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Ole Morten Aamo is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway. His office is located at Elektro D/B2, D344, Gløshaugen, O. S. Bragstads plass 2, and he can be reached at aamo@ntnu.no or by phone at 73594386. Professor Aamo's research focuses on control theory with particular emphasis on partial differential equations (PDEs) and their applications in drilling engineering and the petroleum industry. His work spans multiple areas including boundary control of hyperbolic systems, adaptive control methodologies, vibration control in drilling operations, and leak detection systems for pipe networks. His research combines theoretical control developments with practical applications in the oil and gas sector, particularly addressing challenges related to stick-slip phenomena, torsional vibrations, and pressure oscillations in drilling operations. His publication record reveals a consistent trajectory of high-impact research in control systems, with a notable shift toward integrating machine learning approaches with traditional control theory in recent years. The majority of his work centers around hyperbolic PDE systems, with applications primarily in drilling engineering and fluid dynamics. His research demonstrates a strong connection between theoretical control developments and practical implementations in the petroleum industry. Professor Aamo has actively supervised multiple graduate students, as evidenced by the master's theses listed in his publication record. His work often appears in top-tier control journals including IEEE Transactions on Automatic Control, Automatica, and IEEE Control Systems Letters, as well as petroleum engineering venues like SPE Journal and ASME publications.

• Control Theory
• Partial Differential Equations
• Drilling Engineering
• +6 more

Thor Inge Fossen is a Professor of Navigation and Marine Craft Control at the Department of Engineering Cybernetics, Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). He is a key scientist at the Norwegian Centre for Embodied AI (NCEI) and internationally recognized for his work in navigation systems, guidance systems, and control of marine vessels, aircraft, and drones. Professor Fossen holds a PhD in Engineering Cybernetics and an MSc in Marine Technology. His academic journey has led him to become a Fellow of AAIA, IEEE, and IFAC, reflecting his significant contributions to the field. His research spans several critical areas in marine and aerospace systems: Marine craft hydrodynamics and motion control Navigation, guidance, and control systems for marine craft, aircraft, and drones Cybersecurity of autonomous vehicles Sea-state estimation and wave analysis Attitude control and estimation Fossen's marine craft model, which is widely used in the industry Professor Fossen's publication record demonstrates a strong focus on adaptive control systems, particularly Line-of-Sight (LOS) guidance laws, with numerous papers on 3D path following for marine and aerial vehicles. His recent work (2023-2025) shows increasing integration of machine learning techniques with traditional control systems, particularly in areas like constrained control allocation using deep neural networks. There's also a growing emphasis on cybersecurity aspects of autonomous vehicle guidance systems. His scientific recognition includes: Fellow of the American Institute of Aeronautics and Astronautics (AAIA) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the International Federation of Automatic Control (IFAC) Professor Fossen has been actively involved in advising graduate students, with numerous PhD and MSc graduates. He has led significant research projects including the Marine Systems Simulator (MSS) and the Python Vehicle Simulator, which are widely used tools in the field. His current appointments include being a Study Program Coordinator for the Master's program in Cybernetics and Robotics at NTNU and a Key Scientist at the Norwegian Centre for Embodied AI. He leads research teams focused on embodied AI applications for marine systems, with particular emphasis on safe and secure autonomous operations in complex maritime environments. His work bridges theoretical control systems with practical marine applications, making significant contributions to both academic research and industry implementation.

• Marine craft hydrodynamics
• Motion control systems
• Navigation systems
• +7 more

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

• Macroeconomics
• Inequality
• Labor Market Dynamics
• +4 more

Dzan Zelihic is a Research Fellow at the Department of Special Needs Education, Faculty of Educational Sciences, University of Oslo, focusing on cognitive mechanisms in reading fluency and experimental eye-tracking methodologies. His academic background includes: Doctoral Research Fellow, University of Oslo (2021–present) Master’s in Special Needs Education, University of Oslo (2018–2020) Bachelor’s in Pedagogy, University of Lillehammer (2015–2018) His research investigates automaticity, interference, and simultaneous processing during reading, with emphasis on how adjacent words impede visual recognition. Using eye-tracking paradigms, he examines cognitive skills underlying reading fluency to address challenges in literacy development. This work bridges cognitive psychology and educational interventions for reading disorders. His 2025 publication in the Journal of Memory and Language demonstrates how adjacent words disrupt visual recognition, advancing understanding of parafoveal processing limitations. This aligns with broader trends in reading research focusing on real-time cognitive constraints during text comprehension. He contributes to the BetterReading project analyzing fluency gains and is affiliated with the CREATE research group (Centre for Research on Equality in Education Literacy and Numeracy in Context), which investigates contextual factors in literacy and numeracy development.

