جست‌وجوی استاد و پژوهشگر

Robert Oscar Davidمشاهده پروفایل

پژوهشگر

• Mixed-phase Clouds
• Ice Nucleation
• Cloud Microphysics
• +۳ مورد دیگر

Robert Oscar David is a Researcher at the Section for Meteorology and Oceanography, University of Oslo, Norway, where he has served as a Postdoctoral Fellow since 2019 after completing his Doctorate (Dr. Sc.) at ETH Zurich, Switzerland. His role focuses on advancing cloud microphysics and atmospheric science through experimental and observational methodologies. His academic background includes: Doctorate (Dr. Sc.) from ETH Zurich, Switzerland (2015-2019) David specializes in mixed-phase clouds (MPCs) and ice nucleating particles (INPs) , conducting in situ measurements to analyze cloud particle distribution, the Wegener-Bergeron-Findeisen process efficiency, and MPC glaciation dynamics. His INP research encompasses field/lab measurements of ice formation mechanisms, physio-chemical properties, and parametrization development. He innovatively applies holography and machine learning for phase discrimination and ice crystal classification, bridging meteorology with computational techniques to address climate-relevant questions in atmospheric physics. Analysis of his 15 most recent publications (2019-2022) reveals a dominant focus on mixed-phase cloud microphysics, ice nucleation mechanisms, and aerosol-cloud interactions. Key trends include spatial/temporal characterization of cloud particles, secondary ice effects, INP source identification (e.g., pollen, soot, snowmelt), and development of novel instrumentation like DRINCZ and FINC. His work frequently employs Alpine field campaigns, satellite remote sensing, and laboratory experiments to quantify cloud phase transitions and their climate impacts, with strong emphasis on high-latitude and mountainous regions. David actively contributes to major research initiatives: BRACE-MY – Boosting ReseArch CapabilitiEs of Romanian Cloud MicrophYsics Centre ERC Consolidator Grant 'STate-dEPendent Cloud feedbacks: enHANcing understanding and assessing Global Effects' ERC Start-up grant 'Mixed-phase clouds and climate (MC2)' IceSAFARI – Safer flights for drones through icing condition analysis As a core member of the University of Oslo's Meteorology research group, he collaborates on cloud microphysics projects involving holographic particle sensors, INP characterization, and climate model parametrization. His work integrates observational data with theoretical frameworks to improve understanding of cloud processes in weather and climate systems.

Federica Ghioneمشاهده پروفایل

پژوهشگر ارشد

• Seismic Hazard
• Seismic Risk
• Geohazards
• +۲ مورد دیگر

Federica Ghione is a Doctoral Research Fellow at the Department of Geosciences , University of Oslo , and a seismologist at NORSAR (Kjeller, Norway). She is currently pursuing a 4-year PhD project titled GeobyIT/Geodata-based Machine Learning for real-time urban risk reduction systems , funded through a collaboration between NORSAR, NGU, UiO, and the Municipality of Oslo. Seismic hazard Seismic risk Geohazards Machine learning for urban risk reduction Her research focuses on seismic hazard and risk assessment, particularly in Norway and Svalbard. She integrates geodata with machine learning techniques to model urban risk reduction systems in Oslo and explores hybrid probabilistic models for seismic hazard in tectonically complex regions like Northeast India and Bhutan. Her work combines distributed seismicity analysis with finite fault modeling. Notable publications include studies on earthquake hazards in Norway, Vs30 estimation methodologies for the Oslo area, and building stock classification using machine learning algorithms. These contributions highlight her expertise in seismology, geophysical modeling, and data-driven approaches to urban safety. She holds qualifications from the University of Pavia , including a Master’s in Applied Geological Sciences and a Bachelor’s in Geological Sciences. Her professional activities are centered at both the Geologibygningen (Oslo) and NORSAR (Kjeller).

