جست‌وجوی استاد و پژوهشگر

• Next Generation Internet
• Human-centric Networking
• Ontology and Knowledge-based Management
• +۱۳ مورد دیگر

David Palma 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). His research focuses on next-generation networking paradigms, including intent-based networking , knowledge-driven management , and IoT device automation . Key research interests include: Human-centric Internet of Things (IoT) Ontology-based network management Cloud/Edge/Fog computing for IoT Arctic and satellite communication 5G integration in smart grids His recent publications (2024-2019) highlight trends in knowledge graphs for network compliance, XR applications in critical sectors, UAV-based emergency networks , and 5G-enabled smart grid protection . Articles also explore Arctic connectivity via satellite swarms and energy-efficient IoT management.

• Control Systems
• Robotics
• Power Systems
• +۲ مورد دیگر

Professor Damiano Varagnolo is affiliated with the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU), where he conducts research spanning control systems, robotics, power systems, and data-driven modeling. His work bridges theoretical advances with practical applications in underwater vehicles, medical rehabilitation, and energy infrastructure. His research focuses on: Development of formation control algorithms for autonomous underwater vehicles (AUVs) and snake robots Transient stability enhancement for grid-forming converters in renewable energy systems Data-driven modeling of physiological signals for wheelchair propulsion and industrial processes Distributed optimization for underwater communication networks Recent publications (2024-2025) demonstrate strong emphasis on: Underactuated vehicle control using hand position concepts Energy expenditure estimation through physiological signal processing Consensus protocols for JANUS-based underwater networks Educational innovation through control-themed outreach initiatives like the Advent Calendar project He actively collaborates with NTNU colleagues across engineering disciplines and contributes to curriculum development through graph-theoretic approaches for educational coherence.

• Building Information Modeling (BIM)
• Digital Twins
• Construction Management
• +۳ مورد دیگر

Eilif Hjelseth is a Professor at the Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), with a focus on Building Information Modeling (BIM), Digital Twins, and Construction Technology. His work spans digital transformation in the AECO industry, automated compliance checking, and sustainable construction practices. Role: Professor, Department of Civil and Environmental Engineering University: Norwegian University of Science and Technology (NTNU) Research: BIM, Digital Twins, Construction Automation, Sustainable Development, Semantic Modeling Outreach: Authored multiple textbooks and reports on VDC implementation and BIM standards His recent publications emphasize digital twin frameworks , semantic data integration , and automation in construction , particularly through cross-validation, knowledge graphs, and circular economy applications. While specific educational details or grants aren't mentioned, his work demonstrates extensive collaboration with researchers across Norway and Europe on digitalization challenges. Key trends in his 2024–2025 articles include cross-domain BIM integration , deep learning for component classification , and standardization of digital product passports . Earlier works (2012–2020) established foundational concepts in BIM model checking, lifecycle costing, and regulatory digitization.

Vladimir Mironovمشاهده پروفایل

پژوهشگر

• Semantic Web Technologies
• Systems Biology
• Bioinformatics
• +۳ مورد دیگر

Vladimir Mironov is a Senior Scientist at the Norwegian University of Science and Technology (NTNU), specializing in Semantic Web technologies and their application in systems biology and bioinformatics. His work focuses on knowledge graph integration, biological data modeling, and semantic network construction. Email: vladimir.mironov@ntnu.no Email: vladimir.n.moronov@gmail.com His research interests include: Development of Semantic Web tools for gene regulatory network analysis Ontology engineering for biological knowledge management Integration of chromosome location data with functional genomics Triple store evaluation for biological datasets Recent publications highlight his contributions to: Knowledge graph frameworks for gene regulation Network analysis tools in bioinformatics Ammonia-tolerant microbial communities in biotechnology Orthology prediction algorithms Semantic data modeling for biological datasets He has actively contributed to projects like DrugLogics and Crossover Research since 2008, developing semantic tools for biomedical research, including the Cytoscape BioGateway App and Cell Cycle Ontology (CCO).

• 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 .