• Reading fluency
• Automaticity
• Interference
• +3 more

Martin Marie Hubert Choux is an Associate Professor at the Department of Engineering Sciences , University of Agder, Norway. He holds dual M.Sc. degrees in Mechatronic Engineering from École Nationale Supérieure d'Art et Métiers (France) and University of Queensland (Australia), and a Ph.D. in Automatic Control from Technical University of Denmark (2011). Education: M.Sc. in Mechatronic Engineering, École Nationale Supérieure d'Art et Métiers, Paris, 2006 M.Sc. in Mechatronic Engineering, University of Queensland, Brisbane, 2006 Ph.D. in Automatic Control, Technical University of Denmark, Copenhagen, 2011 His research focuses on mechatronics , robotics , and battery recycling , with over 15 recent publications (2024–2019) on: Automated Disassembly of lithium-ion batteries Fault Diagnosis in motor drives using structural analysis and neural networks Efficiency Optimization of electric drivetrains in offshore applications Comparative Studies of hydraulic vs. electric actuation systems AI and Robotics for EV battery recycling Control Algorithms for mechanical systems His work spans robotics , automatic control , and sustainable engineering , contributing to electric vehicle and offshore technology advancements.

• Mechatronics
• Robotics
• Automatic Control
• +4 more

Narada Dilp Warakagoda is an Associate Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies. His research focuses on Artificial Intelligence, Autonomous Systems, Computer Vision, Robotics, Machine Learning, and Deep Learning, with notable contributions to underwater acoustics, renewable energy forecasting, and unmanned vehicle control systems. He collaborates extensively with researchers across disciplines to advance applications in environmental monitoring, energy systems, and autonomous technologies. His work integrates advanced machine learning techniques with domain-specific challenges, such as synthetic aperture sonar analysis, spatio-temporal wind forecasting, and reinforcement learning for autonomous navigation. He has published in leading journals and conferences, addressing topics like probabilistic solar irradiance prediction, graph-based wind energy modeling, and deep learning for seabed munitions detection. Warakagoda’s research bridges theoretical advancements with practical implementations, emphasizing applications in robotics, environmental science, and defense technologies. His projects often involve interdisciplinary teams, reflecting his commitment to solving real-world problems through innovative AI-driven solutions.

• Artificial Intelligence
• Autonomous Systems
• Computer Vision
• +3 more

Jubin Aboutalebi is an Adjunct Professor (Professor II) in Linguistics at the Department of Language and Culture, UiT The Arctic University of Norway, located in Tromso. He specializes in psycholinguistics and cognitive neuroscience with a focus on bilingualism and multilingualism. His research explores the neurocognitive mechanisms of language processing, bilingual brain plasticity, and cognitive reserve across the lifespan. Key interests include: Neural correlates of bilingual language control Neuroplasticity in multilingual individuals Cognitive reserve enhancement through bilingualism Emotional processing in native vs. foreign languages Neuroimaging of language comprehension (fMRI, EEG) Aboutalebi's recent publications (2022-2025) demonstrate a consistent focus on bilingual cognition, with topics spanning neurodevelopmental effects of multilingualism, emotional interference in language processing, and the neuroprotective benefits of bilingualism in aging. His work frequently employs advanced neuroimaging methodologies to investigate brain-behavior relationships. He collaborates extensively with international researchers and contributes to projects through the Psycholinguistics of Language Representation (PoLaR) lab, C-LaBL, and AcqVA-Nor research groups.

• Psycholinguistics
• Bilingualism
• Cognitive Neuroscience
• +3 more

Erlend Hodneland is a Researcher at the University of Bergen's Department of Informatics, affiliated with the Mohn Medical Imaging and Visualization Centre (MMIV). His work bridges medical imaging, radiomics, and machine learning, focusing on tumor analysis and prognostication in cancers like cervical and endometrial cancers. He specializes in developing automated tumor segmentation techniques and tools for radiomic signature analysis, integrating visualization and computational methods to enhance clinical decision-making. His research interests include medical imaging analytics, radiomics for cancer prognosis, and interactive visualization frameworks for multiparametric medical data. Collaborations involve radiologists, oncologists, and computer scientists to translate imaging data into actionable insights. Key projects include the RadEx platform for radiomic tumor profiling and automated segmentation algorithms for cervical cancer studies. Notable contributions include MRI-based delta radiomics for tracking tumor responses during chemoradiotherapy and fully automatic whole-volume tumor segmentation. His work emphasizes precision medicine through quantitative imaging biomarkers and interdisciplinary approaches to medical data analysis.

