جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• AI Alignment
• +۲ مورد دیگر

Michael Riegler is a Researcher at the AI Department, Simula Research Laboratory , focusing on interdisciplinary applications of Artificial Intelligence in healthcare, sports analytics, and multimedia systems. His work bridges Machine Learning , AI Alignment , and Applied AI across clinical and real-world domains. Key Affiliations: Simula Research Laboratory (AI Department Head) Research Themes: Explainable AI in medicine, multimodal data analysis, and AI-driven health monitoring Research Interests include: Developing AI/ML algorithms for medical imaging (e.g., polyp detection, embryo analysis) Addressing missing data challenges in healthcare through novel imputation techniques Creating multimodal virtual avatars for investigative interview training Designing edge AI systems for sports analytics and sustainable fishing Recent Publications highlight collaborations with institutions in Norway and globally, with a focus on: Medical Applications: Polyp segmentation, ECG analysis, and explainable models for disease detection Sports Analytics: Athlete performance prediction and soccer video processing Data Infrastructure: Lifelogging datasets (ScopeSense), semantic representation frameworks Labs & Teams include leadership in Simula’s AI Department and participation in projects like Medico Multimedia Task , ImageCLEF , and MediaEval workshops. His work emphasizes responsible AI innovation in public sectors and privacy-preserving systems for edge environments.

Vasileios Mavroeidisمشاهده پروفایل

دانشیار

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

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

Anne H Schistad Solbergمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Image Analysis
• +۶ مورد دیگر

Anne H Schistad Solberg is a Professor in the Department of Informatics at the University of Oslo's Faculty of Mathematics and Natural Sciences. She leads research in digital signal processing and image analysis, with a focus on machine learning applications across multiple domains. As co-director of SFI Visual Intelligence, she oversees research on interpretable deep learning models, uncertainty quantification, contextual learning, and self-supervised learning approaches. Her research spans medical imaging (particularly cardiovascular ultrasound), environmental monitoring using satellite imagery, and seabed mapping with sonar technology. Professor Solberg's work demonstrates a consistent trajectory from foundational signal processing techniques to cutting-edge deep learning applications. Her recent publications show increasing specialization in medical image analysis, particularly in echocardiography enhancement and cardiac structure segmentation, while maintaining strong contributions to remote sensing and geophysical applications. She teaches several popular courses including IN2070, IN3310, and IN5400 (Machine Learning for Image Analysis), which is noted as the most popular master's/PhD course on deep learning at the University of Oslo. Professor Solberg serves as principal investigator for the Intelligent Cardiovascular Ultrasound Scanner (INCUS) project, collaborating with GE Vingmed Ultrasound to develop AI-enhanced cardiac imaging systems that improve diagnostic accuracy and productivity in echocardiography. Co-director of SFI Visual Intelligence research center Principal Investigator for the INCUS project (Intelligent Cardiovascular Ultrasound Scanner) Member of the Digital Signal Processing and Image Analysis (DSB) research group Member of the Strategic Research Initiative: Multimodal Medical Imaging and Image Analysis (MEDIMA) Her research group develops algorithms that address real-world challenges in medical diagnostics and environmental monitoring, with a particular emphasis on making deep learning models more interpretable and reliable for critical applications. The INCUS project, funded through User-driven Research-based Innovation (BIA), aims to reduce the time wasted during cardiac ultrasound examinations by implementing intelligent algorithms that learn from expert users and historical data.

• Biomechanics
• Human Kinetics
• Biomedical Engineering
• +۳ مورد دیگر

Dr. Ryan B Graham is an Associate Professor in the School of Human Kinetics at the University of Ottawa , with cross-appointments to the Ottawa-Carleton Institute for Biomedical Engineering . He holds Adjunct Assistant Professor positions at Queen's University and University of Waterloo , reflecting his interdisciplinary collaborations in biomechanics and biomedical engineering. His research focuses on spine movement analysis , motion capture validation , and sensor technology applications in clinical and military contexts. Recent work includes developing markerless motion capture systems, assessing movement reliability, and modeling spine dynamics for injury prevention. Editorial Contributions: Associate Editor for Biomechanics and Control of Human Movement at Frontiers in Sports and Active Living Dr. Graham's academic network includes collaborations with institutions in Canada, the UK, and the Netherlands, with a focus on advancing biomechanical methodologies and their clinical translation.

