جستجوی استاد راهنمای دانشگاهی

Tom Ryenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Digital Signal Processing
• +۱۳ مورد دیگر

Tom Ryen is an Associate Professor and Head of the Department of Electrical Engineering and Computer Science at the University of Stavanger (UiS), Faculty of Science and Technology. He plays a key leadership role in advancing artificial intelligence research and education, including co-founding the Stavanger AI Lab and chairing the board of the Norwegian Artificial Intelligence Research Consortium (NORA). His work bridges technical research and public engagement, particularly on the societal implications of AI. His research focuses on artificial intelligence, machine learning, digital signal processing, and bioinformatics. He has made significant contributions in gene prediction, splice site analysis using neural networks, ECG signal compression, and GPU-based optical flow algorithms. His recent work emphasizes AI ethics, education, and public understanding, reflecting a shift toward societal impact and policy. Tom Ryen's publications from 2024 show a strong trend in public outreach, with articles and lectures on AI literacy, misinformation, workplace integration, and educational challenges. These works highlight his role as a thought leader in Norway’s AI discourse, advocating for responsible adoption, national infrastructure, and ethical guidelines. Scientific Awards: No scientific awards mentioned in the text. Tom Ryen actively mentors students and collaborates across disciplines, though specific advisees are not listed. He has been involved in significant initiatives such as launching new master’s programs, expanding IT education, and promoting AI in medical and urban technologies. He has not received any mentioned grants, but his leadership in NORA and the Stavanger AI Lab suggests substantial project involvement. He is a founding figure in the Stavanger AI Lab, a research unit at UiS dedicated to AI innovation, education, and collaboration with industry and public sectors. The lab focuses on practical applications and ethical deployment of AI, aligning with national and regional development goals.

Lei Jiaoمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Tsetlin Machines
• +۷ مورد دیگر

Lei Jiao is a Professor in the Department of Information and Communication Technology at the University of Agder's Faculty of Engineering and Science. Previously serving as an Associate Professor from May 2014 to October 2022, Dr. Jiao has established himself as a leading researcher in artificial intelligence, with particular expertise in Tsetlin Machines and their applications across diverse domains. PhD in Information and Communication Technology, University of Agder (2008-2012) Master of Engineering in Communication and Information System, Shandong University (2005-2008) Bachelor of Engineering in Telecommunication Engineering, Hunan University (2001-2005) Dr. Jiao's research spans multiple cutting-edge areas including interpretable artificial intelligence, wireless communication protocols, network resource allocation, and signal processing. His work on Tsetlin Machines has pioneered new approaches to machine learning that emphasize interpretability while maintaining high performance. The research group he contributes to at the University of Agder focuses on Autonomous and Cyber-Physical Systems (ACPS), Battery recycling, and the Centre for Artificial Intelligence Research (CAIR). Analysis of Dr. Jiao's recent publications reveals a strong emphasis on interpretable AI systems, particularly through Tsetlin Machines. His work spans applications in GNSS jammer detection, crowd anomaly detection, DNA sequence classification, and hardware acceleration of machine learning models. The research consistently demonstrates how logical, rule-based approaches can provide transparent alternatives to traditional neural networks while maintaining competitive performance. Supervised numerous PhD students including Vojtech Halenka, Ahmed K. Kadhim, and Sindhusha Jeeru Mentored over 30 Master's thesis projects covering topics from Tsetlin Machines to signal processing and computer vision Collaborates extensively with Ole-Christoffer Granmo and other leading researchers in the AI field Dr. Jiao actively contributes to advancing the field through supervision of doctoral candidates, collaboration on major research projects, and development of novel machine learning approaches that balance performance with interpretability. His work bridges theoretical foundations with practical applications across telecommunications, computer vision, and natural language processing domains.

