جست‌وجوی استاد و پژوهشگر

• Railway Engineering
• Transportation Systems
• Structural Engineering
• +۳ مورد دیگر

Albert Lau is an Associate Professor of Civil and Environmental Engineering at the Norwegian University of Science and Technology (NTNU), located in Trondheim, Norway. He specializes in railway engineering, structural dynamics, and transportation systems. Lau holds leadership roles as the Study Program Leader for the MSc in Road, Railway, and Transportation Engineering, overseeing curriculum development and program coordination. His research focuses on railway track design, dynamic modeling of train-track interactions, and infrastructure maintenance, with projects such as the MeTinT initiative (Measurement with Train in Regular Traffic). He has extensive experience supervising master’s and PhD students, and his work emphasizes innovation in rail infrastructure and sustainable transportation solutions. Education and Professional Background: Lau earned his PhD from NTNU in 2018, focusing on numerical simulations of railway turnouts. Prior roles include Postdoc (2018–2020) and Assistant Professor (2017–2018) at NTNU, and teaching at Oslo Metropolitan University (2020). His industry experience includes roles as a Design Engineer (2010–2012) and Project Engineer (2013–2014) in Malaysia, where he managed construction projects and structural design. Research Interests: Lau’s work spans railway track dynamics, infrastructure health monitoring, and machine learning applications in transportation. Key projects include developing digital twins for railway test sites and analyzing ground displacement impacts on track anomalies. His contributions to the Road, Railway and Transport Group at NTNU aim to advance rail safety and efficiency through interdisciplinary approaches. Teaching and Outreach: Lau coordinates courses such as TBA4225 (Railway Engineering) and BA6012 (Fundamental Railway Technology). His outreach includes expert commentary on railway incidents, such as an interview on NRK (2024) discussing potential causes of a train accident. Current initiatives focus on revitalizing regional rail services and optimizing train positioning systems.

• Industrial Ecology
• Climate Change Mitigation
• Resource Efficiency
• +۶ مورد دیگر

Edgar Hertwich is a Professor of Industrial Ecology at the Department of Energy and Process Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU). He is on partial leave from NTNU, serving as a Senior Researcher at the International Institute for Applied Systems Analysis (IIASA) in Austria and as a partner in the environmental data company XIO Sustainability Analytics. His work bridges academic research and practical applications for climate mitigation. Current affiliations: NTNU (Professor), IIASA (Senior Researcher), XIO Sustainability Analytics (Partner) Previous roles: Professor at Yale University (2015-2019), Fellow at Yale (2019-2022), Professor at NTNU (2003-2015) Hertwich's research focuses on industrial ecology, examining material flows in economic systems to advance climate protection and sustainable development. His work spans machinery, buildings, urban form, and food supply systems, employing life cycle analysis, cross-flow analysis, and economic modeling. He contributes to global policy frameworks like the UN's Circular Economy Action Plan and EU Climate Council reports. Recent projects include CIRCOMOD (Circular Economy Modeling for Climate Mitigation) and RAINFOREST (knowledge co-production for biodiversity). He has been recognized with NTNU's Prize for Research and Artistic Activity (2023) for his contributions. Scientific Awards NTNU's Prize for Research and Artistic Activity (2023) Editorial Roles Environmental Science & Technology Journal of Industrial Ecology Journal of Economic Structures As a thought leader in industrial ecology, Hertwich connects technical insights to policy, emphasizing material efficiency and resource allocation. His work influences EU climate strategies and global environmental assessments.

• Biotechnology
• Microbial Ecology
• Synthetic Biology
• +۳ مورد دیگر

Hans Christopher Bernstein is a Professor at the Norwegian Fisheries College, UiT The Arctic University of Norway, and affiliated with the Arctic Centre for Sustainable Energy (ARC). His research focuses on biotechnology, microbial ecology, synthetic biology, and microalgal carbon capture and utilization. University: UiT The Arctic University of Norway School: Norwegian Fisheries College Research Group: Microalgae & Microbiomes Research Centers: Arctic Centre for Sustainable Energy (ARC) Bernstein’s work explores the intersection of biotechnology and microbial ecology, particularly in synthetic biology applications for carbon capture. His research includes modeling microbial processes, studying lipidome plasticity in Arctic diatoms, and developing engineered genetic circuits for microbial consortia. Key trends in his publications involve marine microbiome dynamics, cold seep ecosystems, and daylight-driven carbon exchange in structured microbial communities. Recent articles highlight advancements in microalgal biotechnology for industrial carbon capture, synthetic genetic circuits, and spatiotemporal metabolic network models. His work spans both theoretical modeling (e.g., neighbor-dependent interaction inference) and applied biotechnological solutions (e.g., EcoFABS fabricated ecosystems).

