جستجوی استاد راهنمای دانشگاهی

• Computer Vision
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

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
• +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.

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.

• Maritime safety management and leadership
• Maritime accident and casualty analysis
• Maritime Autonomous Surface Ships (MASS)
• +۳ مورد دیگر

Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.

• Maritime Engineering
• Digital Twin Technology
• Marine Robotics
• +۳ مورد دیگر

Hans Petter Hildre is Head of Department at the Department of Ocean Operations and Civil Engineering , part of the Faculty of Engineering at the Norwegian University of Science and Technology (NTNU). His work focuses on maritime engineering, digital twin technology, and marine operations. Research interests include: Digital Twin Applications in Maritime Industry Offshore Operations and Wind Turbine Installation Marine Robotics and Autonomous Systems Wave Field Estimation and Environmental Load Analysis Human-Machine Interaction in Maritime Contexts Co-simulation and Real-time Monitoring Recent publications highlight trends in: Wave shielding effects for offshore vessels Knowledge transfer from automotive/aviation to maritime Crane path planning using digital twins Visual attention zone recognition systems Hydrodynamic modeling and sensitivity analysis Smart city-maritime integration Scientific collaborations span institutions including: European Commission (Future Skills Reports) Royal Institution of Naval Architects The American Society of Mechanical Engineers (ASME) IEEE Transactions on multiple domains Springer Publishing

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.

• Cognitive Science
• Psycholinguistics
• Multilingualism
• +۴ مورد دیگر

Jon Andoni Duñabeitia is a Full Professor at the School of Languages and Education of Universidad Nebrija in Madrid. He serves as Director of the Centro de Investigación Nebrija en Cognición (CINC) and the International Chair in Cognitive Health . With an h-index of 43 (Scopus), he has published 170+ articles across psycholinguistics, multilingualism, cognitive training, and virtual reality applications in education. His research examines how language processing interacts with cognitive load, emotional modulation, and technological innovation. Principal Investigator for 8+ projects funded by Spanish Government, Basque Government, BBVA Foundation Associate Editor and Editorial Board Member of high-impact journals Recognized among Spain's top 3% scientists across all disciplines Recent publications span topics including: Second-language reading dynamics in VR environments Multilingual cognitive interactions in neurological conditions Emoji/typographic effects on word processing Computerized cognitive assessment and training systems He actively contributes to scientific meetings as invited speaker across Europe, Asia, and Americas. His work bridges basic research in psycholinguistics with applied technologies for cognitive health.

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor 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. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Sigrid Johanna Håheim Ørevikمشاهده پروفایل

دانشیار

• Multimodal Text Analysis
• English as a Second Language (EAL) Education
• Genre Theory in Pedagogy
• +۳ مورد دیگر

Sigrid Johanna Håheim Ørevik is an Associate Professor at the Department of Foreign Languages , University of Bergen. Her work focuses on multimodal text analysis in English education, genre theory, and assessment frameworks. Position: Associate Professor Email: sigrid.orevik@uib.no Research Groups: POTENT – Post-Truth English Teaching Research interests include: Multimodal pedagogies Genre patterns in EAL materials Assessment of student multimodal texts Digital learning resources Vocational English teaching Recent publications (2021–2025) explore: Multimodal design principles Agency in semiotic work Curriculum coherence challenges Remediation of digital resources Long-term genre stability in exams She contributes to the POTENT research group and collaborates internationally on multimodal English learning projects.

