جست‌وجوی استاد و پژوهشگر

Jan Tommy Gravdahlمشاهده پروفایل

استاد

• Mathematical Modeling
• Nonlinear Control Systems
• Spacecraft Control
• +۵ مورد دیگر

Jan Tommy Gravdahl is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). He holds a dr.ing (PhD equivalent) in Engineering Cybernetics from NTNU (1998) and served as department head (2008/09). His research focuses on mathematical modeling and nonlinear control, with applications in spacecraft, robots, ships, and turbomachinery. He has supervised 10 PhD and 78 MSc students, authored/co-authored over 150 publications, and books like *Compressor Surge and Rotating Stall: Modeling and Control* (1999). Education: Siv.ing (1994), dr.ing (1998) from NTNU Leadership: Deputy department head (2006-07), department head (2008/09) Research interests include spacecraft formation flying, attitude control, and coordinated control systems. Notable projects include NTNU Cubesat and contributions to the European Student Earth Orbiter (ESEO). Publications highlight advancements in spacecraft control, nonlinear systems, and model predictive control. His work on robustness in ISS systems earned a Best Student Paper Award (2010). Collaborations involve ESA, Norwegian Space Centre, and Narvik University College. Awards: IEEE Outstanding Paper Award (2000) Advised over 80 students, contributing to academic and industrial advancements in aerospace and control systems. Active in international conferences and educational initiatives like SSETI.

• Computer Science
• Electrical Engineering
• Mathematical Sciences
• +۳ مورد دیگر

Assistant Professor Johannes Møgster is affiliated with the Department of Computer Science, Electrical Engineering and Mathematical Sciences. His research interests span control systems, automation, and petroleum engineering with a focus on Model Predictive Control (MPC) applications in drilling technologies. His work includes studies on managed pressure drilling (MPD), as evidenced by his 2013 publications. Research areas include advanced control strategies for industrial processes, mathematical modeling in engineering systems, and interdisciplinary applications of computational methods. While no formal awards or grants are listed, his publications reflect a specialization in applying control theory to drilling engineering challenges.

• Microbial Bioprocess Control
• Biotechnology
• Control Engineering
• +۵ مورد دیگر

Prof. Nadav Bar is a Professor at the Department of Chemical Engineering, NTNU, leading the Microbial Feedback Control (MFC) laboratory. His research focuses on integrating biotechnology with control theory to develop feedback systems for microbiological processes. He coordinates major EU projects including iCulture (7.8M€, 2023-2028) and AILEEN (1.5M€, 2023-2028), focusing on AI-driven microbial control and food safety. His lab specializes in real-time bioprocess control using advanced methods like Model Predictive Control (MPC) and Reinforcement Learning, alongside Digital Twin technologies for bioreactor monitoring. Key projects include optimizing food preservation via high-pressure processing (SafeFood, 2016-2019) and COPD diagnosis through systems biology (ERA SysMed-COPD, 2018-2022). His research spans microbial fermentation optimization, gene regulatory network analysis, and systems biology. Current PhD students include Fabienne Roessler and Yiwen Li. The lab actively recruits students in control engineering, biotechnology, and analytical chemistry. Notable contributions include developing noise reduction algorithms for gene expression data and advancing sensor fusion techniques in bioprocess monitoring. Research Themes: Feedback control of microorganisms, hybrid modeling with machine learning, optimal control of bio-processes, microbial sensor systems, and COPD systems biology. Lab infrastructure includes state-of-the-art bioreactors, autosamplers, and software tools like MATLAB-CASADI for real-time control. Key Publications: Recent works focus on robust bioprocess optimization using spent sulfite liquor (2024), advanced state estimation in bioreactors (2023), and high-pressure processing effects on Listeria monocytogenes transcriptomes (2021). Over 50 peer-reviewed articles demonstrate cross-disciplinary impact across biotechnology and control engineering.