• 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.

• Artificial Intelligence
• Machine Learning
• Probabilistic Graphical Models
• +۷ مورد دیگر

Helge Langseth is a Professor at the Department of Computer Technology and Informatics , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). His research focuses on Artificial Intelligence , Machine Learning , and Probabilistic Graphical Models , particularly Bayesian Networks and their applications in Decision Support Systems . Langseth's work addresses Explainable AI (XAI) , Reinforcement Learning , and Recommender Systems . He has contributed to Bayesian Optimization , Probabilistic Modeling , and Robotic Control in oceanic environments. His recent publications emphasize transparency , fairness , and scalability in AI systems, with applications spanning maritime trade, migraine diagnosis, and power grid management. He is affiliated with the Intelligent Systems Research Group at NTNU and actively mentors doctoral and master's students. Co-authored works with Yanzhe Bekkemoen , Sverre Herland , and Jørgen Hanssen reflect his role in advising the next generation of AI researchers.

• Computational Fluid Dynamics (CFD)
• Wave Hydrodynamics
• Wave Modeling
• +۹ مورد دیگر

Hans Bihs is a Professor in the Department of Civil and Environmental Engineering, Faculty of Engineering. His research focuses on computational fluid dynamics (CFD), wave hydrodynamics, and wave-structure interaction using the open-source framework REEF3D. Key Research Areas: CFD simulations, wave modeling, floating body dynamics, ocean wave energy, aquaculture hydrodynamics, sediment transport, and high-performance computing. Projects: ERC Consolidator Grant PARTRES (2023-2028), EEA Grants Portugal SurfWave (2023), NFR KPN IPIRIS (2021-2025), EEA Baltic SolidShore (2021-2024), NTNU's MAPLE (2022-2025), and DigiCoast (2021-2024). Email: hans.bihs@ntnu.no His recent publications (2025-2020) analyze fluid-structure interaction, ship-induced waves, floating offshore wind turbines, submerged vegetation, and coastal structures using advanced CFD techniques. Topics include wave hydrodynamics, turbulence, and numerical modeling for marine and aquaculture systems.

• 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

Anne Berit C. Samuelsenمشاهده پروفایل

دانشیار

• Polysaccharide Chemistry
• Pharmacognosy
• Carbohydrate Polymers
• +۴ مورد دیگر

Anne Berit C. Samuelsen serves as Associate Professor at the Department of Pharmacy, University of Oslo, where she also holds the position of Head of Education. Her academic foundation includes a Cand.pharm. degree and Dr.scient. doctorate, establishing her expertise in pharmaceutical sciences. Her research centers on polysaccharides from natural sources—particularly higher plants, cereals, and fungi (Basidiomycota)—with specialized focus on β-glucans. Key interests include carbohydrate chemistry, pharmacognosy, and the development of biopolymer-based pharmaceutical applications. Her work bridges fundamental structural characterization with practical drug delivery solutions, notably through liposome coating technologies and immunomodulatory compound development. Recent publications reveal a strong trajectory in fungal polysaccharide research, particularly with Pleurotus eryngii and Albatrellus ovinus species. Her team employs advanced techniques like diffusion-ordered NMR spectroscopy to analyze polysaccharide structures while investigating biological activities related to immune receptor binding (Dectin-1, Toll-like receptors) and therapeutic applications. This work demonstrates consistent output in high-impact journals including Carbohydrate Polymers and ACS Applied Bio Materials . She actively contributes to academic instruction through courses such as FARM1150 (Pharmaceutically Oriented Biochemistry), FARM3100 (Pharmacognosy), and FARM5200 (Use of Biopolymers in Pharmaceuticals). Her leadership extends to the Bioactive Natural Substances and Health Effects (BioNatH) research group and the Glyconor Consortium, where she investigates natural product applications for health improvement.