• Medical Physics
• Radiation Oncology
• Proton Therapy
• +۳ مورد دیگر

Sara Margareta Cecilia Pilskog serves as an Associate Professor in the Department of Physics and Technology at the University of Bergen, Norway, with dual affiliation at Haukeland University Hospital's Department of Cancer Treatment and Medical Physics. Her research bridges theoretical medical physics and clinical oncology applications, focusing on precision radiotherapy techniques and biological optimization. Her primary research interests center on proton therapy innovation, where she investigates biological optimization strategies using linear energy transfer (LET) and relative biological effectiveness (RBE) modeling. She develops adaptive radiotherapy frameworks to address inter-fractional motion in pelvic cancers, particularly prostate and rectal malignancies. Her work also pioneers neutron-based in-vivo range verification systems and statistical deformation models for dose accumulation. Current projects emphasize reducing treatment margins through anatomical robustness and optimizing biological dose distributions for organ sparing. Analysis of her 15 most recent publications reveals a dominant focus on improving proton therapy precision for pelvic cancers through biological modeling and motion management. Approximately 70% of her work addresses prostate cancer applications, with significant contributions to adaptive strategies for inter-fractional changes and biological optimization techniques. Her research consistently employs Monte Carlo simulations (particularly FLUKA) and clinical data analysis to translate theoretical models into clinically viable solutions. No scientific awards were documented in the provided materials. While specific advising details remain unreported, her collaborative patterns indicate active mentorship within the University of Bergen's medical physics research ecosystem. Her publications consistently involve junior co-authors from clinical physics teams at Haukeland University Hospital, suggesting hands-on supervision of technical staff and research fellows in radiotherapy innovation projects. Grant funding appears primarily channeled through institutional hospital-university partnerships focused on clinical translation of advanced radiotherapy techniques. Dr. Pilskog operates within the University of Bergen's medical physics research cluster that maintains close operational ties to Haukeland University Hospital's radiotherapy department. This integrated academic-clinical environment enables direct implementation of her research on adaptive proton therapy and biological optimization into clinical workflows, with particular emphasis on pelvic cancer treatment protocols. The team utilizes advanced Monte Carlo simulation platforms and clinical treatment planning systems to develop and validate next-generation radiotherapy approaches.

• Applied Artificial Intelligence
• Digital Twins
• Hybrid Modeling
• +۴ مورد دیگر

Idelfonso Nogueira is an Associate Professor at the Department of Chemical Process Technology, Norwegian University of Science and Technology (NTNU). His research focuses on integrating artificial intelligence, advanced control, and system optimization to address challenges in Industry 4.0/5.0. Key research areas include AI-driven product/process development, interpretable machine learning for process systems, multi-scale system integration, and adaptive digital twins. He collaborates extensively with global universities, institutes, and industries to advance sustainable industrial solutions. His work emphasizes digitalization, hybrid modeling, and optimization frameworks, as seen in publications on pressure swing adsorption, fragrance engineering, and CO2 capture systems. He also promotes innovative teaching methods, including augmented reality for chemical engineering education. Recent publications highlight advancements in digital twin frameworks, machine learning for crystallization processes, and optimal control strategies. His research bridges theoretical models with practical applications, ensuring robustness and reliability in industrial contexts.

• Special Education
• Reading Comprehension
• Digital Learning Environments
• +۲ مورد دیگر

Natalia Latini is a postdoctoral fellow at the Department of Education , University of Oslo, Norway. Her research focuses on reading comprehension , digital learning environments , and special education with an emphasis on specific learning disabilities. She actively contributes to research groups like Development, Equity, and Literacy in Learning Contexts (DEAL) , and projects including CrossREAD (Reading across mediums, devices, and contexts) . Education: Ph.D., Department of Education, University of Oslo (2022) Master in Special Education, Specific Learning Disabilities, University of Oslo (2017) Bachelor in Special Education, University of Oslo (2015) Psychology, year unit, University of Oslo (2012) Her research investigates how digital reading impacts comprehension, with a focus on multimedia integration , media multitasking , and self-efficacy in academic writing . She utilizes methodologies like eye-tracking and verbal protocols to analyze behavioral engagement and cognitive processing across mediums. Recent studies examine belief bias in adolescents and the role of main idea summarization in multiple-document comprehension. Key collaborations include work with researchers such as Ivar Bråten , Ymkje Elisabeth Haverkamp , and Helge Ivar Strømsø . Her publications span journals like Journal of Research in Reading , Literacy Research and Instruction , and Contemporary Educational Psychology . Natalia's research contributes to understanding how technology-mediated learning affects educational outcomes, particularly for individuals with learning challenges. She explores the interplay of screen size , text movement , and media multitasking on comprehension and motivation, offering insights for adaptive teaching strategies in digital contexts.

• Computer-Supported Collaborative Learning
• Virtual Reality in Education
• Science Education
• +۵ مورد دیگر

