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Svein Ketil JacobsenView profile

Professor

• Ultrasound Technology
• Microwave Radiometry
• Optics
• +5 more

Svein Ketil Jacobsen is a Professor at the Department of Physics and Technology, UiT The Arctic University of Norway in Tromsø. He specializes in applied physics with a focus on Ultrasound, Microwaves, and Optics. His research bridges medical technology and environmental sensing, with affiliations to the university's research group on these topics. Research interests include: Remote sensing technology : Drone-mounted radar systems for snowpack analysis and avalanche research Biomedical instrumentation : Microwave radiometry for non-invasive diagnostics and hyperthermia treatment Ultrasonic systems : High-frequency transducer design and signal processing techniques Antenna design : Optimized microwave antennas for medical and environmental applications His publication trends show a shift from foundational biomedical microwave work (2001-2012) toward drone-based environmental sensing in recent years (2016-2021). Earlier research focused on medical thermometry, bladder diagnostics, and ultrasonic systems, while recent innovations involve UWB radar for snow hydrology and Arctic monitoring. Professor Jacobsen maintains active laboratory facilities at the Technology Building in Tromsø (Room 2.054), conducting experimental work in microwave and ultrasonic technologies.

Leon MoonenView profile

Research Professor

• Security and Resilience in Software Systems
• Self-Healing and Self-Adaptive Software
• Applications of Machine Learning in Software Engineering
• +6 more

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.

• Scientific Computing
• Applied mathematics
• Numerical methods
• +2 more

Marie E. Rognes is a Chief Research Scientist at Simula Research Laboratory's Numerical Analysis and Scientific Computing department. She specializes in computational mathematics and biomedical modeling, particularly focusing on cerebral fluid dynamics, electrodiffusion, and poroelasticity. Her work bridges advanced numerical methods with clinical applications in neuroscience. Research Pillars: Brain waterscape modeling, finite element methods, and biophysical simulations Software Leadership: Key contributor to FEniCS and Dolfin-adjoint projects Application Domains: Neurodegenerative diseases, cardiac electrophysiology, and personalized medicine Recent publications reveal methodological innovations in perivascular flow modeling , ionic transport simulations , and multi-scale brain mechanics . Her work on glymphatic system dynamics and cardiac tissue modeling demonstrates cross-disciplinary impact. While no explicit awards are listed, her extensive publication record in top-tier computational journals (SIAM, PLOS, Nature Computational Science) and invited talks at premier conferences (SIAM, ECCOMAS, FEniCS workshops) establish her as a leading figure in biomedical computing.

Anamaria CostacheView profile

Associate Professor

• Fully Homomorphic Encryption
• Privacy-Preserving Machine Learning
• Lattice-Based Cryptography
• +3 more

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.

Stephan OepenView profile

Professor

• Computational Linguistics
• Natural Language Processing
• Language Technology
• +3 more

Stephan Oepen is a Professor at the Department of Informatics, University of Oslo, specializing in Computational Linguistics and Natural Language Processing (NLP). He leads the Research Group for Language Technology and serves as Academic Chair in Artificial Intelligence for the Circle U European University Alliance. His research bridges formal linguistics with large-scale computation, focusing on semantic parsing, dependency structures, and multilingual language models. 2002–present: Researcher → Professor at UiO 2011–2017: Head of Language Technology Research Group 2019–20: Section Head for Machine Learning 2021–24: Department Head for Informatics Current projects include HPLT (High-Performance Language Technologies), Nordic Language Processing Laboratory (NLPL), and OpenEuroLLM . He co-directs the 2017 ACL Shared Task on Extrinsic Parser Evaluation and contributes to international NLP conferences like ACL, EMNLP, and CoNLL. Recent publications focus on: Uniform semantic graph representations Hybrid parsing architectures Continual training for small languages Diagnostic parser evaluation Copyright implications in LLMs Community language resource infrastructure He actively participates in editorial boards and technical coordination roles, including the LUMI Scientific Advisory Group and Horizon Europe's High-Performance Language Technologies project.

