جستجوی استاد راهنمای دانشگاهی

• Machine Learning
• Deep Learning
• Neural Networks
• +۷ مورد دیگر

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.

• Artificial Intelligence
• Machine Learning
• AI Alignment
• +۲ مورد دیگر

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 Solbergمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Image Analysis
• +۶ مورد دیگر

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
• +۳ مورد دیگر

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.

Trond Waageمشاهده پروفایل

استاد

• Visual Anthropology
• Migration Studies
• Conflict and Post-Conflict Societies
• +۳ مورد دیگر

Trond Waage is a Professor in the Department of Social Sciences at UiT The Arctic University of Norway , specializing in Visual Anthropology . His research focuses on migration patterns in Sub-Saharan Africa, particularly in Cameroon, the Central African Republic, and Mali, while also exploring the intersection of visual methods with ethnographic research. Active in collaborative visual research with African communities Member of the War and Peace Dynamics research group Co-founder of the Sahel on Sahel research initiative Research Interests include: Migrant integration in urban African contexts Conflict dynamics in the Sahel region Participatory visual methods for ethnographic knowledge production His recent work has examined Boko Haram's impact on youth communities and the role of collaborative filmmaking in documenting post-conflict resilience. Professor Waage frequently collaborates with researchers across institutions in Norway and Africa to explore cultural translation and visual epistemology. He serves as: Editorial contributor to the Journal of Anthropological Films Supervisor in Master of Philosophy in Visual Anthropology program Co-developer of Visual Anthropology curricula in Niger

Benjamin Ricaudمشاهده پروفایل

دانشیار

• Machine Learning
• Graph Signal Processing
• Explainable AI
• +۳ مورد دیگر

Benjamin Ricaud is an Associate Professor and Group Leader in Machine Learning at UiT The Arctic University of Norway's Department of Physics and Technology. His core affiliations include membership in the Machine Learning Group, Visual Intelligence center, and co-directorship of the Digital Technology Innovation Lab focused on Arctic-region tech startups. He also co-chairs the annual Northern Light Deep Learning conference. Ricaud's research spans: Fundamental ML : Graph signal processing, explainable AI, and generative models Applications : Microfossil classification, medical diagnostics (retinal aging), drug analysis, and climate data interpretation Emerging domains : Self-supervised learning and biological data analysis using Raman spectroscopy His recent publications (2020-2025) cluster in three domains: Graph ML methodologies (35%) Biomedical/biological applications (40%) Geoscience/climate informatics (25%) with consistent focus on interpretability and real-world data challenges. Teaching includes Image Processing (FYS-2010), Pattern Recognition (FYS-3012), and Machine Learning (FYS-2021). He leads outreach initiatives developing AI exhibits for Tromsø Science Centre.

Elisabeth Oxfeldtمشاهده پروفایل

استاد

• Nordic Literature
• Orientalism
• Postcolonialism
• +۸ مورد دیگر

Elisabeth Oxfeldt is a Professor of Scandinavian Literature at the University of Oslo's Faculty of Humanities, Department of Literature, Area Studies and European Languages. Specializing in Danish and Norwegian literature from the 19th to 21st centuries, she examines cultural narratives through postcolonial and orientalist frameworks with particular focus on guilt discourse in Nordic contexts. Her educational background includes a Ph.D. in Scandinavian Literature from U.C. Berkeley (2002), M.A. in Scandinavian Literature (1996), and B.A. in French Literature (1988). This interdisciplinary foundation informs her transnational approach to Nordic literary studies. Oxfeldt's research centers on Scandinavian narratives of guilt and privilege within globalization, exploring how Orientalism, postcolonialism, and (post)nationalism manifest in literature and visual media. Her work critically engages with Hans Christian Andersen adaptations, war literature, travelogues, and literary activism, revealing tensions between Nordic self-perception as egalitarian societies and historical complicity in colonial structures. She frequently analyzes word-image relationships and adaptation processes across media. Publication trends show sustained engagement with postcolonial critique since her 2005 monograph Nordic Orientalism , evolving toward contemporary analyses of activist voices and guilt narratives. Recent edited volumes address literary rights struggles (2024) and ecological perspectives in Nordic literature (2023), demonstrating expanding interdisciplinary scope while maintaining core focus on representation and power dynamics. Awards and honors: Member of Det Danske Akademi (The Danish Academy) Advising and grants information was not specified in source materials, though her leadership of major research projects suggests significant supervisory and funding acquisition activities. Teaching responsibilities include courses on Nordic literature after 1800, Norwegian world literature, and literary activism. Oxfeldt co-leads the DINO (Diversity in Nordic Literature) research group and previously participated in ECODISTURB. Her current projects include 'Scandinavian Narratives of Guilt and Privilege in an Age of Globalization' (ScanGuilt) and 'Norwegian Romantic Nationalisms' (NORN), examining historical and contemporary constructions of Scandinavian identity through literary lenses.