• Medical Imaging
• Radiomics
• Tumor Segmentation
• +3 more

Eilif Hugo Hansen is an Associate Professor at the Department of Electric Energy, Norwegian University of Science and Technology (NTNU). His expertise focuses on electrical installations and lighting technology, with an emphasis on energy efficiency and daylight utilization in building systems. Education: MSc and PhD in Electric Power Engineering from Norwegian Institute of Technology (NTH), with additional qualifications as an electrical contractor and electrician. Research: Specializes in low voltage electrical systems, intelligent lighting controls, energy savings through daylight integration, and safety protocols in electrical installations. Outreach: Active in standardization committees (NEK/NK64, IEC TC64 MT12) and public education initiatives. Teaching: Leads courses such as TET4165 Lys og belysning and TET4170 Elektroinstallasjoner, with extensive experience in guiding master's and bachelor's theses.

• Electrical Installations
• Lighting Technology
• Energy Efficiency
• +4 more

Pedro Pablo Lucas Bravo is a Doctoral Research Fellow at the University of Oslo's Department of Informatics (IFI), affiliated with the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion within the Faculty of Mathematics and Natural Sciences. His research focuses on developing interactive music systems using autonomous agents and swarm intelligence, with applications in Extended Reality (XR), Spatial Audio, and robotics. His Ph.D. project explores automatic tempo synchronization in human-machine systems through swarms of autonomous agents, aiming to create emergent musical behaviors in virtual, physical-virtual, and physical platforms. Key technologies include XR, spatial audio synthesis, motion capture, and robotic platforms. Bravo has contributed to projects like the XR Human-Swarm Interactive Music System and the MusicLab Copenhagen Dataset. His work bridges computer science, music technology, and artificial intelligence, with publications in venues such as IEEE ACSOS, NIME, and SMC. He holds a focus on interdisciplinary collaboration, leveraging swarmalator systems for self-organizing compositions and exploring cross-disciplinary applications of embodied oscillators in music performance.

• Music Technology
• Robotics
• Artificial Intelligence
• +5 more

Kenan Dikilitas is a Professor in the Department of University Pedagogy at the University of Stavanger. His research focuses on language education, bilingualism, translanguaging pedagogy, teacher professional development, and English as a Foreign Language (EFL). He has published extensively on topics such as teacher identity, multilingualism in education, and technology integration in teaching. His work often explores collaborative practices, reflective teaching, and policy implications for language education. Key research interests include translanguaging in EFL contexts, teacher autonomy development, and the use of digital tools like ChatGPT in higher education. His studies frequently examine bilingual education policies, student attitudes toward language proficiency thresholds, and the impact of action research on teacher practice. He has collaborated internationally on projects related to English Medium Instruction (EMI), preschool bilingual contexts, and cross-disciplinary language strategies. Recent publications analyze ChatGPT-driven reflective practices, translanguaging in teacher training, and the developmental trajectories of educators in collaborative research settings. His work bridges theoretical frameworks like complexity theory with practical classroom applications, emphasizing pedagogical innovation and policy-informed teaching strategies.

• Language Education
• Bilingualism
• Translanguaging Pedagogy
• +6 more

Torsten Martiny-Huenger is an Associate Professor at the Department of Psychology, UiT The Arctic University of Norway. His research focuses on cognitive processes related to self-regulation, decision-making, and associative learning. He explores topics such as the role of situational cues in future action planning, mechanisms of action control via if-then planning, and the interplay between conscientiousness traits and behavioral strategies. Key research areas include cognitive psychology, behavioral science, and risk judgment. His work often involves experimental methods to study priming effects, implicit learning, and the neural correlates of decision-making. Notable contributions address how verbal instructions shape action-effect associations and how environmental cues influence self-regulation success. Recent studies investigate reinvestment decisions under loss framing, the impact of self-instructed stimulus-affect plans on evaluative responses, and the spontaneous planning mechanisms underlying short-term task adherence. His research spans theoretical discussions on evaluating scientific theories to applied studies in health psychology, such as interventions targeting obesity and cardiometabolic risk factors in older adults. No scientific awards or grants are explicitly listed in the provided materials. His academic profile emphasizes experimental psychology and cognitive science applications, with a focus on translating theoretical insights into real-world behavioral interventions.

