جست‌وجوی استاد و پژوهشگر

Alvaro Fernandez Quilezمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Responsible AI
• AI Ethics
• +۱۳ مورد دیگر

Alvaro Fernandez Quilez is an Associate Professor in Artificial Intelligence at the Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger. He leads the Stavanger AI Laboratory (SAIL), fostering interdisciplinary AI research with a focus on healthcare and education applications. Research Interests: His work centers on responsible AI, emphasizing ethics, fairness, transparency, and uncertainty in AI systems. He applies deep learning and machine learning techniques to medical imaging, particularly in prostate cancer and neurodegenerative diseases like Alzheimer’s and Parkinson’s. His research integrates algorithmic innovation with clinical relevance, addressing challenges in data scarcity, bias, and model interpretability. The recent publications highlight a strong trend in developing and evaluating AI models for diagnostic support in radiology and neurology. Key themes include uncertainty quantification, self-supervised learning, synthetic data generation via GANs, and fairness analysis across gender and centers. The work spans from foundational AI methods to their clinical translation in multi-center studies. Teaching and Academic Leadership: He coordinates the course DAT105 - AI for everyone and has contributed as a guest lecturer in bioinformatics, technological foundations, and PhD ethics, particularly on AI and ethics. He is also enrolled in a PhD supervisory qualification program, underscoring his growing role in graduate education. Advising and Grants: While specific students and grants are not listed in the text, his leadership of SAIL and active publication record suggest involvement in research supervision and project funding. His collaborations span multiple institutions and disciplines, indicating strong team-based research efforts. Laboratories and Teams: He leads the Stavanger AI Laboratory (SAIL), which serves as the central hub for AI research at the University of Stavanger, promoting collaboration across departments and with external partners in healthcare and technology.

Joachim Reuderمشاهده پروفایل

استاد

• Meteorology
• Atmospheric Boundary Layer
• Wind Energy Meteorology
• +۳ مورد دیگر

Joachim Reuder is a Professor and Research Group Leader at the Geophysical Institute, University of Bergen, affiliated with the Bjerknes Centre for Climate Research. His research focuses on turbulence in the atmospheric boundary layer, wind energy meteorology, and the application of drones for atmospheric measurements. He leads the Meteorology research group and collaborates with the Bergen Offshore Wind Centre. His work combines field observations with advanced simulations, emphasizing stable boundary layers, wind turbine wake dynamics, and lidar technology validation. Key projects include the ISOBAR Arctic field campaigns, COTUR offshore turbulence studies, and the SAMURAI-S drone-based turbulence investigation. Publications highlight contributions to lidar data analysis, boundary layer modeling, and wind energy applications. He has organized conferences and contributed to editorial roles, underscoring his influence in atmospheric science and meteorology.