• Gender Studies
• Migration Studies
• Pedagogy
• +۳ مورد دیگر

Tatiana Wara is an Associate Professor at the Department of Teacher Education and Pedagogy, UiT The Arctic University of Norway. Her work focuses on gender studies, migration, and pedagogy, particularly examining the experiences of Russian female migrants in Northern Norway and educational practices in Arctic contexts. She collaborates on interdisciplinary projects related to social sustainability and democratic preparedness. Current projects: DEMBRA (Democratic Preparedness against Racism), RFFVEST (The Founder’s Track for Refugees), Ukrainian Refugees’ Health Services Use Research groups: ICred (Education and Social Sustainability), Sted Makt Mobilitet, LIFT (Teacher Education in Changing Times) Her recent research explores: Gender hierarchies in Arctic landscapes Impact of social media on Arctic youth well-being Using film as a pedagogical tool for discomfort and human rights Cultural adaptation through narratives of Norwegianization Intersectional approaches to critical diversity in education She has published extensively on these topics in journals and book chapters, often collaborating with scholars like Mai Camilla Munkejord, Marcela Douglas Aranibar, and Tove Beate Jensen.

• Cybersecurity
• Artificial Intelligence
• Cyber Ranges
• +۵ مورد دیگر

Muhammad Mudassar Yamin serves as an Associate Professor in the Department of Information Security and Communication Technology at the Norwegian University of Science and Technology (NTNU), Gjøvik campus. His academic work spans cybersecurity research, artificial intelligence applications, and cyber range development, with significant contributions to security exercise frameworks and adversarial machine learning. His research interests focus on Cybersecurity , particularly in cyber ranges, security assurance, and AI-driven threat detection. Key areas include Kill Chain analysis, adversarial machine learning for hate speech detection, and security exercise scenario generation. Recent work demonstrates increasing integration of large language models for cybersecurity training and multilingual threat detection systems. Yamin's publication trends show consistent output in top cybersecurity venues, with recent emphasis on AI applications for security (2022-2025). His work bridges theoretical frameworks and practical implementations, particularly in cyber range technologies and threat intelligence systems. Collaborations with researchers like Basel Katt and Ehtesham Hashmi appear frequently across publications. He teaches courses including IIK3100 - Ethical Hacking and Penetration Testing and TTM4175 - Introduction to Cyber Security and Data Communication, reflecting his expertise in practical security education. His doctoral thesis (2022) focused on modeling and analyzing attack-defense scenarios for cyber ranges, establishing the foundation for his current research trajectory.

• Deep Learning
• Medical Multimedia
• Explainable AI
• +۵ مورد دیگر

Steven Hicks is a Senior Research Scientist in the Holistic Systems department at Simula Metropolitan. His work focuses on applying artificial intelligence techniques to medical and multimedia applications, with particular emphasis on explainability and transparency in AI systems. Dr. Hicks' research spans multiple domains including medical imaging, particularly in gastrointestinal endoscopy and reproductive medicine. His primary interests include Deep Learning , Medical Multimedia , Explainable AI , and Computer Vision . His work has significant applications in polyp detection, sperm analysis, ECG interpretation, and medical image segmentation, contributing to advancements in diagnostic accuracy and clinical decision support systems. Analysis of Dr. Hicks' recent publications reveals a strong focus on medical applications of AI with emphasis on transparency and explainability. His work frequently addresses challenges in gastrointestinal endoscopy, reproductive medicine, and cardiology. A notable trend is his involvement in creating benchmark datasets like Kvasir-VQA and VISEM-Tracking, and organizing challenges through MediaEval and ImageCLEF to advance the field of medical AI and establish standardized evaluation frameworks. Dr. Hicks actively collaborates with medical professionals and researchers across multiple institutions, contributing to the development of practical AI solutions for real-world medical problems. His work bridges the gap between theoretical AI research and clinical applications, with significant contributions to both technical innovations and the creation of essential resources for the medical AI community.