• Robotics
• Control Systems
• Artificial Intelligence
• +۳ مورد دیگر

Martin Pierre Francois Jacquet is a Research Fellow at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on advanced robotics, specifically in collision avoidance systems and autonomous navigation using deep learning and control theory. He has contributed to conferences such as IEEE ICRA and IROS, presenting research on neural control barrier functions and model predictive control (MPC) frameworks. Research interests include integrating deep neural networks with traditional control methods to enhance safety and resilience in autonomous systems. His publications emphasize real-world applications of robotics, particularly in environments requiring dynamic obstacle avoidance. Recent work explores modular deep learning architectures for aerial robot navigation. No scientific awards are explicitly mentioned in the provided text. His professional activities include academic lectures and poster presentations at major robotics conferences, such as the European Robotics Forum and IEEE/RSJ IROS. No advisory or grant information is available in the current data.

• Autonomous Systems
• Control Systems
• Marine Robotics
• +۳ مورد دیگر

Tor Arne Johansen is a Professor at the Department of Engineering Cybernetics, NTNU, and a key scientist at the Centre for Autonomous Marine Operations and Systems (AMOS). He holds a MSc (1989) and PhD (1994) in Engineering Cybernetics from NTNU. His research focuses on autonomous systems, control engineering, and marine robotics. His work spans: Autonomous vessel navigation and collision avoidance Hyperspectral imaging technology for environmental monitoring Model predictive control (MPC) applications UAV and satellite control systems Risk-based decision-making for autonomous systems Recent publications emphasize maritime trajectory planning, hyperspectral data analysis, and navigation algorithms. He has advised over 15 master’s and doctoral students on topics like ship path planning, UAV control, and satellite operations. Labs/Teams: Active member of the AMOS Centre and NTNU’s aerospace robotics group. Collaborates with industry on autonomous systems development.

• Reinforcement Learning
• Model Predictive Control (MPC)
• Renewable Energy Systems
• +۷ مورد دیگر

Prof. Sebastien Nicolas Gros is the Head of the Department of Engineering Cybernetics at NTNU. His research focuses on safe Reinforcement Learning, Data-Driven Model Predictive Control (MPC), and energy systems optimization. He collaborates with major industries like Equinor, DNV, Kongsberg, and CorPower Ocean, alongside academic partners such as SINTEF. He supervises 6 PhD students and co-supervises projects in artificial pancreas systems, multi-rotor wind turbine control, and industrial applications with Volvo. His work emphasizes AI-driven solutions for energy management in buildings, domestic battery systems, and indoor farming. Notable projects include MAIDOM (smart home energy control) and wave energy converter optimization with CorPower Ocean. He actively engages students through MSc projects involving data-driven control, smart home integration, and hydroponics automation. Prof. Gros leads a research group addressing interdisciplinary challenges in energy transition and cybernetic systems. His expertise spans numerical optimization, renewable energy integration, and industrial control systems.

• Control Systems
• Robotics
• Spacecraft Attitude Control
• +۷ مورد دیگر

Jan Tommy Gravdahl is a Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His research focuses on advanced control systems, robotics, and their applications in marine, aerospace, and industrial systems. Key interests include underwater robotics, spacecraft attitude control, nonlinear control, and model predictive control. Research Interests: Development of control algorithms for autonomous underwater vehicles (AUVs) and snake robots, including path following, energy shaping, and compliant interaction. Spacecraft attitude control systems, emphasizing energy optimization and solar-powered mission execution. Robust control methodologies such as sliding mode control (e.g., super-twisting algorithm) and task-priority frameworks. Integration of learning-based techniques (e.g., reinforcement learning, neural networks) into model predictive control architectures. Applications in robotics for manufacturing, including additive manufacturing and sensor-guided robotic systems. Publications Trends: Recent work emphasizes underwater robotics (snake robot locomotion, wake navigation), spacecraft control (energy-optimal attitude maneuvers), and advanced MPC frameworks. Key themes include safety constraints, real-time adaptation, and multi-robot cooperation. Advising/Grants: Advises students on topics ranging from control theory to robotics applications. Collaborates on projects funded by industries and research councils, though specific grants are not listed here. Labs/Teams: Likely involved with NTNU’s robotics and automation groups, particularly in underwater robotics and aerospace control systems research.

