جست‌وجوی استاد و پژوهشگر

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +۳ مورد دیگر

Morten Hovd is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU). His research focuses on advanced control systems, model predictive control (MPC), power electronics, and optimization algorithms. He has contributed significantly to the development of robust control strategies for uncertain systems and has published extensively in leading journals and conferences in the field of control engineering. His research interests span several key areas in control systems engineering, including model predictive control, nonlinear control systems, optimization under uncertainty, and applications in power systems and energy efficiency. He is particularly known for his work on discrete-time bilinear systems, modular multilevel converters (MMCs), and the integration of machine learning techniques with control theory. His contributions address both theoretical advancements and practical implementations in industries such as energy and petroleum engineering. Hovd's recent publications highlight advancements in energy-efficient control systems, stochastic surrogate modeling for subsurface flows, and optimization algorithms tailored for complex engineering problems. His work often combines rigorous mathematical frameworks with real-world applications, such as improving the reliability of power systems and enhancing reservoir management through data-driven methods. He is actively involved in teaching courses such as TTK4210 (Advanced Control of Industrial Processes) and TK8118 (Mini-seminar in Cybernetics). His research has led to innovations in fault detection for power systems, energy-efficient building climate control, and robust MPC strategies for uncertain systems.

• Scanning Transmission Electron Microscopy (4D-STEM)
• Open Source Scientific Software Development
• Big Data Processing in Electron Microscopy
• +۴ مورد دیگر

Magnus Nord is an Associate Professor in the Department of Physics, Faculty of Natural Sciences at Norwegian University of Science and Technology (NTNU). His research focuses on advanced electron microscopy techniques and computational tools for materials characterization. Research Interests : Scanning Transmission Electron Microscopy (4D-STEM), Open Source Scientific Software Development (Python), Big Data Processing, Magnetic/Electric Field Imaging, Structural Characterization using Higher Order Laue Zones. Publications span cutting-edge applications in functional materials, nanomagnets, and perovskite thin films, with emphasis on machine learning and precession-enhanced imaging. Key keywords include Materials Science , Electron Microscopy , and Computational Imaging . Software Development : Lead developer of Atomap and pyxem , contributing to HyperSpy and merlin_interface for electron microscopy data analysis. Current Research Funding : InCoMa (Research Council of Norway) IMPRESS (Horizon EU Program)

Svanhild Breiveمشاهده پروفایل

دانشیار

• Mathematics Education
• Early Childhood Education
• Inquiry-Based Learning
• +۳ مورد دیگر

Svanhild Breive is an Associate Professor at the Department of Mathematical Sciences, University of Agder. Her research focuses on mathematics education in early childhood settings, particularly exploring how play and inquiry-based approaches enhance mathematical learning in kindergartens and early primary years. She has contributed significantly to understanding teacher-child interactions, classroom orchestration, and the role of physical environments in fostering mathematical thinking. Her work examines key themes such as the balance between structured and free play, embodied cognition in mathematics, and the application of semiotic theories to analyze learning processes. She has published extensively in journals like For the Learning of Mathematics and European Early Childhood Education Research Journal , and co-authored influential books including Lekende læring og lærende lek i begynneropplæringen (2022) and the Lekbasert læring series. Her research often intersects with broader educational psychology topics, such as curriculum design for preschool systems and the impact of pedagogical frameworks on child development. Collaborations with projects like the Agder Project highlight her commitment to evidence-based early education practices.

• Lean Construction
• Project Management
• Construction Waste Reduction
• +۴ مورد دیگر

Trond Bølviken is a Professor at the Department of Engineering Sciences, University of Agder. His research focuses on Lean Construction methodologies, project management, and construction waste reduction. He has contributed to advancing understanding of collaborative project teams, waste economics, and production planning. His work emphasizes practical applications of theoretical principles in construction, aiming to bridge gaps between academic research and industry practices. Key areas include uncertainty management, production control systems, and the integration of Lean principles with traditional construction workflows. Bølviken has published extensively in peer-reviewed journals and conference proceedings, particularly within the International Group for Lean Construction (IGLC). He collaborates with international researchers and industry practitioners to address challenges in project delivery and workflow optimization.

Håkon Dahleمشاهده پروفایل

استاد

• Microbial Ecology
• Marine Microbiology
• Environmental Microbiology
• +۳ مورد دیگر

Håkon Dahle is a Professor and Group Leader at the Computational Biological Unit (CBU) at the University of Bergen. He also leads the 'Energy and Life' work package at the K.G. Jebsen Centre for Deep Sea Research. His affiliation is with the Department of Biological Sciences (BIO). His research focuses on microbial ecology, investigating how natural and human-driven factors influence microbial communities and ecosystems across diverse environments, including hydrothermal vents, aquaculture systems, and marine ecosystems. Key research questions include understanding microbial community structure in hydrothermal systems, the interplay between geochemistry and microbial life, and optimizing recirculating aquaculture systems (RAS). Dahle employs bioinformatics, field observations, and population modeling to address these questions. He collaborates on projects like VIRVAR (NFR-funded), exploring algal-virus interactions, and MONITOR, advancing RAS microbial monitoring. His work spans microbial diversity in extreme environments such as Arctic hydrothermal vents and the impacts of deep-sea mining tailings. Notable contributions include studies on Zetaproteobacteria in hydrothermal mats and the microbiome dynamics in salmon farming. Dahle has supervised doctoral candidates like Jan Pieter Vander Roost (2018) and Runar Stokke, advancing microbial ecology and geobiology. Publications highlight interdisciplinary approaches, from viral genomics to aquaculture engineering. His research bridges fundamental microbiology with applied challenges in sustainable aquaculture and environmental stewardship.