Leon Moonenمشاهده پروفایل

استاد پژوهش

• Security and Resilience in Software Systems
• Self-Healing and Self-Adaptive Software
• Applications of Machine Learning in Software Engineering
• +۶ مورد دیگر

Leon Moonen is a Research Professor and Head of the Data-Driven Software Engineering Department at Simula Research Laboratory in Oslo, Norway. He also holds a visiting professor position at the Department of Data Science and Analytics at BI Norwegian Business School. His research focuses on developing advanced data-driven techniques and tools to help software engineers create more secure, trustworthy, and resilient systems. His work combines software analysis, machine learning and AI, software reverse engineering, software repository mining, program comprehension, and empirical software engineering. Moonen's research addresses three main areas: (1) cybersecurity, particularly automated assessment and repair of software security vulnerabilities, as well as automated support for cyber threat intelligence; (2) autonomous self-healing systems, investigating how bio-inspired approaches can build more resilient systems; and (3) intelligent analytics to leverage data from software development, evolution, and operation to support decision-making. His recent publications demonstrate a strong focus on applying large language models to software engineering challenges, including automated programming, program repair, log analysis, and vulnerability detection. The research shows a progression from traditional software engineering approaches toward increasingly sophisticated AI-driven techniques. Professor Moonen has led projects supporting smarter evolution and testing of safety-critical cyber-physical product families, high-integrity software engineering, and software analytics for continuous quality assessment. He collaborates closely with industrial partners including Kongsberg Maritime and Cisco Norway. Before joining Simula, Moonen worked at Delft University of Technology and the Centre for Mathematics and Computer Science (CWI) in Amsterdam. He is also a co-founder of the Software Improvement Group (SIG), which has grown from 6 to over 150 employees since 2000.

Andreas L Opdahlمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Graphs
• Information Systems Development
• +۴ مورد دیگر

Andreas L Opdahl is a Professor at the Department of Information Science and Media Studies at the University of Bergen. He leads the Intelligent Information Systems (I2S) research group, focusing on AI-driven solutions for news media and public sectors, including knowledge graphs, ontologies, and large language models. His work emphasizes ethical AI integration in journalism and data quality frameworks for automated fact-checking. Research interests span AI applications in media, cybersecurity, enterprise modeling, and semantic technologies. Notable contributions include developing methodologies for hacker attack representation (HARM), integrating safety and security requirements (CHASSIS), and advancing knowledge graph platforms for newsrooms. His publications address challenges in information systems development, including interoperability, ontology evaluation, and multi-perspective problem analysis. Opdahl has contributed to foundational work on misuse cases for security threat modeling and semantic quality criteria in requirements engineering. His recent research explores emerging technologies like LLMs for news classification and the ethical dimensions of AI in journalism. He has been involved in projects such as the News Angler platform and semantic annotation frameworks using real-time data. His academic career includes roles as an author in leading conferences (e.g., IEEE, ACM) and journals, with a focus on conceptual modeling, enterprise systems, and requirements engineering. Collaborations span institutions like NTNU, the University of Amsterdam, and international research networks.

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Sarang Shaikh is a Researcher at the Department of Information Security and Communication Technology, affiliated with the Faculty of Information Technology and Electrical Engineering at NTNU. He holds a master’s degree in computer science from Sukkur IBA University (2020) and is currently pursuing a PhD at NTNU. Previously, he served as a Visiting Lecturer at Sukkur IBA University. Education: PhD candidate in Information Security and Communication Technology, NTNU (ongoing) Master’s in Computer Science, Sukkur IBA University, Pakistan (2020) Research Interests: Sarang focuses on applied research in artificial intelligence, including machine learning, deep learning, and natural language processing (NLP). His work integrates language technologies and learning technologies to advance educational applications. He also explores agent-based modeling and simulation within computational frameworks. His expertise spans interdisciplinary areas such as AI-driven educational tools and secure communication systems. Advising & Grants: Currently a PhD student, Sarang has no formal advisees listed. However, he contributes to academic rigor by serving as a Reviewer for IEEE ACCESS . Specific grant details are not provided in the text. Labs/Teams: While no explicit lab or team affiliations are mentioned, his research aligns with the Department of Information Security and Communication Technology’s focus areas at NTNU’s Gjøvik campus.

