جست‌وجوی استاد و پژوهشگر

• 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.

Vasileios Mavroeidisمشاهده پروفایل

دانشیار

• Cybersecurity
• Security Automation and Orchestration (SOAR)
• Cyber Threat Intelligence (CTI)
• +۶ مورد دیگر

Vasileios Mavroeidis is an Associate Professor in Digital Security at the Department of Informatics, University of Oslo (UiO). He specializes in security automation and orchestration (SOAR) and cyber threat intelligence (CTI) representation, reasoning, and sharing. He actively contributes to European cybersecurity initiatives, including Horizon Europe, Connecting Europe Facility, and the European Defense Fund, and serves as the primary representative of UiO at the OASIS standards development organization since 2017. Role : Associate Professor Department : Digital Security (SEC), University of Oslo Standardization Involvement : Chairman of OASIS Threat Actor Context (TAC), Leading Contributor to CACAO and OpenC2 Projects : Concordia, CyberHunt, JCOP (Joint Cyber Security Operations Platform), Oslo Analytics, P4C (Partnership for Cybersecurity) His research focuses on cyber threat intelligence (CTI), exploring its taxonomies, sharing standards (STIX, CACAO), and ontologies, with contributions to the European Union Agency for Cybersecurity (ENISA) Cybersecurity Playbooks task force. He analyzes quantum computing's impact on cryptography, develops automated threat detection systems using machine learning (e.g., recurrent neural networks for malware-generated domains), and investigates privacy issues under GDPR. Recent publications highlight his work on LLMs for code stylometry , neurosymbolic AI for cyber defense , and knowledge management systems for CACAO playbooks . His articles span 2017–2025, emphasizing formal verification, biometric data protection, and incident response automation. He collaborates with organizations like OASIS (Threat Actor Context, CACAO, OpenC2) and FIRST (Traffic Light Protocol), and participates in European research projects. His work includes standardization efforts in cybersecurity playbooks , MITRE ATT&CK representation, and quantum-resistant cryptography .

• Semantics
• Language Technology
• Recommender Systems
• +۵ مورد دیگر

Jon Atle Gulla is a Professor at NTNU and Director of the Norwegian Research Centre for AI Innovation (NorwAI). He holds academic leadership roles, including former Head of the Department of Computer Science and Informatics at NTNU. His expertise spans Semantics, Language Technology, Recommender Systems, and AI-driven innovation. He has nearly 150 international publications and advised over 100 students across MSc, PhD, and postdoctoral levels. Education: MSc in Computer Science (1988), PhD in Computer Science (1993) from Norwegian Institute of Technology (NTH) MSc in Linguistics (1995), University of Trondheim MSc in Management (Sloan fellowship, 2003), London Business School Research interests focus on Semantics and Language Technology applied to Recommender Systems, Information Retrieval, and Text Analysis. He explores AI-based innovations in digitalization and entrepreneurship, advising industry on AI adoption and commercialization. Notable projects include Big Data collaborations with DNB, RecTech for news recommendation, and Trondheim Analytica analyzing political texts/social media. Publications emphasize AI applications in news recommendation, political text analysis, and Scandinavian language models. His work addresses ethical AI, copyright implications, and cross-lingual NLP challenges. Awards: Member of the Royal Norwegian Society of Arts and Sciences. Advising/grants: Supervised 30 PhD students and 70 MSc students. Involved in startups like Fast Search & Transfer (acquired by Microsoft) and Mito.ai/Strise.ai. Active in reviewing for journals like Data & Knowledge Engineering and conferences like ACL. Labs/teams: Leads NorwAI, co-founder of INRA and NOBIDS workshops. Collaborates with industry and academia on AI-driven solutions.

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.

Svitlana Rogovchenkoمشاهده پروفایل

استاد

• Differential Equations
• Impulsive Differential Equations
• Asymptotic Methods in Nonlinear Mechanics
• +۳ مورد دیگر

Svitlana Rogovchenko is a Professor at the Department of Engineering Sciences, University of Agder, Norway. Her academic work bridges pure mathematical research in differential equations with innovative pedagogical approaches in engineering and interdisciplinary education. Educational Background: Doctor of Philosophy in Differential Equations (1988), Institute of Mathematics, National Academy of Sciences, Kyiv, Ukraine Master of Science in Mathematics (1983), Kyiv State University, Ukraine Research Interests: Qualitative theory of ordinary and impulsive differential equations, asymptotic methods in nonlinear mechanics, mathematical modeling, and the intersection of mathematics education with engineering and biology curricula. She focuses on conceptual understanding, pedagogical challenges, and commognitive conflicts in learning differential equations. Recent Publications Trends: Her work spans mathematical modeling of vehicle crashworthiness, interdisciplinary education for biologists and engineers, and pedagogical innovations in ordinary differential equations. Articles emphasize assessment design, group work tensions, and bridging mathematical theory with applied contexts.