Johan Pensarمشاهده پروفایل

دانشیار

• Statistical Machine Learning
• Probabilistic Graphical Models
• Causal Learning
• +۳ مورد دیگر

Johan Pensar is an Associate Professor of Statistics and Data Science at the University of Oslo's Department of Mathematics. He holds a PhD from Åbo Akademi University (2016) and was a postdoc at the University of Helsinki (2016–2020). His research focuses on statistical machine learning, probabilistic graphical models, causal inference, and applications in genomics. He has supervised multiple PhD students and co-supervised others in interdisciplinary projects, including causal modeling in healthcare and machine learning for microbiology. Education: PhD in Statistics, Åbo Akademi University, 2016 Postdoctoral Researcher, University of Helsinki, 2016–2020 Research Interests: Pensar's work integrates statistical theory with practical applications. Key areas include developing methods for causal discovery, probabilistic graphical models (e.g., Bayesian networks), and their use in genomics and healthcare. He emphasizes interpretable machine learning and robust statistical frameworks for complex data. Publications: Recent work spans causal inference, microbial genome analysis, and housing market prediction. His methods address challenges like confounding bias, generalization in ML, and uncertainty quantification in valuation models. Awards: Finnish Statistical Society Doctoral Thesis Award (2013–2016) Teaching & Advising: Pensar teaches advanced courses in statistical learning and probabilistic graphical models. He advises PhD students on causal modeling, ML in healthcare, and data science applications. He collaborates with industry partners like Integreat and Eiendomsverdi AS. Lab/Teams: He is affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) and leads research on Bayesian methods in ML.

Martin Georg Skjævelandمشاهده پروفایل

پژوهشگر

• Semantic Web
• Ontology Engineering
• Data Integration
• +۳ مورد دیگر

Martin Georg Skjæveland is a **Researcher (permanent position)** at the **Department of Informatics, University of Oslo**, and an **Adjunct Associate Professor in Data Science** at the **University of Stavanger**. His work focuses on semantic web technologies, ontology engineering, and data integration. He holds a PhD from the University of Oslo (2015) and has extensive postdoctoral and research experience in informatics. **Education**: PhD in Informatics, University of Oslo (2015) Master in Informatics, University of Oslo (2006) Bachelor in Natural Sciences, University of Bergen (2004) **Research Interests**: Skjæveland specializes in ontology engineering tools like **Lutra (OTTR)** and **Sgvizler**, which support ontology template instantiation and semantic data visualization. His work addresses challenges in data integration, semantic web applications, and industrial data management. Recent projects include developing frameworks for personal knowledge graphs (PKG) and ontology-based data access (OBDA). **Publications**: Over 30 peer-reviewed articles, with recent focus on ontology patterns (**OTTR**), personal knowledge graphs, and industrial data integration. His contributions span journals like *AI Open*, *Semantic Web Journal*, and conferences like ISWC and WWW. **Labs/Projects**: Leads the **Optique** project (ontology-based data access), co-develops **OTTR** templates, and contributes to tools like **Sgvizler** for SPARQL visualization.

• Programming models
• Formal methods
• Distributed systems
• +۳ مورد دیگر

Einar Broch Johnsen is a Professor at the Department of Informatics, University of Oslo. His research focuses on programming models, formal methods, and distributed systems, with significant contributions to languages like ABS and SMOL. He has led major projects including the Sirius Center (2015-2023) and EU initiatives Envisage and HyVar. His work spans asynchronous systems, cloud computing, and digital twins, emphasizing rigorous verification techniques. Recent publications show a trend toward AI integration, robotics, and knowledge-based systems, blending formal methods with practical applications in autonomous decision-making and semantic validation. Johnsen holds editorial and committee roles for journals including Formal Aspects of Computing and conferences like FASE and iFM. He teaches courses on computability and concurrency models, advancing both theoretical and applied aspects of software engineering.

Ahmet Soyluمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Semantic Web
• Data Integration
• +۳ مورد دیگر

Ahmet Soylu is Associate Professor in Data and Knowledge Management at the University of Oslo. His research develops semantic technologies and knowledge systems for applications in healthcare, cloud computing, and industrial domains. Research Focus Creates knowledge graph systems for data integration and analysis, with applications in medical diagnostics (cancer/brain tumor classification), cloud cost optimization, and industrial monitoring systems. Develops transformer-based models for SQL recommendation and data linking. Publication Trends Recent work shows strong emphasis on healthcare AI (particularly cancer diagnostics), cloud storage optimization, knowledge graph embeddings, and industrial applications at Bosch. Increasing focus on imbalanced learning techniques for medical data. Project Leadership Developed Koala-UI for tabular data linking Semantic systems for Bosch welding quality monitoring Open energy management systems for EV charging

Evgeny Kharlamovمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Knowledge Representation
• Machine Learning
• +۳ مورد دیگر