Susanna Röblitzمشاهده پروفایل

استاد

• Systems Biology
• Computational Pharmacology
• Mathematical Modeling
• +۴ مورد دیگر

Susanna Röblitz is a Professor at the Department of Informatics within the Computational Biology Unit at the University of Bergen. Her research focuses on mathematical modeling of high-dimensional dynamical systems in life sciences, including molecular conformation dynamics, systems biology, and pharmacology. She specializes in rare event sampling, meshfree methods, clustering algorithms, and uncertainty quantification, with a particular emphasis on oscillatory systems such as hormonal rhythms. Her teaching includes courses such as BINF100 Introduction to Bioinformatics and BINF305 Systems Biology . Her research has been supported by grants from the Research Council of Norway and Nordforsk, including projects like Markov State Models for Cellular Phenotype Switching and RAS-TOOLS . Key research areas include hormonal regulation (e.g., menstrual cycle modeling), gene regulatory networks, and applications in pharmacokinetics and aquaculture. Recent work highlights include the development of Markov state models for gene networks and spectral clustering techniques for analyzing complex biological systems. She has supervised students such as Anna Kristina Fredheim Grandma, whose master’s thesis focused on pharmacokinetic modeling in personalized dosing. Her interdisciplinary collaborations span computational biology, veterinary medicine, and clinical pharmacology.

• Process Control
• Advanced Process Control
• Control Structure Design
• +۶ مورد دیگر

Sigurd Skogestad is a Professor of Chemical Engineering at NTNU in Trondheim, specializing in process control. He has held this position since 1987, following his PhD from the California Institute of Technology (Caltech) in 1987. From 1999 to 2009, he served as Head of the Department of Chemical Engineering. Since 2015, he has directed the SUBPRO center for research-based innovation, focusing on subsea production and processing. Education: PhD in Chemical Engineering, California Institute of Technology (Caltech), 1987 Research Interests: His work emphasizes advanced control strategies, including control structure design, plantwide control systems, and optimal operation of process systems. He explores robust control methodologies, PID control applications, and distillation column dynamics. Modeling for control and subsea production systems are central to his current research through the SUBPRO initiative. Leadership & Roles: Director of SUBPRO Center (since 2015) Past Head of Department of Chemical Engineering (1999–2009) Labs/Teams: Leads the SUBPRO center, a collaborative research effort advancing subsea production technologies.

• Applied Artificial Intelligence
• Digital Twins
• Hybrid Modeling
• +۴ مورد دیگر

Idelfonso Nogueira is an Associate Professor at the Department of Chemical Process Technology, Norwegian University of Science and Technology (NTNU). His research focuses on integrating artificial intelligence, advanced control, and system optimization to address challenges in Industry 4.0/5.0. Key research areas include AI-driven product/process development, interpretable machine learning for process systems, multi-scale system integration, and adaptive digital twins. He collaborates extensively with global universities, institutes, and industries to advance sustainable industrial solutions. His work emphasizes digitalization, hybrid modeling, and optimization frameworks, as seen in publications on pressure swing adsorption, fragrance engineering, and CO2 capture systems. He also promotes innovative teaching methods, including augmented reality for chemical engineering education. Recent publications highlight advancements in digital twin frameworks, machine learning for crystallization processes, and optimal control strategies. His research bridges theoretical models with practical applications, ensuring robustness and reliability in industrial contexts.

• Lithium-ion Battery Technologies
• Redox Flow Batteries
• Bioenergy
• +۵ مورد دیگر

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

Juergen Pfingstnerمشاهده پروفایل

پژوهشگر

• Particle Accelerator Technology
• Free Electron Lasers
• CLIC (Compact Linear Collider)
• +۵ مورد دیگر

Juergen Pfingstner is a Post-doctoral Fellow at the University of Oslo (since 2015) within the Department of Physics. His research focuses on advanced accelerator technologies, particularly at CERN's CLIC Test Facility (ATF2). Key areas include emittance preservation, ground motion mitigation, and free-electron laser (FEL) design. He holds a PhD from the Vienna University of Technology (2013) and a Master's in Electrical Engineering from Graz University of Technology (2008), specializing in control engineering and electromagnetic field computation. His academic journey includes a postdoctoral stint at CERN (2012–2014), where he investigated ground motion effects on CLIC performance. Collaborations span institutions like KEK (ATF2 facility) and the X-band FEL collaboration. Research interests bridge particle accelerator physics, control systems, and high-frequency radiation technologies. Publications emphasize CLIC final focus systems, wakefield suppression, and plasma wakefield acceleration. His work addresses both theoretical and experimental challenges in next-generation collider design, including THz radiation facilities and feedback control methodologies.