• Recommender Systems
• Privacy Issues in AI
• Fake News Detection
• +۳ مورد دیگر

Özlem Özgöbek is an associate professor at the Department of Computer Science at NTNU, focusing on recommender systems, privacy in AI, and fake news detection. She holds a part-time role as a program manager at the Norwegian Research Center for AI Innovation (NorwAI) since November 2023. She coordinates the International Work-Integrated-Learning in Artificial Intelligence (IWIL AI) project and actively participates in organizing committees such as the INRA Workshop Series and the Norwegian Big Data Symposium (NOBIDS). She collaborates with the Center for Excellent IT Education (Excited) center, contributing to advancements in semantic web technologies and machine learning applications in education. Her research bridges academic and industrial challenges, emphasizing ethical AI deployment and user-centric systems. Key contributions include multimodal fake news detection frameworks, educational technology innovations, and sustainable wardrobe recommendation systems leveraging Linked Open Data. She has organized multiple international workshops (e.g., INRA 2021–2023) and contributed to benchmarking initiatives like MediaEval’s news image analysis tasks. Her academic work spans over 30 peer-reviewed publications since 2014, including studies on classroom interaction tools, privacy perceptions in recommender systems, and the Adressa news dataset for evaluation purposes. She maintains strong ties with collaborative projects such as the IWIL AI initiative, fostering international education-industry partnerships in AI.

Zhirong Yangمشاهده پروفایل

استاد

• Machine Learning
• Information Visualization
• Data Representation Learning
• +۶ مورد دیگر

Zhirong Yang is a Professor at the Department of Computer Science at the Norwegian University of Science and Technology (NTNU). He is affiliated with the Norwegian Open AI Lab and focuses on machine learning, information visualization, and data representation learning. His work integrates techniques like neural attention models, nonnegative matrix factorization, and dimensionality reduction algorithms such as Neighbor Embedding (NE) for visualization. Yang's research has applications in bioinformatics, medical imaging, and engineering systems. His educational background includes advanced studies in pattern recognition and computational methods, though specific details are not provided. Research collaborations span institutions globally, including work on bacterial population genomics and chromosome classification. Key contributions include scalable optimization frameworks for visualization (NE) and novel clustering algorithms using graph random walks and low-rank matrix decompositions. Yang has developed software tools like ChordMixer for sequence processing and HSSNE for robust data visualization. His recent publications emphasize advancements in attention mechanisms, sparse factorization, and medical diagnostics. He actively contributes to open-source projects and collaborates with industry on applications like subsea pipeline inspection and energy scheduling systems.

• Cybersecurity
• Information Security
• Security Assurance
• +۷ مورد دیگر

Basel Cat is a Professor and Head of the Department of Information Security and Communication Technology at NTNU's Faculty of Information Technology and Electrical Engineering. His research focuses on cybersecurity, information security assurance, and innovative approaches to cyber range technologies. Key areas include vulnerability analysis, privacy protection, and AI-driven security solutions. Research Interests Cybersecurity incident triage and attack chain analysis Quantitative security evaluation models for web and cloud services Automated vulnerability injection in source code IoT security and cognitive digital twin architectures Adversarial AI applications in cybersecurity exercises Publications highlight advancements in cybersecurity education, attack-defense scenario modeling, and the integration of AI/LLMs in security frameworks. Recent work explores frameworks for evaluating cloud services and OWASP-aligned web application security standards. Collaborations involve development of hybrid IoT cyber ranges and frameworks for security assurance metrics. His research has been featured in top-tier journals like Computers & Security and Journal of Information Security and Applications .

• Machine Learning
• Recommender Systems
• Natural Language Processing
• +۳ مورد دیگر

Lemei Zhang is a Postdoctoral Fellow at the Norwegian University of Science and Technology (NTNU) in the Department of Computer Technology and Informatics. Their work focuses on advanced machine learning techniques for recommendation systems and social media analysis. Research interests include Deep learning architectures for news recommendation Aspect-based sentiment analysis in multilingual contexts Temporal and graph embedding methods for social recommendation Contextual augmentation in session-based systems Time series modeling for user interest prediction Creation of large-scale datasets like Adressa for media analytics Recent publications demonstrate a trajectory from foundational work on news recommendation datasets (2016-2017) to increasingly sophisticated neural approaches incorporating attention mechanisms, multimodal fusion, and real-time graph analysis across ACM Transactions, Machine Learning, and Human-Computer Studies venues.

