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Anne H Schistad SolbergView profile

Professor

• Machine Learning
• Deep Learning
• Image Analysis
• +6 more

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.

• Marine Propulsion Systems
• Hydrodynamics of High-Speed Vehicles
• Ship Performance Analysis
• +6 more

Sverre Steen is a Professor and Head of the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). He leads the Kongsberg Maritime University Technology Centre focused on 'Ship Performance and Cyber-physical Systems' and is a member of the standing committee for the Symposium of Marine Propulsors. His research emphasizes ship propulsion, hydrodynamics, and big data analysis of in-service vessel performance. Key interests include seakeeping, high-speed marine vehicles, and model testing techniques. Steen teaches TMR 4217 Hydrodynamics of High-Speed Marine Vehicles , covering cavitation, experimental hydrodynamics, and propulsion systems. He collaborates internationally on projects like the Norwegian Ocean Technology Centre. His recent work explores wave-energy extraction via hydrofoil vessels, resistance modeling for fast ferries, and propulsion efficiency in real sea states. He has contributed to global shipping emission models (MariTEAM) and reliability analysis of structural components under vibration. Steen's publications span propulsion in waves, engine-propeller dynamics, and data-driven methods for ship performance monitoring. His applied research bridges experimental testing and computational modeling to address challenges in sustainable maritime transport and operational safety.

• Marine Renewable Energy
• Wind Turbine Drivetrain Systems
• Condition Monitoring
• +5 more

Amir R. Nejad is a Professor at the Department of Marine Technology, NTNU, and leads the Marine Energy Systems and Autonomics (MESA) research group. He chairs the EAWE WindEurope Scientific Track Committee and co-founded the Drivetrain Technical Committee at the European Academy of Wind Energy (EAWE). He is also involved in ISO committees, editorial boards of journals like Wind Energy Science , and contributes to standards for offshore wind energy. Education: Ph.D. in Marine Technology, NTNU (top 10% international ranking) M.Sc. Subsea Engineering, University of Aberdeen (Distinction) B.Sc. Mechanical Engineering, Tehran University (Honors) Research Interests: Focus on stochastic and reliability-based design, dynamic modeling of electro-mechanical systems, fault detection, and condition monitoring in marine and offshore renewable energy applications. Key areas include wind turbine drivetrains, floating offshore systems, and digital twin technology. Awards: 2x Best Lecturer, NTNU (2015-2016, 2019-2020) Best Poster Award, Torque Conference 2016 Nowitech Ph.D. Fellowship, 2012-2015 Advising & Grants: Supervises Ph.D. students in drivetrain design and offshore systems. Leads projects on marine system dynamics and vibration through the MD Lab. Collaborates with industry on drivetrain testing and reliability. Labs & Teams: Director of the Marine System Dynamics and Vibration Lab (MD Lab), fostering innovation in offshore renewable energy systems and digital twin applications.

• Machine Learning
• Graph Neural Networks
• Time Series Analysis
• +7 more

Filippo Maria Bianchi is an Associate Professor in the Department of Mathematics and Statistics at UiT The Arctic University of Norway, where he conducts research at the intersection of machine learning, dynamical systems, and complex networks. He is also a Senior Researcher at NORCE Norwegian Research Centre and actively contributes to the IEEE Task Force on Learning for Structured Data and the ELLIS Society. Department: Department of Mathematics and Statistics School: Faculty of Science and Technology University: UiT The Arctic University of Norway Adjunct Position: Senior Researcher, NORCE Education: Bachelor’s in Computer Engineering, Sapienza University of Rome Master’s in Artificial Intelligence & Robotics, Sapienza University of Rome (cum laude, 2012) PhD in Machine Learning, Sapienza University of Rome His research focuses on graph machine learning, time series analysis, reservoir computing, and probabilistic forecasting , with applications in energy analytics and remote sensing. He has led and contributed to numerous projects involving Arctic power grids, satellite-based environmental monitoring, and deep learning for sustainability. The recent publications reflect a strong trend in graph neural networks —particularly pooling mechanisms, spatiotemporal modeling, and explainability—alongside applications in energy forecasting, avalanche detection, and remote sensing . His work combines theoretical innovation with real-world impact, especially in Arctic and remote environments. Scientific Affiliations and Leadership: Vice-Chair, IEEE Task Force on Learning for Structured Data Member, ELLIS Society Co-founder, Northernmost Graph Machine Learning group Member, IEEE Task Force on Reservoir Computing Visiting Professor, Politecnico di Milano (2024–2025) He actively mentors students and collaborates on interdisciplinary research. He has led projects in power grid reliability, solar fault detection, and unsupervised change detection in satellite imagery . His work is supported by open-source implementations and reproducible research practices. Laboratories and Research Groups: Northernmost Graph Machine Learning group (co-founder) ARC Research Group, UiT Graph Machine Learning Group, Lugano

