Find Academic Supervisors

• Aerospace Engineering
• Aerodynamics
• Thermodynamics
• +11 more

Richard Hann is a Senior Researcher and Director of the UAV Icing Lab at the Norwegian University of Science and Technology (NTNU) . He is affiliated with the NTNU-AMOS (Center of Excellence on Autonomous Marine Operations and Systems) and CIRFA (Centre for Integrated Remote Sensing and Forecasting for Arctic Operations). Additionally, he serves as a Lead Aerodynamics Engineer and Shareholder at UBIQ Aerospace and promotes Arctic drone applications through projects at the University Centre of Svalbard (UNIS) . Education: M.Sc. in Aerospace Engineering (2013, University of Stuttgart) Ph.D. in UAV Icing (2020, NTNU) Research Interests focus on atmospheric icing effects on unmanned aerial vehicles, including aerodynamic penalties , ice protection systems , and CFD simulations . His work spans cold climate wind energy , environmental forensics , and Arctic fieldwork with UAVs in glaciology and atmospheric pollution studies. The UAV Icing Lab under his leadership develops experimental and numerical tools to address icing challenges in cold climates. His publications (2017–2025) cover topics such as ice accretion modeling, aerodynamic degradation, glacier mapping, and sensor placement for UAVs in Arctic conditions. Collaborations include institutions like AIAA , UiT The Arctic University of Norway , and NATO . Scientific Committees: Contributor to IWAIS 2024 (International Workshop on Atmospheric Icing of Structures) Editorial involvement in AIAA and SAE technical papers

• Spacecraft Attitude Control
• Satellite Operations
• Optimal Control
• +3 more

Bjørn Andreas Kristiansen is a Postdoctoral Fellow at the Department of Technical Cybernetics, NTNU Small Satellite Lab, Norwegian University of Science and Technology (NTNU). His research focuses on optimization of satellite operations, particularly for small satellites and hyperspectral imaging missions like HYPSO-1. His educational background includes: Doctorate (PhD) in Technical Cybernetics from NTNU (2023), with thesis titled "Energy and Time Optimal Spacecraft Attitude Control and Operations" Master of Technology (Civil Engineering) in Cybernetics and Robotics from NTNU (2014-2019), specializing in autonomous systems Kristiansen's research centers on spacecraft attitude control, satellite operations, and optimal control theory. He investigates energy/time optimization for spacecraft maneuvers, with applications in solar-powered satellites, magnetorquer actuation, and thruster-based systems. His work bridges theoretical control methods with practical small satellite technology, emphasizing in-orbit validation and agile maneuvering for Earth observation missions. Analysis of his 2021-2024 publications reveals a cohesive research trajectory focused on advancing satellite operational efficiency. Key themes include hands-off control strategies, slew maneuver accuracy validation for HYPSO-1, and energy-optimal task execution. His work consistently addresses real-world constraints through magnetorquer limitations, power availability, and imaging requirements, demonstrating strong industry-academia collaboration with Space Norway and ESA. No scientific awards were mentioned in the provided text. Kristiansen actively supervises master's students, proposing seven thesis topics for fall 2025 covering super-agile satellite operations, fault detection, re-entry control, and high-accuracy attitude determination. He collaborates with StatSat (Space Norway) for ESA on HYPSO-related projects and served as a research assistant for TTK4100 Cybernetics Introduction from 2020-2023. As ADCS group leader for the HYPSO project since 2021, he leads the Attitude Determination and Control System development within the NTNU Small Satellite Lab. His team handles in-orbit characterization, maneuver validation, and imaging optimization for the HYPSO-1 CubeSat mission, contributing to Norway's growing small satellite capabilities in Earth observation.

• Cybersecurity in industrial systems
• Industry 4.0
• Reliability data
• +3 more

Mary Ann Lundteigen is a Professor in instrumentation systems and safety at the Department of Technical Cybernetics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). Her research focuses on cybersecurity in industrial systems, Industry 4.0, reliability data analysis, instrumented safety systems, and the application of artificial intelligence in security systems, with emphasis on security and risk analysis. Current Role: Professor at NTNU Research Themes: Cybersecurity, AI in safety systems, Risk analysis Collaborations: SINTEF, IEEE, IARIA, ACM Her work integrates safety engineering with modern technologies like digital twins, OPC UA information models, and machine learning for anomaly detection. She emphasizes lifecycle approaches to safety systems and standardized failure reporting. Recent publications address AI implementation in safety-critical environments, cybersecurity for unmanned facilities, subsea pipeline monitoring, and security zones in industrial automation. Her research spans both theoretical frameworks and practical case studies. She supervises numerous Master’s and Ph.D. students on topics ranging from hybrid marine energy systems to cyber-physical safety analysis. Her team collaborates with industry partners on projects related to functional safety and IT-OT integration. Key projects include the ICT security and independence report, Asset Administration Shell implementation, and OPC UA for safety systems research. She also contributes to guidelines for safety equipment follow-up and standardized failure classification in the petroleum sector.