Miroslav Bachinskiمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Artificial Intelligence
• Healthcare Technology
• +۴ مورد دیگر

Miroslav Bachinski is an Associate Professor at the Department of Information and Media Studies, University of Bergen. His research focuses on Human-Computer Interaction (HCI), with specialties in AI-driven tools, healthcare technology, and biomechanical modeling. He is affiliated with the Emerging Media Research Group and the Human-Computer Interaction (HCI) Research Group. Key research areas include: AI applications in dementia care (e.g., adaptive voice assistants, wearable integration) Biomechanical simulation for ergonomic interface design VR/AR interaction techniques and validation Human-AI collaboration frameworks Recent work highlights trends in: Scoping reviews of dementia care technologies Automated biomechanical testing in VR Emotion-aware voice assistant design Interdisciplinary workshop methodologies for AI tool development His contributions bridge technical innovation with user-centered design, emphasizing ethical considerations and participatory approaches in healthcare technology. He actively contributes to conferences like NordiCHI and NOKOBIT.

• Control Systems
• Model Predictive Control
• Wind Farm Control
• +۵ مورد دیگر

Lars Struen Imsland is a Professor at the Department of Technical Cybernetics at the Norwegian University of Science and Technology (NTNU). He has been serving in this position since 2009 and is a member of the Control Systems research group. His work spans multiple domains within control theory and its applications. Dr. Imsland's research interests include: Model Predictive Control (MPC) for various applications Wind farm control and optimization Process control in petroleum engineering Energy systems optimization and control Virtual flow metering and estimation techniques Grey-box modeling approaches His recent publications demonstrate a strong focus on applying advanced control techniques to renewable energy systems, particularly wind farms, as well as petroleum engineering applications. His work often combines traditional control theory with modern machine learning approaches, creating hybrid methodologies that leverage the strengths of both domains. The research shows increasing attention to handling uncertainty in control systems and integrating renewable energy sources with conventional power systems. Dr. Imsland has received recognition for his contributions to control systems through numerous publications in high-impact journals and conferences. As an advisor, Dr. Imsland has supervised multiple master's students working on diverse control applications, including wind turbine control, building energy management, and petroleum engineering systems. His students have gone on to work on cutting-edge research problems at the intersection of control theory and practical engineering applications.

• Control Systems
• Autonomous Marine Operations and Systems
• Aerospace Engineering
• +۳ مورد دیگر

Tor Arne Johansen is a Professor at the Department of Technical Cybernetics, Norwegian University of Science and Technology (NTNU), and a key researcher at the Center for Autonomous Marine Operations and Systems (AMOS). His work bridges control theory, autonomous systems, and remote sensing technologies. Education : Civil Engineering Degree Doctorate in Technical Cybernetics His research focuses on autonomous marine and aerospace systems , with emphasis on control algorithms , collision avoidance, and hyperspectral imaging . Recent work explores UAV navigation in extreme conditions, MPC for maritime operations, and adaptive Kalman filters for spectroscopic correction. The 15 most recent articles highlight trends in autonomous navigation , UAV control systems , hyperspectral satellite data processing , and risk-aware industrial drone applications . Subfields include RRT algorithms, wave-motion compensation, intention-aware trajectory prediction, and onboard classification for earth observation. Advising : Supervised numerous Master’s and PhD students on topics like collision avoidance, UAV recovery, and hyperspectral analytics. Collaborates with institutions like SINTEF and international researchers in maritime and aerospace domains.

• Energy Conversion Systems
• Distributed Energy Resources (DER)
• Battery Storage Systems
• +۴ مورد دیگر

Nicolae Lucian Mihet is a **Full Professor in Energy Technology** at **Østfold University College, Norway**, affiliated with the Faculty of Information Technology, Engineering and Economics. His academic journey includes roles as Associate Professor (2008–2016) at Politehnica University of Timisoara, Romania, and Research Scientist at Danish Technical University (DTU) and Aalborg University in Denmark. He holds a PhD in Electrical Engineering from Politehnica University of Timisoara. **Research Interests**: Focuses on energy conversion systems, distributed energy resources (DER), smart grids, battery storage systems (BSS), and power electronics. His work emphasizes modeling, simulation, and control of renewable energy systems, including wind turbines, photovoltaics, and EV integration. **Publications**: Authored over 200 papers, 12 books, and guest-edited 5 special issues in journals like *IEEE Transactions* and *Energies*. Key contributions include wind turbine modeling (2004 IEEE award-winning paper), smart grid technologies, and wireless EV charging systems. **Awards**: 2021 Best Researcher Award at Østfold University College; 2005 IEEE IAS Transactions Second Prize Paper Award. **Grants & Projects**: Led 25+ projects, including 6 EEA/ Norway Grants. Coordinates the Master’s Program in Green Energy Technology and manages the *Intelligent Control of Energy Conversion and Storage Systems* lab. Supervised over 100 students and co-advised 3 PhDs. **Collaborations**: Partners with universities in Denmark, Germany, Italy, and Canada. Industry collaborations include ABB, Danfoss, and DONG Energy.