Yngvar BergView profile

Professor

• Nanoelectronics
• Bionanoprotonics
• Low-Voltage CMOS Circuits
• +3 more

Yngvar Berg is a Professor at the University of Oslo's Department of Informatics, affiliated with the Faculty of Mathematics and Natural Sciences and the Nanoelectronics (NANO) research group. His work focuses on nanoelectronic systems, low-voltage CMOS circuit design, and educational technology. He holds a formal title of Professor and is based at Ole-Johan Dahls hus in Oslo. His research emphasizes analog and digital circuit design for ultra-low voltage applications, including floating-gate amplifiers, MEMS sensors, and energy-efficient systems. He has contributed to advancements in sensor front-ends, oscillator stability, and bidirectional transducer interfaces. Recent work also explores peer assessment methodologies in computer science education, emphasizing formative feedback and gamification for student engagement. Berg's publications span IEEE conferences (ICNSC, NEWCAS, ISMVL) and journals like Electronics and Sensors . His technical contributions include innovations in semi-floating gate amplifiers, Q-loading for particulate matter sensors, and curriculum design for first-year engineering students. His professional affiliations include the IEEE, and he actively collaborates with researchers like Mehdi Azadmehr and Omid Mirmotahari. Current research themes include bionanoprotonics, low-power CMOS integration, and technology-enhanced learning environments.

Phuong H. HaView profile

Professor

• Green Computing
• Energy-Efficient Systems
• Machine Learning
• +4 more

Phuong H. Ha is a Professor at the Department of Computer Science, The Arctic University of Norway (UiT), located in Tromsø, Norway. He leads the Arctic Green Computing Group and is affiliated with the Faculty of Science and Technology. His research focuses on energy-efficient computing systems, machine learning, parallel programming, and cyber-physical systems. He holds a Ph.D. from Chalmers University of Technology (Sweden). Key roles include leading EU-funded projects such as EXCESS (FP7) and TAILOR (H2020), as well as national projects like PREAPP and eX3. He has pioneered research in energy informatics, edge intelligence, and parallel programming systems. His work emphasizes sustainable energy solutions and efficient resource management in distributed systems. Teaching responsibilities include courses on Green Computing, Operating Systems, and Parallel Programming. He has developed innovative frameworks for energy harvesting in wireless devices and contributed to Arctic observational systems through projects like the Arctic Observatory (DAO). Research highlights include over 30 peer-reviewed publications in top venues like IEEE Transactions on Parallel and Distributed Systems and Journal of Parallel and Distributed Computing. His work bridges theoretical foundations with practical applications in smart grids, IoT, and environmental monitoring.

• Hydrodynamics
• Sediment Transport
• Hydraulic Structures
• +7 more

Elena Marianne Pummer is a Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Civil and Environmental Engineering and the Faculty of Engineering. She holds a Dr.-Ing. from RWTH Aachen University (2016) and a Dipl.-Wirtsch.-Ing. from TU Darmstadt (2011). Her research focuses on hydrodynamics, sediment transport, hydraulic structures, and geomorphological processes. She leads projects like RenewHydro (sediment handling), HydroCen (hydropower innovation), and InSpillyFish (spillway improvements with fish passage). Notably, she investigates GLOF hydraulics, underground pumped storage plants, and culvert blockage dynamics. Pummer has supervised PhD students including Jan Hrebrina and Nils Solheim, and previously advised Subhojit Kadia and Joakim Sellevold. Her awards include the Friedrich-Wilhelm Award (2017), ICOLD Young Engineers Award (2017), and the DTK & WasserWirtschaft Prize (2019). She contributes to committees like IAHR’s Hydraulic Structures and EERA Hydropower initiatives. Her work spans experimental modeling, CFD simulations, and policy-driven hydropower modernization.