Evgeny Kharlamov is an Associate Professor at the University of Oslo and Senior Research Expert at Bosch AI. His research focuses on Neuro-Symbolic AI, Knowledge Representation (knowledge graphs, rules, ontologies), data integration, and applications in manufacturing, energy, and corporate intelligence. He has published over 190 papers in venues like IJCAI, AAAI, WWW, and holds an h-index of 41 with ~6K citations. Key awards include ranking 7th in the AI 2000 Knowledge Engineering list (2024) and top 111 German AI researchers (2023). **Education & Previous Roles**: Previously held positions at the Universities of Oxford and Bozen-Bolzano, INRIA Saclay, and Telecom Paris. His expertise spans individual research to managing teams at Bosch AI and coordinating a research center at the University of Oslo. He raised ~6.7M EUR in EU/UK research funding and led multiple large-scale EU projects. **Research Interests**: Combines theoretical advances in AI with industrial applications, emphasizing explainable and scalable solutions. Key areas include knowledge graphs, semantic web technologies, and LLM-centered systems like RAG. **Awards**: Notable recognitions include the 2020 Best Research Paper Award at ESWC, multiple ISWC awards (2015–2017), and IBM’s Best Master’s Thesis Award (2008). His PhD thesis was honored by AI*IA (2012). **Grants & Projects**: Co-secured ~6.7M EUR in funding. Led projects in semantic data integration (e.g., Siemens streaming data), digital twins, and predictive quality monitoring in manufacturing. **Teaching**: Taught courses on Digital Ecosystems (2024), Semantic Web (2023), Knowledge Graphs (2023), and Foundations of Databases (2007). **Labs/Teams**: Active in Bosch AI’s research initiatives and the University of Oslo’s data science teams, focusing on industrial AI applications.

• Cloud computing
• Cybersecurity
• Software Engineering
• +۷ مورد دیگر

Paal Engelstad is a Professor at Oslo Metropolitan University's Faculty of Technology, Art and Design, Department of Computer Science. His research focuses on Cloud computing , Cybersecurity , and Software Engineering , with significant contributions to Graph Neural Networks (GNNs) and their applications in network analysis, renewable energy forecasting, and telecom systems. Research interests span Applied Artificial Intelligence and Autonomous Systems and Networks . Recent publications address spatio-temporal wind forecasting , GNN propagation schemes , and 5G network security . He contributes to advancements in renewable energy integration and telecom protocol analysis .

Leon Moonenمشاهده پروفایل

استاد پژوهشی

• 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.

Anamaria Costacheمشاهده پروفایل

دانشیار

• Fully Homomorphic Encryption
• Privacy-Preserving Machine Learning
• Lattice-Based Cryptography
• +۳ مورد دیگر

Anamaria Costache is an Associate Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Information Security and Communication Technology. Previously, she held roles including a postdoc at Royal Holloway, University of London (RHUL), a Research Scientist at Intel AI Research, and a part-time position at Intel. She earned her PhD from the University of Bristol and undergraduate/master's degrees from the University of Warwick, focusing on number theory and algebraic structures like Brauer Groups. Her research interests center on fully homomorphic encryption (FHE), privacy-preserving machine learning, lattice-based cryptography, and post-quantum security protocols. Her work is supported by Intel, addressing challenges in secure computation on encrypted data. She has authored numerous publications in top venues like CRYPTO, PKC, and IEEE conferences, focusing on FHE optimizations, biometric systems, and cryptographic security analyses. Teaching includes courses on applied cryptography, network security, and quantum-safe encryption at NTNU. She co-chairs NIKT 2019 and the WAHC workshops (2022–2024), and serves on editorial boards for journals like IACR Communications in Cryptology. She actively participates in program committees for conferences such as MathCrypt and FHE.org. Professional service includes the Lattigo Advisory Committee and contributions to the Bristol Crypto Blog. Her current projects emphasize verifiable computation over encrypted data and resilient authentication mechanisms in biometric systems.

Marija Slavkovikمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Ethics
• Computational Social Choice
• +۴ مورد دیگر

Marija Slavkovik is a Professor at the Department of Information Science and Media Studies, Faculty of Social Sciences, University of Bergen. She serves as Head of Department and is a leading researcher in artificial intelligence, with expertise in multi-agent systems, machine ethics, and computational social choice. Research Interests: Focuses on automating moral reasoning, ethical behavior in computational agents, and trust in algorithmic decision-making within public institutions. Grants: Leading applications for ERC Synergy Grants and managing ongoing projects like MediaFutures and Better Video Workflows via AI Techniques. Outreach: A vocal advocate for responsible AI, she participates in public debates and media discussions on AI's societal impact. Supervision: Advises doctoral students Than Htut Soe and Mina Young Pedersen, with past co-supervision of Flavio Tisi, Einar Søreide Johansen, and Hanna Kubacka. Scientific Awards: Received the Best Paper award at Norsk Informatikkonferanse 2020 for bias mitigation studies. Her work bridges logic, ethics, and AI, emphasizing societal trust, fairness, and interdisciplinary collaboration. She co-organizes Dagstuhl Seminars and serves on the editorial board of AI Magazine.

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.