Jan Oskar Engeneمشاهده پروفایل

دانشیار

• Terrorism Studies
• Political Science
• European Politics
• +۴ مورد دیگر

Jan Oskar Engene is an Associate Professor in the Department of Comparative Politics at the University of Bergen, Norway. His academic career spans several decades with significant contributions to both terrorism studies and heraldry research. Engene's research interests have evolved significantly over time, beginning with a strong focus on terrorism, political violence, and European security. His early work centered on the TWEED (Terrorism in Western Europe: Explaining the Trends) dataset, which documented terrorist incidents across Western Europe from 1950 onward. Over the years, his research expanded to include political symbolism, heraldry, and flag history, particularly regarding Norwegian political symbols and their evolution. His work demonstrates a unique interdisciplinary approach, bridging political science with historical and symbolic analysis. Analysis of Engene's publication trends reveals a clear evolution from predominantly terrorism-focused research in the 1990s and early 2000s toward increasing engagement with heraldry, political symbolism, and Norwegian historical identity markers in recent years. The earlier works focus on quantitative terrorism analysis, counterterrorism policy, and European security frameworks, while more recent publications examine municipal heraldry, county coats of arms, and historical political symbols. This shift demonstrates Engene's ability to apply political science methodologies to diverse research areas while maintaining a consistent focus on political symbolism and identity. Engene has supervised numerous Master's theses at the University of Bergen, primarily in the areas of terrorism studies, European politics, and political identity. His supervision record includes students researching topics such as state responses to terrorism in Italy, Nordic political systems, and regional identity in Western Europe. While specific grant information isn't detailed in the available materials, his TWEED project represents a significant research undertaking that likely involved external funding. Engene maintains active engagement with public discourse through media appearances, having participated in numerous television and radio programs discussing terrorism, security policy, and political symbolism. His work with the TWEED project established him as a leading expert on European terrorism patterns, while his more recent heraldry research has positioned him as a specialist in Norwegian political symbolism and historical iconography.

• Marine Propulsion Systems
• Hydrodynamics of High-Speed Vehicles
• Ship Performance Analysis
• +۶ مورد دیگر

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.

• Autonomous Systems
• Marine and Maritime Risk Analysis
• Operational Risk Management
• +۴ مورد دیگر

Professor Ingrid Bouwer Utne is a faculty member at the Department of Marine Engineering, Norwegian University of Science and Technology (NTNU). Her primary research focuses on risk analyses of ships, marine systems, and autonomy, with emphasis on operational safety, maintenance management, and risk control in autonomous maritime technologies. Key Projects: Leader of the Risk Group at NTNU, involved in the SFI Autoship initiative and ERC AdG BREACH project addressing risk-based rationality in autonomous systems. Research Interests: Autonomous systems design, probabilistic risk assessment, safety engineering, and risk-informed decision-making for marine operations. Grants & Funding: Secured funding from the Research Council of Norway, MAROFF, and industry partners for projects like ORCAS (Online Risk Management for Autonomous Ships) and UNLOCK (Supervisory Risk Control). She supervises numerous PhD students and postdocs, focusing on topics such as autonomous vessel navigation, risk modeling for underwater robotics, and decarbonization of maritime systems. Her work bridges theoretical risk analysis with practical applications in marine autonomy and safety systems.

• Marine Renewable Energy
• Wind Turbine Drivetrain Systems
• Condition Monitoring
• +۵ مورد دیگر

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
• +۷ مورد دیگر

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

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Verification
• +۳ مورد دیگر

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on maritime systems, autonomous vessel control, and safety verification. He actively supervises Master's students and contributes to research on risk-informed control systems, hybrid power systems, and systems-theoretic process analysis (STPA). Research Interests: Rokseth's research spans autonomous ship systems, dynamic risk assessment, and safety verification. He explores risk-based decision-making for maritime autonomy, hazard identification in hybrid propulsion systems, and control function allocation in dynamic positioning. His work integrates systems theory, machine learning, and regulatory compliance (e.g., COLREGS) to enhance safety and environmental performance in marine operations. Publications: His recent work includes probabilistic trajectory prediction frameworks for autonomous ships, STPA-based safety analyses, and studies on decarbonization barriers in the maritime industry. These publications emphasize risk modeling, systems-theoretic approaches, and simulation-based verification. Teaching: Rokseth teaches courses such as TTK4130 - Modelling and Simulation, contributing to the education of future engineers and researchers in cybernetics and maritime systems.