Behzad Alaeiمشاهده پروفایل

دانشیار

• Structural Geology
• Sedimentary Basin Analysis
• Fault Zone Architecture
• +۶ مورد دیگر

Behzad Alaei serves as an Associate Professor in the Section for Study of Sedimentary Basins within the Department of Geosciences at the University of Oslo's Faculty of Mathematics and Natural Sciences. His office is located in room K38 of the Geology Building at Sem Sælands vei 1, 0371 Oslo, with a professional email contact at behzad.alaei@geo.uio.no. Dr. Alaei maintains an active research profile with publications spanning from 2005 to the present, demonstrating his ongoing contributions to geological sciences. Dr. Alaei's research spans multiple critical areas within structural geology and sedimentary basin analysis, with particular expertise in fault zone architecture, seismic interpretation techniques, and CO2 storage site assessment. His work bridges theoretical geological concepts with practical applications in petroleum geology and carbon sequestration. A significant portion of his research focuses on the Norwegian Barents Sea region, where he has conducted extensive studies on normal fault systems and their geometric characteristics. His recent work increasingly integrates machine learning and deep learning approaches with traditional geological analysis, reflecting the evolving nature of geoscience research methodology. The analysis of Dr. Alaei's publication record from 2018-2024 reveals a strong thematic continuity in fault characterization research, with progressive incorporation of advanced computational methods. Early publications focused primarily on traditional structural analysis of fault systems in sedimentary basins, while more recent work demonstrates increasing integration of machine learning techniques for fault detection and characterization. A notable trend is the application of these geological insights to practical challenges in carbon capture and storage, particularly regarding fault risk assessment for CO2 storage sites in the North Sea region. His collaborative work with Anita Torabi appears consistently throughout this period, suggesting a strong research partnership. Dr. Alaei maintains an active research program with multiple ongoing projects related to sedimentary basin analysis and fault characterization. His work appears to involve significant collaboration with both academic and industry partners, particularly in the context of CO2 storage research. While specific grant details aren't provided in the available information, his consistent publication record across multiple high-impact journals suggests successful funding of his research activities over the past two decades.

Deodat Edward Mwesiumoمشاهده پروفایل

استاد

• Supply Chain Management
• Digital Business
• Tourism Management
• +۴ مورد دیگر

Deodat Edward Mwesiumo is a Professor of Supply Chain Management at Molde University College (HiMolde), part of the Faculty of Logistics. He holds a PhD in logistics from the same institution and has extensive teaching and research experience since 2012. His roles include Head of the Supply Chain Management Research Group and member of the PhD committee. Previously, he directed the Bachelor program in Supply Chain Management and Logistics. His research focuses on supply chain resilience, digital business transformation, and tourism management. Key areas include procurement strategies, sustainability, circular economy models, and interorganizational relationships in tourism. He has published in high-impact journals like Production Planning and Control , Journal of Purchasing and Supply Management , and Annals of Tourism Research . Dr. Mwesiumo has led externally funded projects and contributed to over 50 peer-reviewed publications. He is affiliated with research groups such as MIIBS (Marketing, Innovation, International Business & Strategy) and the Transport Research Group (TRG). His teaching spans BSc and MSc levels, including courses on value chain analysis, digital business, and supply chain theory. Recent work emphasizes airport digital maturity, supply chain risk mitigation, and the impact of data-driven decision-making in public procurement. He has authored books like Making Value Chains Work and Fundamentals of Digital Business Management , underscoring his commitment to both academic and applied knowledge dissemination.

• 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.

• Metal Forming
• Aluminum Alloys
• Product Development
• +۳ مورد دیگر

Torgeir Welo is a Professor at the Department of Mechanical and Industrial Engineering , Norwegian University of Science and Technology (NTNU) . He specializes in metal forming , particularly aluminum alloy structures , with a focus on plastic bending behavior , dimensional stability , and 3D forming technologies . His research also encompasses Lean Product Development , emphasizing knowledge reuse and maximizing customer value in automotive and aerospace applications. Key Research Areas : Metal Forming, Aluminum Processing, Springback Control, Lean Development, Additive Manufacturing, Material Substitution Teaching : Courses on Aluminum Technology , Metal Forming Analysis , and Machine Element Design Publications (15 most recent): Focus on springback monitoring , charge weld evolution , flexible forming , machine learning applications , and circular economy frameworks in metal manufacturing.