• Software Engineering
• Agile Methodology
• Simulation and Modeling
• +۴ مورد دیگر

Arne Styve is an Associate Teaching Professor at the Department of Information and Communication Technology and Natural Sciences, Norwegian University of Science and Technology (NTNU). He serves as a Studyprogram coordinator for Computing Science and teaches object-oriented programming and system development at the Bachelor level, along with simulation and visualization at the Master level. Education: B.Eng. w/Hons (Sivilingeniør) in Microelectronics and Software Engineering, University of Newcastle upon Tyne Research Interests: Specializing in Agile development, simulation modeling, and technology education. His work focuses on programming pedagogy, digital twin applications, and co-simulation frameworks. Recent research explores integrating generative AI into critical thinking practices in programming courses. Publication Trends: His publications over the past decade demonstrate expertise in simulation modeling for maritime systems, educational technology innovations, and software engineering frameworks. Key themes include digital twins, flipped classroom methodologies, and cross-campus programming education. Teaching Contributions: Instructs courses including IDATA2505 (Practice-Based Learning), IDATT2003 (Programming 2), and IDATA2302 (Algorithms & Data Structures). His pedagogical approach combines industry experience with academic innovation. Industry Experience: Over 20 years in Norwegian IT industry, including roles at Offshore Simulator Center (OSC AS), developing advanced maritime simulators and command control systems for defense applications.

Leonora Onarheim Bergsjøمشاهده پروفایل

دانشیار

• Digital Ethics
• Artificial Intelligence
• Big Data
• +۷ مورد دیگر

Leonora Onarheim Bergsjø is an Associate Professor at Inland Norway University of Applied Sciences, specializing in digital ethics, artificial intelligence, and interdisciplinary research. She teaches digital judgment, ethics, and religious studies in teacher education programs, while also serving as a guest lecturer at institutions like the University of Oslo and MF University College. PhD from the University of Oslo Editor of 'Sensoriness and Transcendence: Perceptions, Revelations, and the Arts' (Brill, 2015) Author of 'Religious Citizenship: Disability, Equality and Human Perspectives' (Cappelen Damm, 2020) Her research focuses on ethical risk assessment of AI applications (ENACT project), e-health innovations (eCardiacRehab), and digital security frameworks. She leads the Norwegian Council for Digital Ethics (NORDE) and contributes to policy-making for authorities like the Ministry of Education and the Norwegian Institute of Public Health. Recent publications address algorithmic bias, ethical AI implementation, and metaverse ethics. She has received recognition for academic outreach, including a 2022 nomination for HiØ's Dissemination Award. Collaborates with international institutions on AI ethics Develops digital competence frameworks for kindergarten teachers Provides expert commentary on AI governance in media

• Educational Technology
• Science Education
• Physics Education
• +۵ مورد دیگر

Trond Morten Thorseth is an Associate Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU), Faculty of Natural Sciences. His research focuses on educational technology, science education, and innovative teaching methodologies. Thorseth's work explores the integration of student response systems, peer learning assessment tools, and mobile technologies into educational environments. He has published extensively on topics like classroom interaction, self-regulated learning, and interdisciplinary teaching approaches, with a particular emphasis on engineering and physics education. His recent publications (2022-2024) highlight strategies for enhancing student engagement through STS (Science, Technology, and Society) integration, analyzing feedback mechanisms in mathematics education, and bridging conceptual understanding gaps in physics and engineering classrooms. Earlier articles (2012-2017) focus on mobile learning, text-based response systems, and playful learning methodologies. Thorseth's research spans educational technology design, peer assessment frameworks, and pedagogical innovations. While no scientific awards are explicitly mentioned in the provided data, his work has been disseminated through academic conferences and journals like SEFI, IATED, and EDULEARN Proceedings.