Rolf Steier serves as Professor at Oslo Metropolitan University within the Faculty of Education and International Studies, Department of Primary and Secondary Teacher Education, holding the position of Head of Studies for Area of Responsibility 5. His office is located at Pilestredet 52, 0167 Oslo (B534), with contact details including mobile +47 906 92 626, office +47 672 36 014, and email rolf.steier@oslomet.no. He actively contributes to the Digital Learning Arenas research group, focusing on technology-enhanced educational environments. Steier's research centers on computer-supported collaborative learning (CSCL) and virtual reality applications in education, with specific expertise in embodied cognition, science education, museum learning, and narrative structures in STEM. His work examines how learners co-construct knowledge through digital interactions, particularly investigating the role of physical embodiment in virtual environments and the integration of narrative techniques to facilitate engagement in informal learning contexts. Recent projects explore immersive VR experiences for collaborative meaning-making and the adaptation of interaction analysis methodologies for technology-mediated educational research. Analysis of Steier's 2021-2025 publications reveals a clear trajectory toward increasingly sophisticated integration of virtual reality in educational research, with growing emphasis on interdisciplinary applications in science education. Key thematic developments include the refinement of interaction analysis frameworks for digital contexts, the exploration of perspective-taking across blended realities, and the strategic use of narrative to enhance STEM engagement in informal settings. His work consistently bridges theoretical learning science with practical educational technology implementation. The Digital Learning Arenas research group serves as the primary platform for Steier's collaborative work, functioning as an interdisciplinary hub for developing and studying innovative digital learning solutions. This group facilitates partnerships across educational sectors to transform teaching practices through emerging technologies, with recent focus on VR-based collaborative learning environments and cross-contextual knowledge transfer.

Adriana Gerarda Busمشاهده پروفایل

استاد

• Early Literacy
• Digital Literacy
• Multimedia Learning
• +۷ مورد دیگر

Adriana Gerarda Bus is a Professor at the University of Stavanger, Faculty of Arts and Education, and a leading researcher at the National Centre for Reading Education and Research. Her work bridges early literacy, digital media, and educational intervention, with a strong focus on how digital picture books can support children's language and reading development. Her research interests include early literacy, digital literacy, multimedia learning, bilingual and multilingual reading, home literacy environments, and educational technology. She investigates how digital enhancements in e-books influence story comprehension and vocabulary acquisition, particularly among young and language-minority children. Her work often employs meta-analytic methods to synthesize evidence across studies. The most recent articles highlight a consistent trend: exploring the efficacy, design, and accessibility of digital picture books across diverse contexts. Themes include screen vs. paper reading, multilingual access, nudging strategies to promote reading, and interventions like Bookstart. Her publications appear in high-impact journals such as AERA Open , Learning and Instruction , and Review of Educational Research . Building a Stronger Case for Independent Reading at School (2024) Nudging to Stimulate Reading in Primary and Secondary Education (2023) Efficacy of digital picture book enhancements... (2023) Free access to multilingual digital books... (2023) A Comparison of Children’s Reading on Paper Versus Screen: A Meta-Analysis (2021) She has received no explicitly mentioned scientific awards in the provided text. Her advising activities are not detailed, but she frequently collaborates with PhD students and early-career researchers. She has been involved in grant-funded projects related to digital literacy, Bookstart evaluations, and cross-cultural studies of reading interventions. She is affiliated with the National Centre for Reading Education and Research, a key hub for literacy research in Norway. Her team engages in both experimental and meta-analytic studies, often in collaboration with international partners from the Netherlands, the U.S., Poland, and Zambia. Future work appears to focus on expanding digital access for multilingual families and refining digital book designs for optimal learning outcomes.

Martin Wulf Gerdesمشاهده پروفایل

دانشیار

• eHealth
• Artificial Intelligence
• Machine Learning
• +۹ مورد دیگر

Martin Wulf Gerdes is an Associate Professor at the Department of Information and Communication Technology, University of Agder, Norway. With a Ph.D. in eHealth and over two decades of experience in telecommunications and healthcare technology research, he focuses on developing user-friendly, interoperable eHealth solutions using ICT and IoT. His career spans roles at Ericsson Eurolab and academic leadership in Norway. Education: M.Sc. equivalent in General Electrical Engineering (1998) from RWTH Aachen, emphasizing ICT. Ph.D.: Information and Communication Technologies with eHealth specialization (2019) from University of Agder. Research Interests: Gerdes explores AI-driven decision support systems, distributed eHealth infrastructure, telemedicine, and assistive technologies for chronic disease management. His work bridges IoT, data privacy, and user-centered design in healthcare robotics. Teaching: Since 2014, he has taught at bachelor's and master's levels, currently leading courses in Communication & Cooperation, Technology Understanding, and seminar projects in eHealth. Scientific Publications: His 15 most recent articles (2020-2024) span AI in dental radiology, blood glucose prediction, digital twins, and ethical considerations in healthcare algorithms. Topics include IoT integration, data privacy, and pandemic analytics.