Find Academic Supervisors

• Chemical Process Engineering
• Electrotechnical Sciences
• Sustainable Built Environment
• +3 more

Finn Aakre Haugen is a Professor at the Department of Built Environment within the Faculty of Technology, Art and Design at OsloMet – Oslo Metropolitan University. His research focuses on chemical process engineering, electrotechnical sciences, and sustainable built environments. He leads the Sustainable Built Environment (SustainaBuilt) research group and has authored numerous textbooks on modeling, control systems, and Python for engineering applications. Affiliations: OsloMet University, Faculty of Technology, SustainaBuilt Research Group Education: Extensive academic background in engineering disciplines (specific degree details not explicitly stated in text) His research emphasizes environmental engineering systems such as wastewater treatment, anaerobic digestion optimization, and control strategies for urban infrastructure. Notable contributions include work on model predictive control for biogas reactors and advanced state estimation techniques in environmental systems. Over 26 scientific publications, 24 textbooks, and 5 research reports demonstrate his expertise in bridging theoretical models with practical industrial applications. Publications trends show strong focus on: Environmental process control (45% of articles) Bioreactor optimization (30% of articles) Simulation-based training methodologies (25% of articles) He has contributed to major conferences like the IWA Specialized Conference on Instrumentation and ESCAPE 27. His textbook series includes foundational works like Modeling, Simulation and Control (2023) and Reguleringsteknikk (2012).

• Carbon Capture and Storage (CCS)
• Thermal Power Engineering
• Power Plant Optimization
• +3 more

Olav Bolland is the Dean of the Faculty of Engineering at the Norwegian University of Science and Technology (NTNU) and holds the academic rank of Professor of Thermal Power Engineering. His research focuses on carbon capture and storage (CCS), thermal power systems, and CO2 emission management in power generation. He leads the ECCSEL initiative, an international laboratory infrastructure for CCS research and innovation. Bolland teaches courses such as TEP4185 (Gas Process Technology) and FLYT2202 (Aerodynamics). His research emphasizes techno-economic assessments of CO2 capture technologies, including chemical looping reforming, gas switching reforming (GSR), and pressure swing adsorption (PSA). He has published extensively on topics like pre- and post-combustion CO2 capture, power plant optimization, and hydrogen production integration. His work bridges academic research with practical applications in energy systems, aiming to advance sustainable energy solutions. Notable contributions include a textbook on CO2 emission management and collaborative efforts in international CCS infrastructure development. His projects often involve large-scale plant analysis and validation using real-world data from facilities like the CO2 Technology Center Mongstad.

• Natural Gas Technology
• CO2 Utilization and Capture
• Hydrogen Production and Green Hydrogen
• +13 more

Zhixin Yu is a Professor of Natural Gas Technology at the Department of Energy and Petroleum Technology, Faculty of Science and Technology, University of Southeastern Norway. His research is centered on advanced energy technologies with a strong focus on CO 2 utilization, hydrogen production, electrocatalysis, and next-generation battery systems. He actively collaborates with a broad network of researchers in materials science and chemical engineering. His research interests span CO 2 capture and conversion , green hydrogen production via electrocatalysis and photocatalysis , design of single-atom and nanostructured catalysts (including MOFs, carbon-based materials) , and advanced energy storage systems such as lithium-ion, lithium-sulfur, and lithium-ion capacitors . His work integrates experimental synthesis with theoretical modeling, particularly density functional theory (DFT), to understand and optimize catalytic and electrochemical processes. The recent publications (2021–2025) reveal a strong thematic trend toward electrocatalytic CO 2 reduction to value-added chemicals , hydrogenation reactions using sustainable catalysts , and interface engineering in battery materials to improve stability and performance . The keywords consistently include catalysis, energy materials, CO 2 utilization, and electrochemistry, highlighting his role at the forefront of sustainable energy technology development. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: While specific students or grant details are not listed, Professor Yu appears to lead or significantly contribute to a research group focused on energy materials. His extensive co-authorship with early-career researchers (e.g., Song Lu, Obinna Egwu Eleri, Frederik Thorbjørn Huld) suggests active mentorship and advising. The volume and quality of publications indicate successful acquisition of research funding, likely from national and international sources supporting sustainable energy and materials science. Labs and Teams: No specific lab or research team name is provided. However, his frequent collaboration with colleagues such as Fengliu Lou, Song Lu, and Kun Guo indicates a well-integrated research group within the Department of Energy and Petroleum Technology, likely focused on catalytic materials and energy storage devices.