• Numerical linear algebra
• Matrix polynomials and spectral theory
• Stability and perturbation analysis
• +۳ مورد دیگر

Aleksandr Malyshev is Professor of Mathematics at the University of Bergen. His research integrates numerical linear algebra, stability theory, optimisation-based control, and image-processing algorithms, yielding a portfolio of more than 60 peer-reviewed articles and conference contributions. Education & affiliations: Professor, Department of Mathematics, University of Bergen, Norway (present) Previous research and teaching engagements in informatics and applied mathematics at the same university Research interests: Malyshev’s core interest is the theoretical and algorithmic analysis of matrix problems arising in stability, control and imaging. He develops numerically reliable tools for assessing the distance to instability of dynamical systems, constructs preconditioners that accelerate optimisation solvers in real-time model predictive control, and designs variational models for 3-D reconstruction and image denoising. His work frequently combines spectral theory of matrix polynomials with practical issues such as high-performance implementation and medical-image quantification. Across the last decade his articles reveal three dominant strands: (i) stability and perturbation of time-delay and periodic systems, (ii) preconditioned iterative solvers for interior-point and MPC formulations, and (iii) variational and learning-based approaches to depth estimation, surface reconstruction and glenoid-bone assessment. These themes are unified by a common mathematical substrate—exploitation of matrix structure to obtain computationally efficient, numerically trustworthy solutions. Scientific awards & recognition: Regular invited speaker at international workshops on numerical linear algebra and control (e.g., SK Godunov conference 2009, IFAC 2018) Funded principal investigator / co-investigator on Research Council of Norway and EU Horizon Europe grants Advising & grants: Malyshev has supervised numerous MSc and PhD candidates in numerical analysis and scientific computing and currently advises graduate researchers on projects ranging from 3-D machine-vision algorithms to Krylov-subspace preconditioning. Recent grant participation includes EU project 101373 (3-D quantification of glenoid bone loss) and the Norwegian Research Council project 262203 on perfusion-flow simulation. Labs & collaboration: He collaborates closely with the Group for Numerical Methods and Applications at UiB, the Visual Computing cluster at the Department of Informatics, and maintains international partnerships with the Universities of Brest, Lübeck, and several US institutions. These joint efforts feed cross-disciplinary projects combining rigorous matrix analysis with real-world applications in biomechanics, process control, and computer vision.

• Control Engineering
• Automation
• Marine Icing
• +۵ مورد دیگر

Sushmit Dhar serves as an Associate Professor in the Department of Automation and Process Technology at UiT The Arctic University of Norway, focusing on control engineering and automation solutions for Arctic maritime challenges. His work bridges theoretical control methods with practical applications in extreme environments. His research spans: Classical and modern control methods (PID, LQR, MPC) State estimation and Kalman filtering Physics-Informed Neural Networks and Reinforcement Learning for decision support IoT-based automation for maritime operations Marine icing phenomena and sea spray measurement Recent publications demonstrate cutting-edge work in marine icing prediction using LiDAR and capacitive sensors, Arctic road safety systems, and optimization of maritime operations. His research integrates advanced sensing technologies with data-driven modeling to address safety challenges in cold climates, particularly through sea spray measurement innovations and route planning algorithms for fishing vessels and search-and-rescue operations. Dr. Dhar actively contributes to collaborative initiatives: Member of the Sustainable Technology and Safety (STS) research group Member of the IR, Spectroscopy, and Numerical Modelling Research Group Key participant in the SPRICE project (Multidisciplinary approach for spray icing modelling and decision support) His teaching portfolio includes foundational courses in Linear Systems (AUT-2604) and Control Engineering (AUT-2801) for Automation Engineering undergraduates, preparing students for technical challenges in Arctic engineering contexts.