• EEG Signal Processing
• Brain-Computer Interfaces
• Artificial Intelligence
• +۵ مورد دیگر

Marta Molinas is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). Her research spans multiple interdisciplinary domains with a focus on EEG technology and brain-computer interfaces. She actively supervises numerous Master's projects and maintains extensive international collaborations with institutions including Kavli Institute for Systems Neuroscience, RIKEN Center for Brain Science, University of Tsukuba, Juntendo University, and several European universities. Professor Molinas' research interests center on developing innovative EEG technologies, particularly her FlexEEG concept for reduced-channel EEG systems with brain imaging capabilities. Her work integrates signal processing, artificial intelligence, and neuroscience to create practical applications in mental health, sleep research, neurorehabilitation, and human-computer interaction. She specializes in EEG source imaging, machine learning for brain signal analysis, and the development of brain-computer interfaces for various applications including locked-in syndrome communication, ADHD treatment, and driver monitoring systems. Her publication portfolio demonstrates strong trends in interdisciplinary research combining neuroscience with electrical engineering and artificial intelligence. The work shows particular emphasis on developing practical EEG-based systems that minimize invasiveness while maintaining analytical power, with applications spanning healthcare, rehabilitation, and human augmentation. Her research bridges theoretical signal processing with real-world implementations through numerous student projects and international collaborations. Professor Molinas actively supervises a large team of Master's and PhD students across multiple projects, with each project typically requiring two students working collaboratively. Her research is supported through numerous international collaborations with institutions in Japan, India, and Europe, indicating substantial research funding and project leadership. She has developed a pipeline of student projects that build upon previous work, creating a cumulative knowledge base within her research group. She leads the EEG ITK research team at NTNU, which focuses on developing the FlexEEG headset prototype featuring flexible, wireless, dry electrodes designed to move across the scalp. This team works at the intersection of neuroscience, electrical engineering, and computer science, developing applications for sleep research, mental health monitoring, neurorehabilitation, and brain-computer interfaces. The team collaborates extensively with international partners including the Kavli Institute for Systems Neuroscience, the International Institute of Integrative Sleep Medicine at University of Tsukuba, and several engineering departments across Europe and Asia.

Mikaela Vasstrømمشاهده پروفایل

دانشیار

• Energy transitions
• Energy democracy
• Energy governance
• +۵ مورد دیگر

Mikaela Vasstrøm (b.1977) is an Associate Professor at the Department of Global Development and Planning, University of Agder. She holds a PhD from the University of Copenhagen and leads significant research projects including the Norwegian Research Council-funded WINDPLAN initiative, which analyzes social acceptance and governance challenges in onshore wind power development across Norway, Scotland, and Denmark. She co-leads work packages in the WINDREG project focusing on procedural justice and knowledge co-production for energy transitions. Her research examines: Just energy transitions and energy democracy Governance challenges in renewable energy deployment Public participation in environmental conflicts Local/regional development implications of energy policies She co-directs UiA's participation in the Empowered Futures research school, developing PhD-level expertise in energy policy frameworks. Publications focus on wind energy governance, policy legitimacy, and spatial planning conflicts, with consistent themes of: Energy justice in policy design Local government capacity in energy transitions Participatory approaches in sustainability planning Research group affiliations include: Energy and Society Urban and Regional Planning (URPLAN)

• Sociology
• Consumer Behavior
• Food Culture
• +۵ مورد دیگر

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

Terese Johannessenمشاهده پروفایل

دانشیار

• Quality Improvement in Healthcare
• Nursing Education
• Healthcare Leadership
• +۶ مورد دیگر