• Structural Dynamics
• Bridge Engineering
• Wind Engineering
• +۶ مورد دیگر

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

• Synthetic biology
• Microbial molecular biology
• Metabolic engineering
• +۵ مورد دیگر

Trygve Brautaset is a Professor at the Department of Biotechnology and Food Science within the Norwegian University of Science and Technology (NTNU) . His research primarily focuses on synthetic biology and microbial molecular biology, with significant contributions to methylotrophic bacteria engineering and methanol-based bioproduction systems. Project Leader for Centre for Digital Life Norway Board Member, Vectron Biosolutions Member, Norwegian Biotechnology Advisory Board Research Interests: Specializing in synthetic biology and metabolic engineering , Brautaset has extensive publications on Bacillus methanolicus systems, including methanol-based production of amino acids, vitamins, and organic acids. His work explores microbial physiology, genetic tool development, and biorefinery applications. Publication Trends: Recent studies (2025-2021) show consistent focus on methanol utilization , thermophilic biocatalysis , and metabolic flux optimization . Key outputs include systems-level analyses of amino acid production, formaldehyde metabolism, and seaweed-based feedstock conversion.

Karl Harmenbergمشاهده پروفایل

دانشیار

• Macroeconomics
• Inequality
• Labor Market Dynamics
• +۴ مورد دیگر

Karl Harmenberg is a Swedish economist based at the Department of Economics, University of Oslo since 2022. He holds a PhD from Stockholm University's Institute for International Economic Studies (2018) and previously worked at Copenhagen Business School (2018-2021) and BI Norwegian Business School (2021-2022). As a tenure-track associate professor , he teaches Macroeconomic Theory and develops open-source Python tooling for macroeconomic modeling. Key research themes include macroeconomic dynamics with heterogeneous agents , earnings distribution mechanisms , and integrated epi-econ modeling for pandemic preparedness His methodological innovations include the permanent-income-neutral measure for heterogeneous-agent models and directed cycle graph representations of macroeconomic frameworks Current projects include WaCoMacro (wage contracts and macroeconomics) and ongoing collaborations with Timo Boppart , Per Krusell , and Erik Öberg Recent publications span: 2025 International Economic Review work on unemployment-risk amplification mechanisms 2025 Quantitative Economics article on integrated epi-econ modeling 2024 Economics Letters paper establishing Pareto distribution in top earnings 2023 AER Insights research on wage contract rigidity 2021 Journal of Economic Dynamics & Control contribution on permanent income shocks His work has been cited in policy discussions regarding: Swedish automatic stabilizer design Norwegian pandemic response strategies Scandinavian labor market reforms Nordic macroeconomic teaching curricula

• High-performance Computing
• Energy-efficient Computing
• Machine Learning
• +۳ مورد دیگر

Dr. Ngoc Nha Vi Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She holds a PhD from UiT and was a visiting scholar at Rutgers University, USA. Her research focuses on high-performance and energy-efficient computing, machine learning, and bioinformatics. She is a member of the NORA.startup Steering Group and leads the Arctic Green Computing Group. Education: PhD in Computer Science (UiT), M.Sc. in Software Engineering via Erasmus Mundus (Blekinge Institute of Technology, Sweden & Technical University of Kaiserslautern, Germany). Research interests include energy-efficient algorithms, bioinformatics tools (e.g., vCOMBAT), and applications of machine learning in healthcare and robotics. She teaches courses such as INF-2200 Computer Architecture, INF-2900 Software Engineering, and INF-2202 Concurrent Programming. Her work spans computational models for antibiotic target-binding, runtime energy optimization (REOH framework), and power models for embedded systems (RTHpower/ICE). She contributed to the EXCESS project on energy-efficient computing systems. Labs/Teams: Arctic Green Computing Group, EXCESS consortium.

Sigurd Skogestadمشاهده پروفایل

استاد

• Process Control
• Systems Engineering
• Optimization
• +۲ مورد دیگر

Sigurd Skogestad is Professor in the Department of Chemical Engineering at the Norwegian University of Science and Technology (NTNU). He serves as Program Leader for the 5-year Master program in Chemical and Biochemical Engineering. His research develops simple yet rigorous methods to solve engineering problems, focusing on self-optimizing control structures that enable near-optimal operation under varying conditions. His approach moves economic optimization from slow real-time optimization to faster control layers. Key research areas: Self-optimizing control structures Process systems engineering Multivariable feedback control Plantwide process control Distillation modeling and control He has received significant recognition including the AIChE Computing in Chemical Engineering Award and IFAC Fellow status. He leads research groups in Process Control and contributes to the SUBPRO center on subsea production.