• Molecular Biology
• DNA Repair
• Genome Stability
• +5 more

Henrik Peter Sahlin Pettersen is an Associate Professor at the Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU). His research focuses on molecular mechanisms of DNA repair, cancer biology, and applications of digital pathology. He is affiliated with the Molecular Biology research group (http://www.ntnu.no/dmf/ikm/molbiol) and the DNA Repair and Genome Stability group (http://www.ntnu.no/dmf/ikm/dna-r). His work spans interdisciplinary areas including: Genomic instability and mutagenesis in cancer Role of tumor-associated macrophages in meningiomas Development of AI-driven tools for histopathological analysis Quantitative immunohistochemistry methods Recent studies highlight contributions to: IBD treatment mechanisms using patient-derived colonoids Disease differentiation in inflammatory bowel diseases through T-cell analysis Automated breast cancer segmentation techniques He actively collaborates across disciplines, integrating molecular biology with computational pathology solutions. His presentations at international conferences reflect commitment to advancing translational research in oncology and digital diagnostics.

Ana Isabel Silva MartinsView profile

Researcher

• CMB
• Gravitational Waves
• Machine Learning
• +1 more

Ana Isabel Silva Martins is a Doctoral Research Fellow at the University of Oslo's Faculty of Mathematics and Natural Sciences , affiliated with the Department of Astrophysics. Her research focuses on cosmology, gravitational waves, and machine learning applications in high-performance computing. Education: MSc in Experimental Physics (2022-2024), Utrecht University BSc in Engineering Physics (2019-2022), Instituto Superior Técnico, University of Lisbon Research Interests: She explores early detection mechanisms for gravitational wave signals from binary neutron star coalescence, leveraging convolutional neural networks (CNNs) and field-programmable gate arrays (FPGAs). Her work bridges astrophysics, machine learning, and computational hardware optimization. Projects & Groups: Active in the CMB&CO group , Cosmoglobe , and CosmoglobeHD . Collaborates on cosmology and extragalactic astronomy research.

• Structural Dynamics
• Railway Structural Dynamics
• Structural Health Monitoring
• +7 more

Anders Rønnquist is a Professor and Head of the Department of Structural Engineering at NTNU’s Faculty of Engineering Science. His research focuses on structural dynamics, railway systems, and bridge engineering. He leads projects on structural health monitoring, wind engineering, and architectural collaboration in structural design. Key collaborations include work with KTH Stockholm, Vilnius University, and the University of Porto. He teaches courses such as Structural Dynamics, Steel Structures II, and Railway Catenary Systems. His work integrates advanced sensor technologies, machine learning, and probabilistic methods to address challenges in infrastructure longevity and safety. Research interests span structural monitoring, overhead contact line dynamics, and reliability assessments. Notable contributions include the development of Kalman filter-based systems for crosswind load identification and shape grammar approaches for architectural-structural design integration. His team has pioneered non-contact measurement techniques using digital image correlation and advanced neural networks for bridge rivet inspection. Publications highlight innovations in railway catenary optimization, timber structure dynamics, and probabilistic fatigue analysis. His work emphasizes interdisciplinary approaches, bridging engineering and architectural disciplines to enhance sustainable infrastructure solutions.

• Concrete Technology
• Cementitious Materials
• Rheology of Cement Pastes
• +5 more

Rolands Cepuritis is an Associate Professor at the Department of Structural Engineering , Norwegian University of Science and Technology (NTNU) . With over 20 years of international experience in cement production, concrete technology, and academia, his research focuses on sustainable concrete materials and advanced rheological modeling. Research Highlights: Leading MiKS (Microproportioning with Crushed Sand) project to optimize crushed sand in concrete Coordinating COIN (High Quality Manufactured Sand) initiatives Developing the FlowCyl one-parameter rheology test for cement paste Investigating calcium sulfoaluminate binders for carbonation resistance Advancing steel fiber-reinforced concrete for thin overlays Publication Trends: Recent work emphasizes manufactured sand optimization, rheological modeling with neural networks, acid resistance of novel binders, and sustainable tunnel lining solutions via SUPERCON project. Contact: Email: rolands.cepuritis@ntnu.no Office: Materialteknisk, 3-202, Gløshaugen, Richard Birkelands vei 1a, Norway