Terese Johannessen serves as an Associate Professor in the Department of Health and Nursing Sciences at the University of Agder (UiA), Norway. Her academic work focuses on quality improvement, leadership development, and implementation science within healthcare settings, particularly in nursing homes and home care services. Dr. Johannessen's research primarily centers on understanding quality and safety in long-term care environments. Her work investigates contextual factors influencing healthcare quality, leadership interventions for improvement, and the conceptualization of 'quality' among healthcare providers. She employs qualitative methodologies to explore managers' experiences, implementation challenges, and the development of practical tools for frontline staff. Her research has significant implications for improving care delivery in nursing homes and home care services through evidence-based leadership approaches. Analysis of Dr. Johannessen's publication record reveals a strong thematic focus on the SAFE-LEAD project, a comprehensive research initiative examining leadership interventions for quality and safety in nursing homes and home care. Her work spans multiple dimensions including intervention design, implementation challenges, contextual mapping, and evaluation of leadership approaches across different healthcare settings. The research demonstrates a methodological preference for qualitative and mixed-methods approaches to capture the complex realities of healthcare improvement work. Dr. Johannessen collaborates extensively with researchers including Siri Wiig, Eline Ree, and Ingunn Aase, primarily through the SHARE Centre for Resilience in Healthcare at the University of Stavanger. Her work bridges academic research and practical application in healthcare settings, with significant contributions to understanding how quality improvement efforts can be effectively implemented in real-world contexts. Her research portfolio demonstrates consistent productivity with multiple publications annually, showing progression from foundational studies on contextual factors to the development and testing of specific leadership interventions. The SAFE-LEAD project represents a cohesive research program addressing critical challenges in long-term care quality and safety through systematic investigation and practical tool development.

• Risk Management
• Risk Analysis
• Uncertainty Quantification
• +۱۲ مورد دیگر

Roger Flage is a Professor of Risk Management at the University of Stavanger, affiliated with the Faculty of Science and Technology and the Department of Security, Economics and Planning. His research focuses on foundational and applied aspects of risk analysis, uncertainty quantification, and decision-making under uncertainty, with applications in critical infrastructure, environmental systems, and offshore energy. Roger Flage's research interests lie at the intersection of risk science, safety engineering, and decision theory. He investigates how uncertainty—especially epistemic uncertainty and assumptions—affects risk assessments, and advocates for more transparent and robust frameworks. His work spans theoretical advances, such as the treatment of 'black swan' events and the concept of 'real risk', as well as practical applications in offshore safety, power systems, and geohazards. He emphasizes the integration of data-driven methods, AI, and digital twins while critically assessing their limitations and associated security risks. His recent publications show a strong trend toward integrating dynamic, data-rich, and interdisciplinary approaches to risk analysis. Themes include the role of time in risk, AI applications, infrastructure interdependencies, and environmental risk in the oil and gas sector. He frequently publishes in top-tier journals like Risk Analysis , Reliability Engineering & System Safety , and Safety Science , often in collaboration with leading scholars such as Terje Aven and Seth Guikema. No scientific awards are mentioned in the provided text. Roger Flage has supervised or collaborated with several researchers, though no formal list of advisees is provided. His work is supported through academic collaborations and institutional affiliations rather than explicit grant mentions. He is actively involved in advancing risk science methodology, particularly in the treatment of assumptions and uncertainty, and contributes to both theoretical foundations and real-world applications in safety-critical domains. He is associated with research groups and collaborative networks at the University of Stavanger, particularly within the Department of Security, Economics and Planning. His work often involves interdisciplinary teams focusing on risk in complex engineered systems, including energy, transportation, and environmental systems.

• Educational Leadership
• Implementation Science
• Capacity Building in Education
• +۱۲ مورد دیگر

Pål Roland is a Professor at the University of Stavanger, Faculty of Arts and Education, and affiliated with the Norwegian Centre for Learning Environment and Behavioral Research in Education. He is based in Stavanger and actively contributes to research and dissemination in educational leadership, implementation science, and behavioral research in schools and kindergartens. His research interests focus on implementation science , capacity building in educational organizations , social and emotional learning , bullying prevention , classroom interactions , and leadership in change processes . He emphasizes systemic and organizational approaches to sustainable development in pedagogical settings. The recent articles highlight a consistent focus on implementation quality, professional learning communities, leadership in educational change, and behavioral support in early childhood and school contexts. His work bridges theory and practice, often involving collaboration with school leaders and practitioners. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: No formal advisees or grant information is listed in the provided content. However, his extensive collaborative research and leadership in dissemination suggest active involvement in research projects and networks, likely supported by external funding. Labs and Teams: He is a key researcher at the Norwegian Centre for Learning Environment and Behavioral Research in Education , which functions as a research group focused on improving learning environments through evidence-based practices. He frequently collaborates with researchers such as Sigrun K. Ertesvåg, Ella Maria Cosmovici Idsøe, and others on projects related to bullying, SEL, and implementation.