• Control Systems Engineering
• UAV Flight Control
• Nonlinear Model Predictive Control
• +3 more

Dirk Peter Reinhardt is a Postdoctoral Fellow in the Department of Technical Cybernetics at the Norwegian University of Science and Technology (NTNU), Faculty of Information Technology and Electrical Engineering. His research focuses on advanced control systems for unmanned aerial vehicles with particular expertise in nonlinear model predictive control and reinforcement learning applications. Dr. Reinhardt's research spans several key areas in control engineering: Nonlinear Model Predictive Control (NMPC) for UAV flight systems Reinforcement Learning applications in flight control UAV attitude and path-following control systems Flight dynamics modeling and system identification Embedded control systems for autonomous aircraft Sensor calibration and wind tunnel testing His publication record from 2019-2024 demonstrates a progression from fundamental control theory to increasingly complex real-world applications, with numerous field experiments validating theoretical approaches. Dr. Reinhardt frequently collaborates with researchers at NTNU, particularly with Tor Arne Johansen and Sebastien Nicolas Gros, and has published in top venues including IEEE Transactions, IFAC World Congress, and International Conference on Unmanned Aircraft Systems. Dr. Reinhardt's laboratory work involves extensive flight testing of fixed-wing UAVs, including the Skywalker X8 platform, with a focus on validating control algorithms under various conditions including challenging scenarios like icing conditions. His recent research shows growing interest in data-efficient learning methods and robust control for adverse flight conditions.

• Control Systems
• Marine Robotics
• Autonomous Vehicles
• +3 more

Henrik Schmidt-Didlaukies is a postdoctoral fellow at the Department of Technical Cybernetics , Norwegian University of Science and Technology (NTNU). His research focuses on advanced control systems for marine and aerial vehicles, including hybrid feedback, adaptive algorithms, and safety-constrained navigation. Current affiliation: NTNU, Department of Technical Cybernetics Research areas: Control Systems, Robotics, Autonomous Navigation Contact: henrik.schmidt@ntnu.no His recent work includes 3D path-following for autonomous vehicles, Kalman filtering for inertial navigation, and reinforcement learning for marine guidance. Publications in IEEE and IFAC journals highlight his contributions to impedance control, cooperative transport, and bearing-based localization. Key subfields: Adaptive control, underwater robotics, multirotor tracking, and extremum-seeking optimization.

• Chemometrics
• Multivariate Data Analysis
• Machine Learning
• +3 more

Frank Westad is a Professor at the Norwegian University of Science and Technology (NTNU), specializing in Chemometrics , Multivariate Data Analysis , and Near-Infrared Spectroscopy . His research spans environmental monitoring, biomedical applications, and machine learning for complex data systems. Recent publications highlight his work in Statistical extensions for ecosystem monitoring Non-linear chemometric methods Privacy risks in generative data synthesis Deep learning for geophysical data Model validation techniques He has presented at international workshops, including ACM and TUM Munich, and teaches advanced courses in multivariate analysis and machine learning (TK8117, TTK4260). No scientific awards or formal lab affiliations were explicitly mentioned in the provided texts.

Ole Magnus BrasteinView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Ethics in AI
• +4 more

Ole Magnus Brastein is an Associate Professor at the Department of Electrical, IT and Cybernetics, Faculty of Technology, Natural Sciences and Maritime Studies, University of South-Eastern Norway. He also serves as R&D Manager at Kelda Dynamics and operates as a self-employed consultant at BEDKO. With a background as an industry developer and programming experience since age eight, Brastein focuses on bridging research and development while emphasizing practical applications of technology. His research interests center on artificial intelligence (AI) and its societal implications, including ethical decision-making by autonomous systems, the role of AI in the green energy transition, and machine learning applications in smart buildings and industrial contexts. His public lectures explore topics like AI and Ethics , AI in Society , KI og det grønne skiftet , and SmartHus og KI .