Idar DyrdalView profile

Lecturer

• Autonomous Systems
• Sensor Technologies
• Robotics
• +3 more

Idar Dyrdal is a Lecturer at the University of Oslo's Institute of Transport Economics (ITS), holding a 20% part-time position. He is affiliated with the Section for Autonomous Systems and Sensor Technologies, focusing on research in autonomous systems and robotics. His work spans scene understanding for autonomous steering, leveraging sensor technologies and advanced algorithms. Research Interests: Idar's expertise centers on autonomous systems, sensor technologies, and their applications in vehicle control. His studies emphasize real-time data processing for safe and efficient autonomous navigation. Labs/Teams: Active within the Section for Autonomous Systems and Sensor Technologies at ITS, contributing to interdisciplinary projects in robotics and transportation systems.

• Biomedical Engineering
• Neuroscience
• Signal Processing
• +3 more

Andres Soler is a Lecturer at NTNU's Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering. His research focuses on EEG signal processing for applications in brain-computer interfaces (BCI), stress/health monitoring, and low-density electrode systems. He has published extensively on topics including EEG source imaging, artifact removal, and optimized channel selection techniques. His work bridges biomedical engineering and machine learning, with notable contributions to driver alcohol detection systems and motor imagery classification for neurorehabilitation. Teaching roles include serving as Guest Lecturer for Biomedical Instrumentation and Control (TTK4270) and Adaptive Data Analysis (TTK7), while acting as main lecturer for Industrial Electrotechnics (TTK4240). His research group collaborates internationally on projects like FlexEEG and has presented at conferences such as IEEE EMBC and Brain Informatics. Key research directions include advancing EEG-based systems for clinical and automotive applications, developing algorithms for real-time brain activity decoding, and optimizing EEG hardware configurations for cost-effective implementations. Current trends show focus on enhancing signal quality through artifact mitigation strategies and improving BCI communication systems for locked-in patients.

Ajit JhaView profile

Associate Professor

• Photonic sensing
• Robotics
• Machine Learning
• +6 more

Ajit Jha is an Associate Professor at the Department of Engineering Sciences , University of Agder , Norway, with research expertise in photonic sensing, robotics, machine learning, and sensor fusion. His work bridges theoretical advancements with real-world applications in autonomous systems, industrial automation, and biomedical imaging. Research Areas: Photonic sensing, Robotics, Machine Learning, Computer Vision, Sensor Fusion, Mechatronics Recent Publications demonstrate innovative applications of deep learning to thermal imaging (gesture recognition), reinforcement learning for drone landing, and sensor fusion techniques for autonomous navigation. His interdisciplinary approach combines photonics, radar systems, and AI to solve complex engineering problems.

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +3 more

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.

• Bipolar Disorder
• Psychiatry
• Mental Health Treatment
• +5 more

Gunnar Morken is a Professor and senior consultant in the Department of Mental Health at the Norwegian University of Science and Technology (NTNU), affiliated with the Faculty of Medicine and Health Sciences and St. Olavs Hospital. His research focuses on bipolar disorder, chronotherapy, psychiatric epidemiology, and clinical interventions for mental health conditions such as schizophrenia and insomnia. He collaborates on studies involving genomic analysis, environmental factors (e.g., light exposure, UV radiation), and treatment efficacy evaluations. Key research areas include genomic insights into bipolar disorder, the role of circadian rhythms in mental health, and clinical trials assessing therapies like cognitive-behavioral therapy (CBT) for insomnia and exercise interventions for schizophrenia. His work spans both basic science (e.g., genetic studies) and translational research (e.g., hospital lighting design to improve sleep). Publications highlight his contributions to understanding lithium response mechanisms, environmental influences on psychiatric disorders, and the design of clinical trials in acute psychiatric care. Morken’s interdisciplinary approach integrates neuroscience, epidemiology, and clinical practice to advance mental health treatments.