• Power Market Analysis
• Hydropower Scheduling
• Power System Balancing
• +۵ مورد دیگر

Hossein Farahmand is a Professor at the Department of Electric Energy, Norwegian University of Science and Technology (NTNU), and leads the Electricity Markets and Energy Systems Planning (EMESP) research group. He holds an Associate Editor role at IEEE Transactions on Energy Markets, Policy and Regulation and contributes to international initiatives like IEA Wind Task 25 and ISGAN Annex 9. Education : Dr.ing. (PhD) from NTNU (2012) His research focuses on power market analysis, hydropower scheduling, power system balancing, and local flexibility markets in smart grids. Recent work explores renewable energy integration, digitalization, and hydrogen systems. Trends include machine learning applications in hydropower scheduling, offshore wind economics, and grid flexibility solutions. Scientific awards include Senior Member of IEEE and representation in ISGAN Annex 9 and IEA Wind Task 25 . He supervises PhD candidates and co-supervised projects in areas like grid tariffs , local energy communities , and electric vehicle integration . Grants include EU Horizon 2020 and Research Council of Norway funding for projects such as IntHydro , HONOR , and Ocean Grid . Labs and teams include the EMESP research group at NTNU, collaborations with Hohai University , Smart Innovation Norway , and industry partners in China and Norway.

Maria Sydnesمشاهده پروفایل

دانشیار

• Emergency Management
• Crisis Response
• Organizational Resilience
• +۴ مورد دیگر

Maria Sydnes serves as an Associate Professor in the Department of Technology and Security at UiT The Arctic University of Norway, Tromsø. Her academic work focuses on emergency management and organizational resilience within high-risk Arctic environments, with particular emphasis on maritime safety and cross-border crisis coordination between Norway and Russia. Her research interests span interorganizational coordination during emergencies, organizational learning for resilience building, and practical applications of lean production principles in crisis contexts. She investigates Arctic-specific challenges including avalanche response in Longyearbyen, oil spill management in polar waters, and integration of unorganized volunteers into formal emergency systems, consistently addressing the intersection of climate change impacts and security vulnerabilities. Analysis of her publication record reveals a strong trend toward interdisciplinary solutions for Arctic safety, with recurring themes of Norwegian-Russian cooperation, maritime risk assessment, and adaptive governance structures. Her work bridges theoretical frameworks with real-world case studies—from Svalbard waters to the Barents Sea—demonstrating practical approaches to disaster risk reduction in extreme environments. Dr. Sydnes actively participates in multiple research initiatives including the Climate Change Adaptation and Secure Societies groups. Her current projects encompass Co-producing knowledge about risk and safety of maritime activities around Svalbard SPRICE (spray icing modelling for maritime decision support) GLOBSEC (North-South security partnerships) NoCoU (civil security for Norwegian communities) Beredt! (risk-based governance for climate-driven natural hazards) highlighting her commitment to scalable, community-focused security solutions in vulnerable Arctic regions.

• Wildlife Ecology
• Large Mammal Conservation
• Human-Wildlife Conflict
• +۵ مورد دیگر

Martin Mayer serves as Associate Professor at the University of Inland Norway within the Faculty of Applied Ecology, Agricultural Sciences and Biotechnology and the Department of Forestry and Outback Studies. Based at the Evenstad study location, his research focuses on large mammal ecology in human-dominated landscapes across Scandinavia and Europe. His primary research interests center on Wildlife Ecology and Large Mammal Conservation , with particular emphasis on human-wildlife conflict resolution, road ecology, and carnivore management. Mayer investigates how species like moose, deer, and beavers adapt to anthropogenic landscapes through habitat selection, movement patterns, and population dynamics. His work integrates cutting-edge methodologies including GPS telemetry, drone surveillance, and citizen science data to address conservation challenges in agricultural and urban settings. Analysis of Mayer's recent publications reveals strong trends in using roadkill data for population monitoring, examining spatial constraints on wildlife movement, and developing mitigation strategies for human-wildlife conflicts. His research increasingly incorporates cross-border European perspectives on wildlife management while maintaining a strong foundation in Scandinavian field ecology. Mayer actively contributes to the LARGE research group (ecology of large animals), which conducts field studies on ungulate behavior, predator-prey dynamics, and landscape-scale conservation planning in Norway's boreal ecosystems.