• Wireless Communications
• Machine Learning
• Digital Twins
• +۵ مورد دیگر

Pierluigi Salvo Rossi is a Professor at the Department of Electronic Systems , Norwegian University of Science and Technology ( NTNU ), with additional roles as Deputy Head of Department (since 2021) and Deputy Manager at the Center for Green Shift in the Built Environment (since 2022). He also serves as a part-time Research Scientist at SINTEF Energy's Gas Technology department. Education: Ph.D. in Computer Engineering, University of Naples “Federico II”, Italy (2005) Dr.Eng. (cum laude) in Telecommunications Engineering, University of Naples “Federico II”, Italy (2002) Research Interests span Wireless Communications , Digital Twins , Machine Learning , and Statistical Signal Processing , focusing on applications like Industrial IoT , Fault Detection , and Energy Systems . His recent Publications highlight trends in Federated Learning , Graph Signal Processing , and Multi-Sensor Anomaly Detection across domains from Natural Gas Pipelines to Subsea Leakages . Scientific Awards include: Exemplary Senior Editor, IEEE Communications Letters (2018) Department Ambassador, NTNU (2016) IEEE Senior Member (since 2011) Professional Roles encompass editorial leadership (e.g., IEEE Sensors Journal) and conference organization (e.g., General Chair for IEEE Sensor Array and Multichannel Signal Processing Workshop, 2022). He leads major funded research projects like PREFERENCE (RCN, 2023-2027) and AUTOSHIP (RCN, 2020-2028).

• Artificial Intelligence
• Knowledge Management
• Secure Software Development
• +۳ مورد دیگر

Shao-Fang Wen is an Associate Professor at the Department of Information Security and Communication Technology, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). Their work focuses on integrating artificial intelligence with cybersecurity, secure software development, and socio-technical systems. Research Interests: Artificial Intelligence and Cybersecurity Secure Software Development Semantic Web and Ontology Socio-Technical Systems System Security Assurance Publications and Contributions: Shao-Fang Wen has contributed significantly to developing frameworks for AI security assurance, quantitative security evaluation models (e.g., SAEOn metamodel), and contextualized learning systems for software security. Their work spans journal articles, conference papers, and book chapters, emphasizing ontology-based approaches and open source community dynamics. Teaching: IIKG2001 - Software Security

Ferreira Joao Carlosمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Energy and Transportation
• +۶ مورد دیگر

Joao Carlos Amaro Ferreira is a Professor at the Faculty of Logistics, Molde University College (HiMolde), Norway. He holds PhDs in Computer Engineering and Industrial Engineering from the Technical University of Lisbon and the University of Minho, respectively. His research focuses on Artificial Intelligence (AI) applications in healthcare, energy, transportation, IoT, blockchain, and smart cities. He has led over 40 projects, including 6 as Principal Investigator, and contributed to international conferences like OAIR and INTSYS. He served as IEEE CIS President (2016-2018) and is an IEEE Senior Member since 2015. His academic contributions span AI-driven solutions for public sector informatics, healthcare data quality, and cybersecurity. He actively participates in European projects such as e-Hospital4Future and explores blockchain applications in supply chains and medical records. Ferreira leads the ABC-AI research group, emphasizing ethical and applied AI. His work bridges academia and industry through projects like gamification systems for eco-driving and AI in fisheries traceability. Recent publications highlight AI's role in cardiovascular disease detection, emergency department optimization, and blockchain-enhanced healthcare interoperability. He collaborates internationally, co-editing journals like Applied Sciences , and has authored patents in edge computing for maritime monitoring.

• Metal Forming
• Aluminum Alloys
• Product Development
• +۳ مورد دیگر

Torgeir Welo is a Professor at the Department of Mechanical and Industrial Engineering , Norwegian University of Science and Technology (NTNU) . He specializes in metal forming , particularly aluminum alloy structures , with a focus on plastic bending behavior , dimensional stability , and 3D forming technologies . His research also encompasses Lean Product Development , emphasizing knowledge reuse and maximizing customer value in automotive and aerospace applications. Key Research Areas : Metal Forming, Aluminum Processing, Springback Control, Lean Development, Additive Manufacturing, Material Substitution Teaching : Courses on Aluminum Technology , Metal Forming Analysis , and Machine Element Design Publications (15 most recent): Focus on springback monitoring , charge weld evolution , flexible forming , machine learning applications , and circular economy frameworks in metal manufacturing.