• Marine Ecology
• Biodiversity Conservation
• Pollution Impact Assessment
• +3 more

Marianne Nilsen is an Associate Professor at the Department of Civil Engineering and Environmental Sciences , Western Norway University of Applied Sciences (HVL). As a marine ecologist specializing in fjord ecosystems, her work focuses on biodiversity preservation, pollution effects, and climate change impacts on benthic organisms. She actively supervises students at all educational levels.

• Musculoskeletal Health
• Machine Learning in Healthcare
• Spinal Disorders
• +4 more

Bjørnar Berg is a Postdoctoral Fellow at the Department of Rehabilitation Science and Health Technology , Oslo Metropolitan University . His research focuses on applying machine learning to develop prediction models for musculoskeletal health outcomes, particularly in spinal disorders and knee/hip osteoarthritis . Key Research Areas: Personalized healthcare systems using AI Clinical prediction models for spinal pain Comparative effectiveness of surgical vs. non-surgical treatments Functional performance assessment after musculoskeletal injuries Recent Trends: 2024 studies on lumbar disc herniation surgery prediction models 2024 work on AI-driven disability/pain forecasting 2023-2022 OPTIKNEE consensus projects for post-injury knee health Collaborations: Co-author with international experts in British Journal of Sports Medicine Partnerships with AktivA Quality Register and HUNT Study

• Quantum Physics
• Condensed Matter Physics
• Quantum Technologies
• +4 more

Jeroen Danon is a Professor at the Department of Physics, Norwegian University of Science and Technology (NTNU). His research focuses on theoretical condensed matter physics and quantum technologies, particularly on solid-state quantum devices such as spin qubits, superconducting qubits, and quantum sensors. He collaborates closely with experimental groups to advance the design of next-generation quantum systems. His research spans semiconductor spin qubits, superconducting qubit architectures, and topologically protected quantum states. He has explored machine learning for quantum device tuning and control, aiming to enhance fault-tolerant quantum computing and sensing. His work also investigates magnon-plasmon polaritons and spin pumping phenomena in heterostructures. Professor Danon teaches advanced courses in quantum transport theory (FY8909) and quantum information (TFY4355), alongside introductory courses on quantum transport. His contact information includes the email jeroen.danon@ntnu.no and office location at Realfagbygget, E5-127, Gløshaugen, NTNU. Research trends include: Quantum devices for computing and sensing Spin-orbit coupling and Majorana fermions Machine learning applications in quantum control Josephson junctions and diodes Magnon-plasmon interactions Multi-carrier spin blockade in graphene

• Healthy Aging
• Mobility Impairments
• Fall Prevention
• +7 more

Jorunn Hege Lægdheim Helbostad is a Professor at the Department of Neuromedicine and Movement Science , Norwegian University of Science and Technology . As a physiotherapist and leading researcher in healthy aging , she focuses on mobility impairments , fall prevention , and digital health technology for older adults. Her work bridges geriatric medicine and movement science , emphasizing balance assessment , gait analysis , and physical activity monitoring . Helbostad has led major projects such as PreventIT (EU-funded personalized health initiative), ADAPT (Research Council of Norway-funded fall risk assessment), and Mobilise-D (validating wearable sensors for clinical endpoints). Her research integrates machine learning and digital mobility outcomes to enhance rehabilitation strategies and policy implementation in aging populations . Her publications span biomedical engineering , gerontology , and clinical research , with a focus on real-world mobility monitoring , hip fracture recovery , and lifestyle-integrated exercise programs . Collaborations with institutions across Europe highlight her role in multidisciplinary studies addressing functional decline and postoperative outcomes in older adults.

• Musculoskeletal Pain
• Low Back and Neck Pain Management
• Physical Activity and Sedentary Behaviour Epidemiology
• +5 more

Anna Marcuzzi is a Postdoctoral Fellow at the Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU). Her research focuses on musculoskeletal pain epidemiology and digital health interventions, with significant contributions to AI-based pain management tools and population health studies using Norwegian registry data. Her research portfolio centers on: Musculoskeletal pain mechanisms and comorbidities Digital therapeutics for low back/neck pain Physical activity and sedentary behaviour determinants Chronic pain interactions with mental health and metabolic conditions Cross-cultural pain measurement validation Epidemiological methods using large cohort studies Analysis of her 15 most recent publications (2021-2025) reveals a dominant focus on developing and evaluating AI-driven self-management applications for musculoskeletal pain, particularly through randomized clinical trials. She has made substantial contributions to systematic reviews on physical activity determinants in children (DE-PASS project) and investigates complex pain comorbidities using longitudinal data from the Norwegian HUNT study, examining relationships between multisite pain, insomnia, diabetes risk, and mental health outcomes. No scientific awards were documented in the available information. Details regarding student advising, research grants, or laboratory affiliations were not specified in the provided materials.