Ronny SchererView profile

Professor

• Meta-analysis
• Educational Measurement
• Digital Divides
• +6 more

Ronny Scherer is Center Director and Professor at CEMO (Center for Educational Measurement) and Deputy Director at CREATE (Center for Research on Equality in Education) at the University of Oslo's Faculty of Educational Sciences. His work bridges educational measurement, assessment, and evaluation with a focus on research syntheses and complex sampling surveys. Dr. Scherer's research spans two interconnected domains: substantive areas including digital divides, equity and equality in education, and measurement of complex cognitive skills (such as complex problem solving, adaptability, computational thinking, and executive functioning); and methodological areas focusing on advanced meta-analytic techniques, multilevel structural equation modeling, and spatial analysis of complex survey data. His work frequently utilizes international large-scale assessment data from PISA, ICILS, TIMSS, PIRLS, PIAAC, and TALIS. His publication record demonstrates a clear trajectory toward increasingly sophisticated meta-analytic approaches, with recent work focusing on second-order meta-analyses, AI-assisted screening methods, and advanced techniques for handling complex survey data. His research consistently addresses critical educational challenges related to equity, digital literacy, and measurement of 21st century skills. Dr. Scherer has secured significant research funding for projects including ARISE (Academic resilience in mathematics and science among vulnerable students), DiDiRes (Digital inequalities in education), and ADAPT21 (Educational assessments of the 21st century: Measuring and understanding students' adaptability in complex problem solving situations). Co-director of CREATE (Centre for Research on Equality in Education) since 2023 Professor of Educational Assessment and Measurement at CEMO since 2019 Extensive experience with international large-scale assessments including ICILS, TALIS, and PIAAC As an educator, Dr. Scherer teaches advanced courses in measurement models, multilevel models, meta-analysis, and equity in education. He actively supervises graduate students interested in his research areas and has developed numerous workshops on structural equation modeling and meta-analytic methods for international audiences.

• Risk Management
• Risk Analysis
• Uncertainty Quantification
• +12 more

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.

• Wireless Communications
• Machine Learning
• Digital Twins
• +5 more

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).

Marco SeeberView profile

Professor

• Public Policy
• Higher Education Governance
• Research Evaluation
• +5 more

Marco Seeber is a Professor at the University of Agder's Department of Political Science and Management. He holds a PhD from the University of Chieti Pescara (Italy) and has previously worked at the University of Lugano (Switzerland) and Ghent University (Belgium). His research focuses on public policy, governance, and management with specialization in higher education systems, research evaluation, and science policy. Professor Seeber's research examines policy implementation, research metrics, peer review systems, academic careers, internationalization, and interdisciplinarity in higher education. He employs comparative and quantitative methodologies to analyze governance structures and policy impacts across different educational systems. He has received significant recognition including the Swiss Prize for Research in Education (2019) and fellowships from IEEE, AIUM, and AIMBE. As Co-Editor-in-Chief of the European Journal of Higher Education, he shapes scholarly discourse in his field. He currently coordinates the Horizon CSA project IANUS (2025-) and leads courses in organizational theory, research methodology, and leadership.