Jim Tørresenمشاهده پروفایل

استاد

• Artificial Intelligence
• Robotics
• Biology-Inspired Computing
• +۶ مورد دیگر

Jim Tørresen is a Professor of Computer Science at the Department of Informatics, University of Oslo, where he has been employed since 1999 (Associate Professor 1999-2005, Professor since 2006). He serves as group leader for the Robotics and Intelligent Systems (ROBIN) research group and is also a Principal Investigator at the Centre for Interdisciplinary Studies in Rhythm, Time and Motion (RITMO). His academic career includes visiting positions at Cornell University's Creative Machines Lab (2010-2011) and Kyoto University in Japan (1993-1994). His educational background includes a Dr.ing. (Ph.D.) in Computer Architecture from the Norwegian University of Science and Technology (1996) and an M.Sc. in Computer Architecture from the same institution (1991). Before his academic career, he worked in industry at Navia Aviation (1998-1999) and NERA Telecommunications (1996-1998). Tørresen's research spans artificial intelligence, robotics, and bio-inspired computing. His work focuses on biology-inspired algorithms, programmable logic (FPGA), robotics (simulation, prototyping, control), and human-robot interaction. He has made significant contributions to areas including evolutionary computing, reconfigurable hardware, and adaptive systems. His research often bridges theoretical computer science with practical applications in healthcare, music, and industrial settings. His recent publications demonstrate a strong focus on human-robot interaction, particularly in healthcare contexts for elderly care, as well as applications in sports science, musical robotics, and geological engineering. His work shows a consistent pattern of interdisciplinary research that combines machine learning techniques with domain-specific challenges. Tørresen has also authored a popular science book on artificial intelligence in the "what is" series by Universitetsforlaget, which discusses fundamental concepts, methods, future perspectives, and ethical aspects of AI. He has been active in academic leadership, serving as General Chair for the 22nd International Conference on Field Programmable Logic and Applications (FPL) in 2012 and the 9th Joint IEEE International Conference of Developmental Learning and Epigenetic Robotics in 2019. As group leader of ROBIN, he oversees research on intelligent systems that operate in dynamic environments requiring runtime adaptation. The group works at both fundamental and applied levels, using evolutionary algorithms for robot learning and machine learning techniques for classification and recognition tasks in various application domains.

• Cognitive Science
• Psycholinguistics
• Multilingualism
• +۴ مورد دیگر

Jon Andoni Duñabeitia is a Full Professor at the School of Languages and Education of Universidad Nebrija in Madrid. He serves as Director of the Centro de Investigación Nebrija en Cognición (CINC) and the International Chair in Cognitive Health . With an h-index of 43 (Scopus), he has published 170+ articles across psycholinguistics, multilingualism, cognitive training, and virtual reality applications in education. His research examines how language processing interacts with cognitive load, emotional modulation, and technological innovation. Principal Investigator for 8+ projects funded by Spanish Government, Basque Government, BBVA Foundation Associate Editor and Editorial Board Member of high-impact journals Recognized among Spain's top 3% scientists across all disciplines Recent publications span topics including: Second-language reading dynamics in VR environments Multilingual cognitive interactions in neurological conditions Emoji/typographic effects on word processing Computerized cognitive assessment and training systems He actively contributes to scientific meetings as invited speaker across Europe, Asia, and Americas. His work bridges basic research in psycholinguistics with applied technologies for cognitive health.

Adín Ramírez Riveraمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Representation Learning
• +۶ مورد دیگر

Adín Ramírez Rivera is a Professor in the Digital Signal Processing and Image Analysis (DSB) group at the Department of Informatics, University of Oslo. His research focuses on representation learning and computer vision, particularly exploring machine learning methods to describe and understand visual data. He is a Senior Member of the IEEE and a member of the ELLIS Society. Education : PhD from Kyung Hee University's Image Processing Lab, South Korea; Bachelor's degree in Engineering from Universidad de San Carlos de Guatemala, majoring in Computer Science and Systems Engineering. Ramírez Rivera's research spans diverse computer vision tasks including facial analysis, object detection, image enhancement, and vision transformers. His work emphasizes self-supervised learning, fair representation learning, and novel neural network architectures for image segmentation and classification. Recent publications highlight trends in vision transformers, crowd counting, facial expression recognition, and fair representation learning. His articles frequently address statistical modeling, feature extraction, and deep learning techniques for visual tasks. Scientific Awards : Senior Member of the IEEE, Member of the ELLIS Society. He collaborates with researchers across institutions, contributing to projects involving anomaly detection, multilingual translation, and astrophysical modeling. His lab affiliations include the Digital Signal Processing and Image Analysis group and the Section for Machine Learning at the University of Oslo.