• Risk Assessment
• Hydrogen Technologies
• Process Safety
• +۴ مورد دیگر

Nicola Paltrinieri is a Professor of Risk Assessment at the Department of Mechanical and Industrial Engineering, NTNU (Norway), and an Adjunct Professor at the University of Bologna (Italy). His expertise spans risk assessment, hydrogen technologies, process safety, and data-driven safety management. He holds Chartered Engineer and Chartered Scientist certifications and has served on editorial boards for journals like Safety Science and Journal of Risk Research . Education: PhD in Environmental, Safety and Chemical Engineering (University of Bologna, 2012) Master’s in Chemical and Process Engineering (University of Bologna, 2008) Research Interests: Focuses on hydrogen infrastructure safety, Natech accident analysis, risk-based inspection strategies, and AI integration in safety systems. His work emphasizes sustainable energy transitions and mitigating risks in emerging technologies like hydrogen. Key Projects (2022-2026): H2Glass : Decarbonizing glass and aluminum sectors via hydrogen HyInHeat : Hydrogen technologies for industrial heating HYDROGENi : Norwegian research center for hydrogen/ammonia Awards: Onsager Fellowship (2016–2021) Frank Lees Medal (2012) for safety-related publications Grants & Leadership: Head of NTNU Energy Team Hydrogen, coordinator for EU-funded projects like SUSHy , and active in international risk committees (e.g., EFCE, ESRA). His work bridges academia and industry, with over 8 PhD examinations supervised. Labs/Teams: Leads the NTNU Energy Team Hydrogen and collaborates on initiatives like SH2IFT-2 for safe hydrogen fuel handling. His research group focuses on AI-driven risk analysis and hydrogen infrastructure resilience.

Ronny Schererمشاهده پروفایل

استاد

• Meta-analysis
• Educational Measurement
• Digital Divides
• +۶ مورد دیگر

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
• +۱۲ مورد دیگر

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

• Anthropology of Science and Technology
• Computer Supported Collaborative Work
• Digitalization
• +۹ مورد دیگر

Vidar Hepsø is a Professor at the Department of Computer Technology and Informatics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His work bridges anthropology of science and technology with practical challenges in digitalization, energy transition, and remote operations. Research focuses on digital infrastructures, socio-technical systems, and human factors in oil and gas industries Active in NTNU Applied Information Technology and NTNU Energy Transition Initiative Publications emphasize open-source ecosystems, autonomous systems, and environmental monitoring His scholarly output spans computer-supported collaborative work, IT infrastructure governance, and risk-informed anomaly detection in subsea systems. He leads projects connecting digital innovation with offshore wind and petroleum geoscience.

Jan Butsمشاهده پروفایل

دانشیار

• Translation Theory
• Medical Humanities
• Conceptual History
• +۵ مورد دیگر

Jan Buts is an Associate Professor at the Sustainable Health Unit within the Faculty of Medicine at the University of Oslo, specializing in the intersection of translation theory, medical humanities, and corpus linguistics with a focus on sustainable health and development discourses. His academic background includes: Linguistics and Literature studies at KU Leuven (Belgium) PhD in Translation and Intercultural Studies from the University of Manchester (UK) Postdoctoral research at Trinity College Dublin (Ireland) Assistant Professor position at Boğaziçi University (Turkey) Buts' research centers on corpus-assisted discourse analysis applied to translation theory, medical humanities, and sustainable development. He actively develops the Sustainability and Health Corpus to analyze how language shapes public health narratives, gender discourses in development aid, and conceptual frameworks around sustainability. His work bridges linguistic analysis with critical perspectives on social justice and health equity. Analysis of his recent publications reveals a strong trajectory toward integrating corpus linguistics with medical humanities and sustainable development goals. Key trends include examining gendered vulnerabilities in policy discourse, translation's role in knowledge dissemination for sustainability, and digital media's impact on health communication – all characterized by methodological innovation in corpus construction and conceptual analysis. His scientific recognition includes: Runner-up for the Martha Cheung Award (2023) Buts serves on the executive council of IATIS (International Association for Translation and Intercultural Studies) and leads multiple research initiatives including the SHE Corpus project. His grant activities focus on interdisciplinary collaborations between translation studies and medical humanities, particularly through projects like KNOWIT (Knowledge in Translation) and MEDRA (Medicalisation of Democratic Rights in Abortion debates). He directs the Sustainable Health Unit, fostering cross-disciplinary teams that combine linguists, medical researchers, and public health experts to advance data-driven critical analysis of health and sustainability discourses through innovative corpus methodologies.