• Allergy-related disease prevention
• Immunological components of breast milk
• Clinical trials
• +4 more

Melanie Rae Simpson is an Associate Professor at the Department of Public Health and Nursing , Norwegian University of Science and Technology (NTNU). Her research focuses on allergy-related disease prevention, breast milk immunology, and clinical trials. Education: PhD in Medicine (NTNU, 2018), Masters in Medical Statistics (Newcastle University, 2015) Key Research Areas: Allergy prevention, microbiota development, maternal-child health, probiotics, clinical trial endpoints Recent Article Trends: 2025 work includes studies on domestic violence and psychiatric care; 2024 research spans cancer cachexia endpoints, PCOS outcomes, and music therapy for delirium.

• Software Engineering
• Programming Languages
• Runtime Verification
• +3 more

Volker Stolz is a Professor at the Department of Informatics, University of Bergen, within the Faculty of Mathematics and Natural Sciences. He teaches Mobile Application Development (DAT153), Model-driven Software Engineering (DAT355), Model Checking (PCS955), and Refactoring (DAT159). He serves as program director for INF/INF-F/INF-H programs and exchange coordinator for DATA & INF, with his office located at Kronstad (D403). His research focuses on Software Engineering, particularly Programming Languages and Software Testing, where he develops productivity tools to create safer, faster code with fewer crashes in applications. His work spans Runtime Verification, Formal Methods, and Internet of Things (IoT), emphasizing model-driven approaches for reliable software systems in mobile and web environments. Recent publications (2024-2025) demonstrate deep engagement with Runtime Verification for timed systems, advanced software testing techniques like clone elimination, and emerging applications in IoT data acquisition. His work bridges theoretical computer science with practical engineering challenges, particularly in time-series analysis and formal verification of concurrent systems. Stolz leads significant research initiatives including: Ongoing: MSCA DN "TUAI - Towards an Understanding of Artificial Intelligence" Completed: EU H2020 project "COEMS - Continuous Observation of Embedded Multicore Systems" Completed: AURORA bilateral project "SecuTrace" (NO/FR, 2020-2022) Completed: DIKU/CAPES bilateral project "Modern Refactoring" (NO/BR, 2017-2021) He serves as General Chair for ECOOP'25, a premier conference in object-oriented programming. He actively contributes to the Smart Software System (S3) research group and IoT research lab at the University of Bergen, driving innovation in software verification and reliable system development through collaborative projects and industry partnerships.

• Signal Processing for Wireless Communications
• Machine Learning for Cyber-Physical Systems
• Cloud and Edge Computing
• +3 more

Min Dong is a Professor and Research Excellence Chair at the Department of Electrical, Computer and Software Engineering, Faculty of Engineering and Applied Science, Ontario Tech University. She holds a status-only Professor appointment at the University of Toronto's Department of Electrical and Computer Engineering and has served as Associate Dean (Academic) at Ontario Tech University (2017, 2021-2022). With a Ph.D. from Cornell University (2004), she previously worked at Qualcomm Research (2004-2008) before joining academia. Her research focuses on Signal processing for wireless systems Machine learning in cyber-physical networks MIMO transmission optimization Cooperative communication Smart energy systems with storage Publications highlight advancements in federated learning over wireless channels, edge computing optimization, and robust beamforming in massive MIMO networks. Key trends include leveraging temporal similarity for distributed optimization, handling imperfect channel state information (CSI) in network virtualization, and integrating machine learning with traditional signal processing frameworks. Scientific recognitions include IEEE Fellow Early Researcher Award (2012) Multiple Best Paper Awards (IEEE ICCC 2012, SPAWC 2021, ICASSP 2016) NSERC Discovery Accelerator Supplement (2019) She has supervised numerous Ph.D. and MASc. students now employed at institutions like Ericsson, Microsoft, and AMD Canada. Professional leadership roles include Senior Area Editor for IEEE Transactions on Signal Processing, Associate Editorships, and organizing conference tracks at ICASSP and Globecom.