Jim Tørresenمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Biology-Inspired Computing
• +۶ مورد دیگر

Jim Tørresen is a Professor of Computer Science at the Department of Informatics, University of Oslo, where he has been employed since 1999 (Associate Professor 1999-2005, Professor since 2006). He serves as group leader for the Robotics and Intelligent Systems (ROBIN) research group and is also a Principal Investigator at the Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO). His academic career includes visiting positions at Cornell University's Creative Machines Lab (2010-2011) and Kyoto University in Japan (1993-1994). His educational background includes a Dr.ing. (Ph.D.) in Computer Architecture from the Norwegian University of Science and Technology (1996) and an M.Sc. in Computer Architecture from the same institution (1991). Before his academic career, he worked in industry at Navia Aviation (1998-1999) and NERA Telecommunications (1996-1998). Tørresen's research spans artificial intelligence, robotics, and bio-inspired computing. His work focuses on biology-inspired algorithms, programmable logic (FPGA), robotics (simulation, prototyping, control), and human-robot interaction. He has made significant contributions to areas including evolutionary computing, reconfigurable hardware, and adaptive systems. His research often bridges theoretical computer science with practical applications in healthcare, music, and industrial settings. His recent publications demonstrate a strong focus on human-robot interaction, particularly in healthcare contexts for elderly care, as well as applications in sports science, musical robotics, and geological engineering. His work shows a consistent pattern of interdisciplinary research that combines machine learning techniques with domain-specific challenges. Tørresen has also authored a popular science book on artificial intelligence in the "what is" series by Universitetsforlaget, which discusses fundamental concepts, methods, future perspectives, and ethical aspects of AI. He has been active in academic leadership, serving as General Chair for the 22nd International Conference on Field Programmable Logic and Applications (FPL) in 2012 and the 9th Joint IEEE International Conference of Developmental Learning and Epigenetic Robotics in 2019. As group leader of ROBIN, he oversees research on intelligent systems that operate in dynamic environments requiring runtime adaptation. The group works at both fundamental and applied levels, using evolutionary algorithms for robot learning and machine learning techniques for classification and recognition tasks in various application domains.

• Sports Medicine
• Cardiovascular Health
• Health Services Research
• +۷ مورد دیگر

Hilde Moseby Berge is an Associate Professor in the Department of General Practice at the University of Oslo. Her research focuses on cardiovascular health in athletes, injury and illness prevention in elite sports, and the psychological and social impacts of cardiac arrest survival among young exercisers. She has collaborated extensively with institutions like the Norwegian Olympic and Paralympic committees, contributing to longitudinal health monitoring programs for athletes. Her work includes evaluating automated external defibrillator (AED) availability in sports clubs and analyzing post-surgical outcomes for musculoskeletal injuries. Berge is also affiliated with the Clinical General Practice Research (Allmix) and General Practice Health Services Research (ALHF) groups, emphasizing her commitment to practical healthcare solutions. Key research themes include: 1) Cardiac events in sports contexts, 2) Health disparities affecting Paralympic athletes, and 3) Long-term health surveillance for Olympic/Paralympic participants. Her studies often use systematic reviews and multi-year cohort analyses, with findings published in journals like British Journal of Sports Medicine and Resuscitation . Berge’s contributions to healthcare systems include designing prevention protocols for sudden cardiac arrest and investigating bone density issues in elite Para athletes. She has co-authored over 15 peer-reviewed articles since 2014, addressing topics such as ECG interpretation in athletes, post-cardiac arrest quality of life, and the epidemiology of sports-related injuries. Her work bridges clinical research and real-world healthcare applications, particularly in sports medicine and emergency preparedness.

• Sonic Arts
• Sound Studies
• Music Technology
• +۵ مورد دیگر

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.

• Biomedical Engineering
• Neuroscience
• Signal Processing
• +۳ مورد دیگر

Andres Soler is a Lecturer at NTNU's Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering. His research focuses on EEG signal processing for applications in brain-computer interfaces (BCI), stress/health monitoring, and low-density electrode systems. He has published extensively on topics including EEG source imaging, artifact removal, and optimized channel selection techniques. His work bridges biomedical engineering and machine learning, with notable contributions to driver alcohol detection systems and motor imagery classification for neurorehabilitation. Teaching roles include serving as Guest Lecturer for Biomedical Instrumentation and Control (TTK4270) and Adaptive Data Analysis (TTK7), while acting as main lecturer for Industrial Electrotechnics (TTK4240). His research group collaborates internationally on projects like FlexEEG and has presented at conferences such as IEEE EMBC and Brain Informatics. Key research directions include advancing EEG-based systems for clinical and automotive applications, developing algorithms for real-time brain activity decoding, and optimizing EEG hardware configurations for cost-effective implementations. Current trends show focus on enhancing signal quality through artifact mitigation strategies and improving BCI communication systems for locked-in patients.