Eduard KamburjanView profile

Researcher

• Digital Twins
• Formal Methods
• Hybrid Systems Verification
• +5 more

Eduard Kamburjan is a Researcher at the University of Oslo , affiliated with the Reliable Systems (PSY) and Data and Knowledge Systems (DKM) research groups. His work bridges formal methods , digital twin engineering , and knowledge graph applications . Research interests include: Formal verification of hybrid systems using deductive methods Digital twin architecture with compositional correctness guarantees Semantic lifting and ontology-driven modeling for complex systems Concurrency analysis and non-determinism in program verification Interactive visualization as serious games for formal methods His 2024-2023 publications demonstrate expertise in digital twin reconfiguration , semantic interoperability , and knowledge-based runtime enforcement . Key contributions include Crowbar for active object verification and ABS simulator toolchain for model-driven engineering. Collaborations span institutions like Springer , ACM , and IEEE , with work featured in Lecture Notes in Computer Science (LNCS) , Software and Systems Modeling (SoSyM) , and Science of Computer Programming . His research integrates RDF data management , behavioral contracts , and modular analysis for distributed systems.

• Marine Renewable Energy
• Wind Energy Systems
• Drivetrain Design and Reliability
• +7 more

Amir R. Nejad is a Professor in the Department of Marine Technology at NTNU, leading the Marine Energy Systems and Autonomics (MESA) research group. He holds roles such as Chair of the EAWE WindEurope Scientific Track Committee and co-chair of the Drivetrain Technical Committee at the European Academy of Wind Energy (EAWE). His research focuses on stochastic design, reliability-based operation, dynamic modeling, and fault detection in marine and offshore renewable systems. Nejad is an editorial board member for journals like Wind Energy Science and Ocean Engineering , and a member of ISO committees on drivetrain health monitoring. Education: PhD in Marine Technology, NTNU (2015) MSc Subsea Engineering, University of Aberdeen (2012) BSc Mechanical Engineering, Tehran University (2009) His research interests emphasize offshore wind drivetrain reliability, condition monitoring, and digital twin applications. Recent work includes studies on blade bearing fatigue estimation, SCADA-based lifetime extension of drivetrains, and wake steering techniques in floating wind farms. Key awards include multiple 'Best Lecturer' honors at NTNU and international conference recognitions. His research has been supported by grants such as the Nowitech Fellowship and DNV Education Fund. Key Projects: Marine System Dynamics and Vibration Lab (MD Lab) oversees projects on wind turbine drivetrains, floating offshore systems, and digital twin integration. Lab/Teams: MD Lab focuses on advancing marine energy systems through experimental and computational studies.

• Lithium-ion Battery Technologies
• Redox Flow Batteries
• Bioenergy
• +5 more

Dr. Jacob Joseph Lamb is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Energy and Process Engineering within the Faculty of Engineering. He serves as the Study Program Manager for the Bachelor of Engineering in Renewable Energy (BIFOREN) and leads the Digital Energy Systems laboratory group. His roles include WP8 leadership in the FME Battery initiative and Theme Leader for Efficient Energy Use at ENERSENSE. Education: PhD in Energy and Process Engineering, NTNU (2013–2016) MSc in Chemical Engineering, University of Otago, New Zealand (2011–2012) BSc in Chemical Engineering, University of Otago, New Zealand (2008–2010) Research Interests: Dr. Lamb focuses on sustainable energy systems, particularly lithium-ion battery technologies , redox flow batteries , bioenergy , and digitization of energy systems . He explores sensor technologies for real-time monitoring and optimization of energy storage devices. His work integrates machine learning with physics-based models to enhance battery performance and reliability. Key Projects: FME Battery: Norwegian research initiative for advanced battery technologies ReZinc: Zinc-air flow battery development for stationary storage HeaLiSelf: Self-healing lithium-ion batteries using optical sensing and data analytics Computational studies on pre-lithiation processes and cold-climate battery performance Publications: His recent work emphasizes lithium-ion battery digitalization , SoC estimation , and electrode structuring . He bridges experimental and computational methods to address challenges in energy storage scalability and safety. Affiliations: ENERSENSE (Efficient Energy Use Theme) NTNU Thermal Engineering Laboratories