Ida Scheelمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Data Science
• Machine Learning
• +۷ مورد دیگر

Ida Scheel is an Associate Professor in Statistics and Data Science at the University of Oslo , Department of Mathematics. She specializes in Bayesian hierarchical modeling, recommendation systems, and stochastic processes on networks. Her research interests include: Bayesian statistics and model diagnostics Data science applications in environmental and health domains Network-based machine learning Uncertainty quantification in predictive modeling Recent publication trends show a focus on Bayesian model validation, machine learning for product adoption prediction, and real-estate analytics. She contributes to interdisciplinary projects like BigInsight and CELS . Scientific awards : Sverdrup Prize for Young Researchers (2011) Advising : Supervised 8 PhD students (main/co-supervisor) in areas spanning Bayesian causal effects, neural network survival analysis, and model conflict detection. Key grants include participation in the Data Science@UiO and Integreat projects. Labs/teams : Active member of the Center for Computational Inference in Evolutionary Life Science (CELS) and the BigInsight center.

• Cold Climate Hydrology
• Hydropower Environmental Impact Assessment
• River Ice Formation and Modeling
• +۳ مورد دیگر

Knut Tore Alfredsen is a Professor at the Department of Water and Environmental Engineering at NTNU. He specializes in cold climate hydrology, river ice dynamics, and environmental impacts of hydropower. His work integrates field measurements, modeling, and data analysis to address challenges in regulated river systems. Research Focus: Environmental impacts of hydropower, hydrological modeling, and river ice processes. Projects: Trygg Elv (flood detection tools), Hydro Connect (climate mitigation), and HydroFlex (fish-friendly turbines). Supervised 17 PhD/MSc students focusing on topics like hydropeaking, ice formation, and green infrastructure. Led the 25th IAHR Symposium on Ice (2020) and authored/co-authored over 50 peer-reviewed publications. Publications emphasize numerical modeling of ice dynamics, land-use impacts on hydrology, and hydropower sustainability. He actively collaborates with stakeholders on projects like the ALB laser initiative for river mapping. Labs/Teams: HydroCen (Renewable Energy Center), NTNU’s Water Resources Engineering Group.

Thor Inge Fossenمشاهده پروفایل

استاد

• Marine craft hydrodynamics
• Motion control systems
• Navigation systems
• +۷ مورد دیگر

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.

• Reservoir Engineering
• CO2 Enhanced Oil Recovery & Storage
• Data-Driven Reservoir Modeling
• +۵ مورد دیگر

Ashkan Jahanbani Ghahfarokhi is an Associate Professor in Reservoir Engineering at NTNU’s Department of Geosciences since 2019. He leads the CEORS Gemini Centre (CO2 Enhanced Oil Recovery & Storage) and is a core member of the BRU21 Reservoir Management group. His research focuses on data-driven subsurface modeling, CO2 storage, and optimization of oil recovery processes. Education: PhD, NTNU (2015); MEng, University of Calgary (2009); MSc/BSc, Petroleum University of Technology, Iran (2006–2009). Roles: Head of Reservoir Engineering Group (2021–2022), Project Manager for NORHED II (2022), and NTNU’s Outstanding Academic Fellow (2022–2026). Research interests include CO2-EOR/Storage, machine learning applications, proxy modeling, and reservoir simulation. He has supervised 20+ students and published over 40 journal/conference papers. Awards include DNVA postdoc scholarship (2015–2017) and PoreLab postdoc (wettability studies). Teaching: Masters/PhD courses in reservoir fluids, simulation, and geomechanics. Guest editor for Energies (AI in Oil & Gas).

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +۳ مورد دیگر

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.

• Embedded Systems
• Digital Signal Processing
• Multimedia Systems
• +۵ مورد دیگر