Sergej Stoppelمشاهده پروفایل

پژوهشگر

• Visual Data Science
• Data Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Sergej Stoppel is currently a researcher (PostDoc) in the visualization group at the University of Bergen. His academic background includes a Mathematics master's degree (2014) and a PhD in 2018, both from the University of Bergen. His research focuses on visual data science, with an emphasis on interactive visualization techniques, human-computer interaction, and physical visualization systems. He has authored/co-authored numerous papers on topics such as hexagonal map enhancements, spatio-temporal data interaction, and low-cost physical art generation. Education: M.Sc. Mathematics (2014), University of Bergen PhD in Visualization (2018), University of Bergen Research Interests: His work spans data visualization, scientific visualization, and interactive techniques. Notable contributions include Vol²velle (printable interactive volume visualization widgets), Firefly (virtual illumination drones), and LinesLab (low-cost art generation systems). He explores methods to bridge the gap between virtual and physical visual representations, emphasizing user-centric design. Publications: His recent work includes advancements in hexagonal map visualization (2022), spatio-temporal selection techniques (2020), and illumination automation (2019). These contributions highlight his focus on enhancing data interpretation through novel interaction paradigms. Labs/Teams: Active member of the VisGroup at the University of Bergen, collaborating on projects like MetaVis and VIDI. His work is supported by grants involving visualization and medical imaging applications.

Eric Mörthمشاهده پروفایل

پژوهشگر

• Medical Visualization
• Medical Imaging
• Biomedical Engineering
• +۶ مورد دیگر

Eric Mörth is a PhD Scientist in Multimodal Medical Visualization at the University of Bergen's Department of Informatics, collaborating with the Mohm Medical Imaging and Visualization Center (MMIV). His research focuses on innovative medical data visualization techniques, such as MuSIC and ICEVis, which enhance clinical decision-making. Currently on a research stay at Harvard University's VCG Group, he holds a Master's in Medical Informatics from the Medical University of Vienna and a degree in Biomedical Engineering from the Technical University of Vienna. His awards include the Best Paper Honorable Mention (VCBM2022) and Best Short Paper (VINCI2022). Mörth's work spans cancer imaging, scrollytelling narratives, and interactive visualization tools, supported by grants from Trond Mohn Stiftelse. He advises through Team Smit and has contributed to projects like RadEx and ParaGlyder, advancing medical data exploration and communication.

• Computer Vision
• Artificial Intelligence
• Digital Twins
• +۳ مورد دیگر

Frank Lindseth is a Professor in the Department of Computer Science at NTNU, where he leads the NTNU Autonomous Perception lab (NAP-lab) and co-directs the Visual Computing group. As a core member of the Norwegian Open AI-Lab (NAIL), his research bridges Visual Computing, AI, and real-world applications in mobility and healthcare. He holds leadership roles in multiple initiatives: Mobility lead for Green2050 Centre, Digital Technology lead for MoST - MobilityLab Stor-Trondheim, and core membership in strategic research areas including Digital Twins and PERSEUS doctoral program. He also contributes to Gemini centers focusing on future road transport, medical imaging AI, and extended realities. His research spans: Visual Intelligence and Computer Vision AI for Autonomous Driving systems Digital Twin development Extended Reality (XR) applications Medical Image Computing

• Serious Games
• Healthcare Technology
• Gamification
• +۴ مورد دیگر

Simon McCallum is an Associate Professor at NTNU’s Faculty of Information Technology and Electrical Engineering. Born in New Zealand, he transitioned from commercial game development in Norway to academia in 2009. His research focuses on Serious Games, particularly in healthcare contexts, gamification, and virtual reality applications. He holds a PhD from the University of Otago (2007), where he studied Computer Science, Mathematics, Psychology, and Philosophy. McCallum has contributed to over 30 publications, including works on cognitive health gaming, software engineering education, and AR applications. He teaches courses such as IMT4307 (Serious Games Research) and IMT3603 (Game Programming). His key projects include the Smartkuber AR game for cognitive screening and the Traction Trebuchet historical engineering study. McCallum has collaborated with institutions like the University of Otago and has engaged in outreach through conferences and media appearances, promoting game technology in healthcare and education.