Owen Rohwer Huffمشاهده پروفایل

پژوهشگر ارشد

• Geophysics
• Machine Learning
• Seismic Data Processing
• +۳ مورد دیگر

Owen Rohwer Huff is a Research Fellow in the Department of Geosciences at the University of Oslo, pursuing an industrial PhD in collaboration with Aker BP. His work focuses on applying machine learning techniques to geophysical challenges, particularly in seismic data processing and reservoir monitoring. PhD Fellow (Industry), University of Oslo (2022–) Industrial Partner: Aker BP Supervisors: Professor Jan Inge Faleide (UiO), Jan Erik Lie (Aker BP), Aina Juell Bugge (Aker BP) MSc in Geophysics, Colorado School of Mines (US) Research Interests center on: Reconstruction of missing near offset data in marine seismic surveys Angle stack alignment and conditioning for AVO (Amplitude Versus Offset) analysis Deep learning architectures (e.g., convolutional neural networks) for geophysical data processing Distributed Acoustic Sensing (DAS) for microseismic monitoring Key Publications demonstrate trends in: Machine learning for near offset gap restoration in marine seismic data Angle stack conditioning techniques via convolutional neural networks Guided wave eigenfunction theory for unconventional reservoir characterization Microseismic event classification using DAS and CNNs Academic Code contributions include open-source CNNs for seismic data processing available on GitHub: Repository: near_offset_reconstruction_CNN Features: UNet architecture, synthetic generation code, trained models Requirements: Data dimensions of 448×40 (CMPs) or 448×72 (shots) for processing

Benjamin James Knoxمشاهده پروفایل

دانشیار

• Cybersecurity
• Human-Computer Interaction
• Cognitive Psychology
• +۳ مورد دیگر

Benjamin James Knox is an Associate Professor at the University of South-Eastern Norway's Department of Welfare, Management and Organization. His research focuses on the intersection of cybersecurity, cognitive psychology, and human-computer interaction. He leads projects related to cyber defense training, situational awareness, and neuroergonomic approaches to security. Primary Affiliation: University of South-Eastern Norway Department: Welfare, Management and Organization Role: Associate Professor Email: benjamin.knox@hiof.no Research Themes: Dr. Knox's work examines how cognitive processes and emotional regulation affect cybersecurity performance. Key areas include gamification for training, 3D visualization in cyber defense, and combating disinformation attacks through psychological interventions. Scientific Contributions: His projects like ACDICOM and ADVANCES address improving cyber team communication and human performance in digital security contexts. Publications span journals such as Frontiers in Psychology and NATO Science and Technology Organization reports. Collaborations: Active in multi-institutional collaborations with institutions like Norwegian Defence University College (FHS), NTNU, TALTECH, and international partners in Germany and the US.

• Statistics
• Optimization
• Machine Learning
• +۳ مورد دیگر

Etor Arza Gonzalez is a Postdoctoral Fellow at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Technical Cybernetics and the Department of Language and Literature. His research focuses on Statistics and Optimization, with applications in algorithm runtime prediction, policy search, and random variable analysis. He develops open-source tools like RVCompare (random variable comparison), RTDHW (CPU runtime prediction), and GESP (early stopping for policy search), primarily in R, C++, and Python. Contact: etor.arza@ntnu.no

• Control Theory
• Marine Cybernetics
• Robotics
• +۳ مورد دیگر

Erlend Andreas Basso is a postdoctoral researcher at the Department of Technical Cybernetics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on applying Control Theory , Marine Cybernetics , and Robotics to develop advanced control systems for autonomous vehicles and robotic manipulators. Academic Affiliation: Norwegian University of Science and Technology (NTNU) Department: Technical Cybernetics Research Focus: Autonomous navigation, safety-critical control, and hybrid feedback systems for marine and aerial vehicles Basso's work bridges Feedback Control , Optimal Control , and Autonomous Systems through mathematical modeling and algorithm development. His publications demonstrate expertise in 3D Guidance Systems , Sliding Mode Control , and Task-Priority Frameworks , with applications in underwater robotics, collision avoidance, and marine vehicle autonomy. Recent trends in his Google Scholar profile show increasing emphasis on Machine Learning Integration for control systems, Reinforcement Learning for path optimization, and Safety-Critical Systems in maritime environments. His collaborations with researchers at NTNU and international institutions reflect cross-disciplinary approaches to Marine Technology and Underwater Localization . For contact, his primary email is erlend.a.basso@ntnu.no . His GitHub profile includes technical repositories related to embedded systems, multirotor dynamics, and OSQP quadratic programming solvers.

• Aerospace Engineering
• Aerodynamics
• Thermodynamics
• +۱۱ مورد دیگر

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
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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 Brasteinمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Ethics in AI
• +۴ مورد دیگر

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
• +۳ مورد دیگر

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
• +۴ مورد دیگر

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