Per Gunnar Kjeldsberg is a Professor at the Department of Electronic Systems, Norwegian University of Science and Technology (NTNU), and currently serves as acting head of the institute. His research focuses on embedded heterogeneous multi-processor systems , particularly in multimedia and digital signal processing applications . He has led and participated in numerous national and international projects, including EU Horizon 2020 initiatives like READEX (as work package leader) and Tulipp (as principal researcher), and supervises the MSCA-IF project Palmera . Kjeldsberg is a Senior Member of IEEE and part of the European Network of Excellence HiPEAC . Education : Sivilingeniør (MSc) in Electrical Engineering (1992), PhD (2001) from Norwegian Institute of Technology (NTH)/NTNU His work spans energy-efficient computing , radiation-hardened memory design for space applications, and dynamic hardware management . Publications include co-authoring three books and over 150 peer-reviewed articles in journals and conferences. He leads the Circuit and Radio Systems group and drives a strategic NTNU initiative on Energy Efficient Computing Systems . Kjeldsberg has held visiting researcher roles at imec (Belgium), University of California, Irvine, imec Netherlands (Holst Centre), and University of New South Wales (Australia). Scientific Awards : Senior Member of IEEE Mikroelektronikkprisen (2006–2015)

• Computational Chemistry
• Molecular Simulation
• Path Sampling Methods
• +۳ مورد دیگر

Professor Titus Sebastiaan van Erp is affiliated with the Department of Chemistry at the Norwegian University of Science and Technology (NTNU), where he has worked since 2016. His research focuses on advancing molecular simulation techniques to study complex biological and industrial processes without approximations, particularly through path sampling methods for rare events. 2016 – Present: Professor, NTNU 2012 – 2016: Associate Professor, NTNU 2006: Centre-of-Excellence Fellow, Leuven 2004: Marie Curie Fellow His research develops innovative methodologies like RETIS and REPPTIS to enhance simulation accuracy and expand accessible time/system scales. He has supervised students in DNA denaturation, electron transfer reactions, and protein folding studies. Recent publications analyze NaCl dissociation, ABL-imatinib kinetics, and permeation mechanisms. His work involves Python-based PyRETIS software development and collaborations across computational chemistry, biophysics, and materials science. 2025: NaCl Dissociation via Predictive Power Path Sampling 2025: RETIS/REPPTIS for Biomolecular Kinetics 2024: PyRETIS 3 for Boundary-Free Rare Events Scientific recognitions include: Centre-of-Excellence Fellowship (2006) Marie Curie Fellowship (2004) He has advised multiple students in masters theses on molecular simulation, including projects on DNA unwinding, electron transfer, and protein folding. His lab integrates algorithm development with applications in chemical reactions, biomolecular systems, and nanoscale materials.

Lisa Hanssonمشاهده پروفایل

استاد

• Transport Policy and Governance
• Urban Sustainable Transport/Mobility
• Socio-technical Change
• +۳ مورد دیگر

Lisa Hansson is a Professor of Community Planning at Molde University College, specializing in urban governance and transport policy. She is affiliated with the Logistics Department and actively contributes to sustainable mobility, socio-technical change, and multi-level governance research. PhD in Science and Technology Studies (2011), Linköping University MSc in Political Science/Public Administration (2005), Gothenburg University BA in Human Geography/Urban Planning (2003), Karlstad and Gothenburg Universities Her research focuses on sustainable transport systems, visual representation in planning, and policy adaptation. She leads externally funded projects like LEAD (Digital Twins for logistics) and SNAPSHOT (e-commerce transport), with partners including SINTEF and K2 Sweden. Her work bridges political science and transport governance, challenging economic-technical discourses. Recent articles analyze equity in 15-minute city planning, social justice in transport protests, and regulatory governance for autonomous vehicles. She chairs the WCTRS SIG G1 Transport Governance group and serves on the Thredbo Conference Committee. 2023: Co-authored Public Participation in Transport in Times of Change (Emerald) 2021: Chapter on Transport Policy and Governance (Elsevier) 2020: Editorial in Transportation Research Part A Lisa teaches MA/BA courses like Smart Mobility, European Transport Policy, and Future Cities. She supports Master’s and PhD research in sustainable urban development and transport policy.

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Ørjan Grøttem Martinsenمشاهده پروفایل

استاد

• Bioimpedance
• Biomedical Physics
• Electronics and Instrumentation
• +۳ مورد دیگر

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.