• Cognitive Psychology
• Self-Regulation
• Decision Making
• +4 more

Alexey Pavlov is a Professor in Petroleum Cybernetics at the Norwegian University of Science and Technology (NTNU), leading the BRU21 program. He holds a PhD in Mechanical Engineering from Eindhoven University of Technology (2004), an MSc in Applied Mathematics from St. Petersburg State University (1998), and has industrial experience at Equinor and Ford Motor Co. His research focuses on automatic control systems, optimization, signal processing, and human-machine interaction, with applications in petroleum engineering, mechatronics, and medical fields. Current projects include digital solutions for oil and gas, high-performance systems, and shared human-machine control via haptics. Past work includes leading R&D projects at Equinor on drilling automation, production optimization, and heavy oil systems. He has supervised 8 completed PhD projects and authored over 120 publications, including the book Uniform Output Regulation of Nonlinear Systems (2005). His awards include the IEEE Control Systems Technology Award (2015) and multiple recognitions for academic and industrial contributions. Prof. Pavlov serves on editorial and program committees for IEEE, IFAC, and other conferences, and is a Senior Member of IEEE. His leadership in the BRU21 initiative aligns with Norway’s OG21 strategy for innovation in petroleum technology.

• Automatic control systems
• Optimization and estimation systems
• Nonlinear and high-performance systems
• +4 more

Bjarne Foss is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), and Managing Director of the Kavli Institute for Systems Neuroscience. He has been a professor since 1989 and holds a PhD in Engineering Cybernetics from NTNU. His roles include Vice President for Research at NTNU (2017–2020) and Adjunct Professor at the University of South-East Norway (2021–2023). He has extensive board experience with companies like Cybernetica AS, Solution Seeker AS, and KTH Royal Institute of Technology. Foss specializes in process control, reservoir management, and optimization algorithms, with over 300 publications and an H-index of 49. He has supervised 31 PhD students and led major international projects for ESA and EU. Awards include the IBM Open Collaborative Faculty Award (2010, 2011), the Karl Diesel Best Paper Award (1995), and recognition for pedagogical innovation in 2007. His research focuses on enhancing oil production efficiency, automation in energy systems, and control strategies for complex industrial processes. His education includes a PhD from NTNU (Engineering Cybernetics) and an MSc degree awarded with the prestigious «Innstilling» honor. Professional activities include editorial roles, IEEE Senior Membership, and leadership in international committees like IFAC. Foss co-founded Solution Seeker AS (2013), Cybernetica AS (2000), and FIRST Scandinavia (2000). Recent work emphasizes distributed optimization for large-scale oil systems, dynamic control under uncertainty, and shale-gas production strategies. His publications span journals like IEEE Transactions on Automatic Control and Journal of Petroleum Science and Engineering , addressing challenges in reservoir control, model predictive control, and well-placement optimization.

• Process Control
• Petroleum Engineering
• Optimization Algorithms
• +3 more

Erlend Magnus Lervik Coates is an Associate Professor at the Department of ICT and Natural Sciences , Norwegian University of Science and Technology (NTNU) , Ålesund campus. He serves as head of the Cyber-Physical Systems Laboratory (CPS-Lab) and coordinator for the Autonomous Ships research area within NTNU. As a key researcher in SFI AutoShip , he supervises 4 PhD candidates and teaches courses in automatic control and artificial intelligence across bachelor’s and master’s programs. His research focuses on motion control, autonomy, and power and energy management for autonomous ships and drones (UAVs) . Technical competencies span control technology, cybernetics, robotics, and vehicle control , with applications in hybrid control systems, geometric methods, and deep reinforcement learning . Publications highlight nonlinear control strategies, decision support systems, and propulsion modeling. Scientific Awards : None explicitly listed. Labs/Teams : Leads CPS-Lab, contributes to SFI AutoShip. Teaching : Courses include Automation and Mechatronics with Project , Dynamical Systems , Control Systems Engineering , and Intelligent Machines .

• Motion Control
• Autonomous Systems
• Power and Energy Management
• +6 more