailored attacks and distribution shifts. These works consistently bridge theoretical bounds with empirical validation across domains from GAN training to federated settings. Scientific recognition includes: FRIPRO Grant for Early Career Scientists (2025) for MLReal project SFI Visual Intelligence Spotlight Publication award (2023) for federated learning work He actively mentors 11 graduate students across Oslo and Tromsø universities, with recent PhD placements at Apple and NVIDIA. Current grant portfolio features the FRIPRO Early Career award and leadership roles in two major Norwegian research centers. His lab maintains strong industry collaborations through Vector Institute and EPFL, with recent hiring for PhD and postdoc positions in physics-informed machine learning.

Michael RauhutView profile

Professor

• Popular Music Studies
• Musicology
• Sociology of Music
• +7 more

Michael Rauhut is a Professor at the University of Agder where he leads the PhD specialization in popular music performance and represents subject teachers within scientific disciplines at the Department of Rhythmic Music . His academic work focuses on popular music studies and musicology, with supervisory responsibilities for master's and doctoral candidates. Rauhut's research explores the intersection of music, politics, and society, with particular emphasis on: Popular music history in socialist contexts (especially the GDR) Cultural transfer during the Cold War Blues, rock, and jazz as forms of cultural expression Youth cultures and music under authoritarian systems Church-state dynamics in musical expression His work demonstrates how music functioned as both state propaganda and vehicle for dissent. Analysis of Rauhut's publications reveals consistent focus on: Cultural mechanisms in socialist states (75% of recent works) Transnational music exchanges across the Iron Curtain Archival methodologies for reconstructing musical histories Identity formation through popular music State censorship and artistic resistance strategies His documentary filmography expands these themes into visual media. As PhD supervisor, Rauhut guides research in popular music performance and musicology. His extensive conference participation includes keynote addresses in Germany, USA, Georgia, and Ukraine, covering topics from blues reception to music's role in political revolutions.