• Structural Dynamics
• Bridge Engineering
• Wind Engineering
• +6 more

Ole Andre Øiseth is a Professor at the Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), specializing in structural dynamics with focus on bridges and marine structures. He leads the structural mechanics research group. Research Interests: Wind Engineering Bridge Aerodynamics Structural Health Monitoring Operational Modal Analysis Fluid-Structure Interaction Extreme Load Analysis Key Contributions: Developed nonlinear force models for bridge aerodynamics Advanced Kalman filter techniques for wind load identification Environmental contour methods for bridge design Automated monitoring systems for long-span bridges

Kirsti KletteView profile

Professor

• Learning and education
• Pedagogy
• Classroom research
• +5 more

Kirsti Klette is Professor at the Department of Teacher Education and School Research within the Faculty of Education at the University of Oslo. She serves as Centre Director at the Nordic Centre of Excellence Quality in Nordic Teaching (QUINT), launched in autumn 2018. Her academic career spans over two decades, beginning as Associate Professor at Lillehammer University College in 1994, then at the University of Oslo Faculty of Education in 1998, and becoming full Professor in 2002/2004. She held a Visiting Fulbright Professorship at Stanford University (2007-2008) and has directed numerous national research programs including UTDANNING 2020 (2009-2014). Professor Klette's research focuses on classroom teaching and learning through video methodology, instructional quality, and teacher education. Her work examines the relationship between teaching practices and student outcomes across Nordic educational contexts. She leads major projects including Linking Instruction and Student Achievement (LISA), Linking Instruction and Student Experiences (LISE), and the Synthesizing Research on Teaching Quality (SYNTEQ). Her methodological expertise in video research has established her as a leading figure in educational research methodology. Analysis of her recent publications (2022-2024) reveals consistent focus on classroom observation systems, teacher education coherence, and Nordic educational practices. Her work spans multiple subject areas including mathematics, social studies, and language arts, with particular attention to how instructional quality can be measured and improved. She frequently collaborates with international researchers, contributing to global understanding of teaching quality across different educational systems. Professor Klette has made significant contributions to educational policy and practice, particularly in teacher education reform and classroom observation methodology. Her research bridges educational theory and classroom practice, with implications for teacher preparation, professional development, and educational assessment systems.

Joachim HornView profile

Associate Professor

• Orthopaedics
• Pediatric Orthopaedics
• Biomechanics
• +5 more

Joachim Horn is an Associate Professor in the Department of Orthopaedics at the University of Oslo. His work focuses on pediatric orthopaedics, biomechanical studies of bone fixation, and surgical techniques for limb deformities. He has contributed to research on femoral anteversion treatment, epiphysiodesis accuracy, and hip displacement in cerebral palsy patients. His recent studies (2020-2025) emphasize clinical outcomes of limb lengthening, growth plate modulation, and orthopaedic instrumentation improvements. Publications span biomechanical analysis, surgical case studies, and population-based epidemiological research in orthopaedic conditions. Key affiliations: Rikshospitalet Hospital, Oslo University Hospital Research interests include skeletal growth modulation, orthopaedic biomechanics, and pediatric trauma management. Collaborations involve multi-institutional studies on limb reconstruction and congenital bone disorders.

• Service Design
• Interaction Design
• Experience-centric Organizations
• +4 more

Simon David Clatworthy is a Professor at the Department of Design, Oslo School of Architecture and Design. With a business leadership background, he pioneered interaction design and service design at AHO. His work focuses on experience-centric organizations, emphasizing service design's role in creating value through customer, user, and employee experiences. 20+ years service design research Co-founder of SFI projects: CSI & C3 Collaborations with Telenor, Posten, DNB Research spans service innovation, organizational transformation, and tangible design tools. Recent work explores service materials like aesthetics, culture, and experiential structures. He teaches service design at both bachelor and master levels. Publications include 15+ service design books/chapters, with 2023's The Materials of Service Design as a key contribution. His AT-ONE methodology remains foundational in service innovation. Current explorations involve sensory experiences in public spaces (2024's The Garden of Senses ) and cultural plurality in service design (2021's Narrating Service Design ).