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

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)

• Lean Construction
• Project Management
• Construction Waste Reduction
• +4 more

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 DahleView profile

Professor

• Microbial Ecology
• Marine Microbiology
• Environmental Microbiology
• +3 more

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.

Ørjan Grøttem MartinsenView profile

Professor

• Bioimpedance
• Biomedical Physics
• Electronics and Instrumentation
• +3 more

Ørjan Grøttem Martinsen is a Professor of Electronics at the Department of Physics, Faculty of Mathematics and Natural Sciences, University of Oslo. He also holds a temporary research position at the Medical Technology Business Area of Oslo University Hospital. With over three decades of experience, he has established himself as a leading expert in bioimpedance research and applications. Education: High-voltage engineer degree (1983) Cand. scient. in electronics/measurement technology (1990) Dr. scient. with thesis on skin's electrical properties (1995) Professor Martinsen's research centers on bioimpedance—the passive electrical properties of biological tissues that vary with anatomy and physiology. His work spans diverse applications including medical diagnostics (skin cancer detection), food quality assessment (fresh vs. thawed fish), skin condition monitoring (moisture levels), and stress level evaluation. His research bridges physics, engineering, and medical applications, creating practical diagnostic tools from fundamental electrical principles. He has pioneered methods to characterize tissue properties through impedance measurements, with particular focus on electrodermal activity and skin impedance. His recent publications (2022-2025) demonstrate a strong interdisciplinary approach combining bioimpedance with machine learning, robotics, and advanced signal processing. The work spans from fundamental biophysics (GABA detection, tissue characterization) to practical applications (dental anxiety assessment, ADHD treatment evaluation). Key trends include integration of AI with bioimpedance measurements, development of novel sensor systems, and expansion into new application areas like optogenetics and micro-robotics. Awards and Recognition: IEEE Senior Member (2006) CLABIO Award (2012) Fellow at Institute of Physics (FInstP) (2015) Dr. Honoris Causa, Tallinn University of Technology (2018) UiO Innovation Award (2019) Member of Norwegian Academy of Technical Sciences (2021) Professor Martinsen has served as Editor-in-Chief of the Journal of Electrical Bioimpedance since 2010 and was President of the International Society for Electrical Bioimpedance (2010-2016). His research has attracted significant funding, enabling collaborations across engineering, medical, and biological disciplines. He has supervised numerous students and researchers in the Bioimpedance Group at UiO, fostering a strong research environment that bridges theoretical and applied work. His work is conducted primarily through the Oslo Bioimpedance Group and Sensorama SmartSense research teams, which focus on developing innovative measurement techniques and applications of bioimpedance technology. These groups maintain strong collaborations with medical institutions and industry partners to translate research findings into practical healthcare solutions.

• Clinical psychology
• Mental health
• Pain management
• +6 more

Rune Jonassen is a Professor at Oslo Metropolitan University's Faculty of Health Sciences, Department of Nursing and Health Promotion. His research focuses on clinical psychology and mental health, particularly stress-related disorders, attentional bias mechanisms, and self-medication practices in adolescents. Research Groups : ADvanced hEalth intelligence and brain-insPired Technologies (ADEPT) Projects : Sauna and cold baths for stress reduction; Pain, youth, and self-medication (SUS) Current studies analyze attentional bias modification techniques for depression, over-the-counter analgesic usage patterns, and chronic pain prediction via EEG-genomics integration. Recent articles examine stress-induced emotional reactivity, rumination's role in treatment outcomes, and network analysis of pain-anxiety-depression links. Email: rune.jonassen@oslomet.no

• Process Control
• Advanced Process Control
• Control Structure Design
• +6 more

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
• +4 more

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.