Tengjiao JiangView profile

Researcher

• Computer Vision
• Machine Learning
• Structural Health Monitoring
• +2 more

Tengjiao Jiang is a Researcher at the Department of Structural Engineering , Faculty of Engineering , Norwegian University of Science and Technology (NTNU) . Their work focuses on computer vision and deep learning applications for structural monitoring of transportation infrastructure. Research Interests : Computer Vision (CV) Machine Learning (ML) Optical Measurement Structural Health Monitoring (SHM) Condition Assessment of Transportation Infrastructures Recent Research Trends : Their publications (2020–2025) emphasize computer vision systems for railway and bridge monitoring, including uplift measurement, corrosion detection, displacement analysis, and damage assessment using CNNs and transformers. Key methods involve IMU sensors, line tracking, photogrammetry, and 3D reconstruction. Scientific Awards : Best Paper Award at IMAC-XLII conference (Jan 2024) Olympiad Medal in Olympiad in Engineering Science (May 2023) Supervision : Co-supervises PhD student Ziyue Lu (2022–present) and has co-supervised multiple Master’s students on topics like vision-based bridge inspection, modal identification, and vibration response analysis. Labs & Outreach : Conducts field tests on the Oslo Airport Line with vision-based monitoring systems.

• Autonomous Ships
• Maritime Cybernetics
• Collision Avoidance
• +5 more

Morten Breivik is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), and an affiliated researcher at NTNU's SFI Autoship. His work spans autonomous maritime technology, societal cybernetics, and coastal development initiatives. 2016-2024: Member of Teknologirådet 2013-2021: Former Head of Department (Instituttleder) at NTNU's Department of Engineering Cybernetics 2013-2023: Associated researcher at NTNU's SFF AMOS Breivik leads cutting-edge research in autonomous ship technology, including: World's first autonomous electric ferries for urban waterways (Zeabuz spin-off) Revitalizing Norwegian coastal regions through technology-driven solutions Developing Nyhavna 5.0 as a high-tech maritime cluster Founding the new discipline of Societal Cybernetics His work focuses on autonomous vessels with 15+ recent publications covering collision avoidance, trajectory planning, docking control, and human-machine teaming. The research integrates control systems, maritime autonomy, and urban transport optimization. Projects include: Autoteaming : Human-machine collaboration for autonomous ferry operations Kystutviklingssenter : Government-funded coastal development pilot in Kirkenes Nyhavna 5.0 : High-tech maritime cluster in Trondheim Societal Cybernetics : Modeling complex societal phenomena

• Membrane Technology
• Gas Separation
• Carbon Capture
• +4 more

Arne Lindbråthen is a Researcher in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU), Faculty of Natural Sciences. His work centers on membrane technology development for gas separation applications, with focus on CO 2 removal from flue gas, biogas, and natural gas streams, as well as natural gas dehydration and hydrogen purification. His research interests span membrane technology development, carbon capture, and gas separation processes. Lindbråthen specializes in manufacturing carbon molecular sieve membranes, from polymer solution optimization to pilot-scale testing. His work integrates materials science with process engineering for applications in carbon capture, biogas upgrading, and hydrogen purification. Key focus areas include membrane stability under harsh conditions (H 2 S, moisture), techno-economic assessments, and scaling lab innovations to industrial pilots. Lindbråthen's publication record shows strong collaboration with the MEMFO research group, particularly with Liyuan Deng, Linfeng Lei, and May-Britt Hagg. His work demonstrates consistent contributions to CO 2 separation membrane development since the early 2000s, with recent emphasis on moisture-swing adsorption, mixed matrix membranes, and field trials in industrial settings like cement plants. His research bridges fundamental membrane science with practical engineering solutions for decarbonization. His laboratory work includes pilot-scale production of carbon hollow fiber membranes and testing under high-pressure, high-temperature conditions. The MEMFO group, where he is active, maintains long-term focus on reducing carbon emissions through membrane-based separation technologies, with documented field trials in demanding industrial environments.