جستجوی استاد راهنمای دانشگاهی

• Early Childhood Education and Care
• Child Development
• Self-regulation
• +۵ مورد دیگر

Ingunn Størksen is a Professor in the Norwegian Centre for Learning Environment and Behavioral Research in Education at the Faculty of Arts and Education , University of Stavanger. Her research focuses on Early Childhood Education and Care (ECEC) , Child Development , Self-Regulation , and Social Development , with specialized interests in parental divorce impacts and the application of Q Methodology . Størksen leads major projects such as SELMA (2021–2025), examining social-emotional learning in ECEC, and the Agder Project (2014–2019), which developed play-based curricula. Her work integrates Quantitative Research Methods to assess educational interventions and child outcomes, including the Ani Banani Math Test and School Readiness studies. Recent publications highlight the role of Executive Functions in academic achievement and the impact of Parental Socioeconomic Status on child development. She supervises PhD candidates studying topics like social competence, optimism, and classroom quality assessments. Størksen has authored books on playful learning and child wellbeing, including Livsmestring og livsglede i barnehagen and Lekbasert læring .

Eva Raulsمشاهده پروفایل

استاد

• Computational Materials Science
• Surface Physics
• Theoretical Physics
• +۷ مورد دیگر

Eva Rauls is a Professor of Materials Physics in the Department of Mathematics and Physics at the University of Stavanger, under the Faculty of Science and Technology. Her research focuses on computational investigations of molecular adsorbates, catalytic properties, and electronic behavior of molecules on surfaces such as metals and graphitic materials. Her research interests include computational materials science, surface physics, supramolecular materials, and applications in CO2 capture and gas separation. She employs first-principles and semi-empirical methods, particularly density functional theory (DFT), to model and predict the behavior of functional materials. Current projects involve the design of supramolecular materials and optimization of metal-organic frameworks (MOFs) for environmental applications. The recent publication trends highlight a strong focus on pillararenes for CO2 adsorption, with detailed DFT studies analyzing functional group effects, cavity size, and molecular interactions. These works span chemistry, materials science, and environmental engineering, demonstrating interdisciplinary impact. Scientific awards include: Feodor-Lynen Fellowship of the Alexander-von-Humboldt-Society (2004–2006) Eva Rauls advises students such as Ho Quoc Duy and collaborates closely with the chemistry department and researchers like Uwe Gerstmann and Christoph Tegenkamp. Her work is supported by active research projects in functional material design for sustainable technologies. She regularly presents at international conferences including ECOSS, VCTP, and European Graphene Forum. She leads research efforts in atomistic modeling and computational studies of 2D heterostructures and molecular systems, indicating an active research group focused on theoretical and computational materials physics.

Alf Kristian Gjerstadمشاهده پروفایل

دانشیار

• Automated Drilling
• Drilling Optimization
• Rate of Penetration (ROP) Optimization
• +۱۷ مورد دیگر

Alf Kristian Gjerstad is an Associate Professor in the Department of Energy and Petroleum Engineering at the University of Stavanger, Faculty of Science and Technology. His research focuses on automated drilling systems, optimization of drilling parameters (such as rate of penetration and tripping speed), and computational modeling for real-time hazard detection (e.g., kicks, losses, differential sticking). He is based in Stavanger, Norway, and can be reached at alf.k.gjerstad@uis.no. His research interests span automated drilling , drilling fluid rheology , mechanical and flow modeling , multiphase flow , and geothermal drilling . He emphasizes practical simulation tools for real-time applications, particularly in high-pressure, high-temperature (HPHT) environments. His work bridges petroleum engineering, fluid dynamics, and control systems, promoting interdisciplinary collaboration. The recent publications (2012–2024) highlight a strong trend in modeling non-Newtonian and multiphase flows in drilling, with applications in surge/swab pressure prediction, gas kick simulation, and real-time optimization. His work frequently appears in SPE journals and ASME/IEEE conferences, indicating a focus on both theoretical and applied aspects of drilling engineering. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: While specific students and grant details are not listed, Dr. Gjerstad has co-authored research with academic and industry collaborators, suggesting involvement in funded projects and student supervision. His publications in optimization and control systems imply engagement in research teams and potential advising of graduate students in petroleum and mechanical engineering. Labs and Teams: Though not explicitly mentioned, his research in real-time modeling and automated drilling suggests affiliation with simulation labs or drilling automation research groups at the University of Stavanger, possibly involved in digital oilfield or smart drilling initiatives.

• Petroleum Engineering
• Drilling Engineering
• Wellbore Stability
• +۱۲ مورد دیگر

Bernt Sigve Aadnøy is a Professor in the Department of Energy and Petroleum Engineering at the University of Stavanger, Faculty of Science and Technology. His work bridges theoretical and applied petroleum engineering, with a strong emphasis on drilling operations, well design, and geomechanics. His research focuses on drilling optimization, wellbore stability, drilling fluids, and smart well systems. He has extensively studied the use of nanoparticles in drilling fluids, rate of penetration modeling, torque and drag in 3D wells, and closed-loop drilling optimization. His work integrates computational modeling, laboratory experiments, and field case studies. The recent publications highlight a consistent trend in applying advanced modeling techniques—including machine learning, finite element analysis, and stochastic optimization—to solve complex drilling challenges. Topics include nanoparticle-enhanced fluids, real-time mechanical specific energy minimization, and autonomous downhole control systems, reflecting a strong interdisciplinary approach combining petroleum engineering with data science and control theory. Bernt Sigve Aadnøy has collaborated with numerous researchers and students, contributing to advancements in drilling safety, efficiency, and sustainability, particularly in challenging environments such as the Arctic and deep-water reservoirs.

Martin Fernøمشاهده پروفایل

استاد

• Reservoir Physics
• Multiphase Flow in Porous Media
• CO2 Storage
• +۵ مورد دیگر

Professor Martin Fernø is affiliated with the Department of Physics and Technology at the University of Bergen. His research focuses on reservoir physics, multiphase flow in porous media, CO2 and hydrogen storage, and enhanced oil recovery. He leads the Reservoir Physics – Energy Technology and CO2 Storage (CCUS) research group. Research interests include capillary heterogeneities, wettability effects, in-situ imaging via MRI/NMR/CT, and SCAL techniques. He has contributed to projects like HyPE (Hydrogen Storage in Subsurface Porous Media) and FluidFlower, a meter-scale CO2 storage laboratory. His work integrates experimental and computational methods to address energy transition challenges. Recent publications explore microbial interactions in hydrogen storage, CO2 mobility control via foam, and pore-scale dynamics. He advises PhD candidates and mentors master’s students in reservoir physics and energy technology. Key collaborations involve NORCE, Equinor, and the Research Council of Norway. Labs/Teams: FluidFlower Lab, Reservoir Physics Research Group Funding: HyPE (Research Council of Norway), CSSR (Center for Sustainable Subsurface Resources)

Guttorm Alendalمشاهده پروفایل

استاد

• Environmental Monitoring
• CO2 Storage
• Oceanography
• +۵ مورد دیگر

Guttorm Alendal is a Professor in the Department of Mathematics at the University of Bergen. His research focuses on mathematical modeling applied to environmental challenges, particularly CO2 storage monitoring, oceanography, and climate science. He leads projects like ACTOM (Advanced Monitoring for Offshore CO2 Storage) and MATH4SDG, emphasizing cross-disciplinary approaches to sustainability. Education: Ph.D. in Applied Mathematics (1996, University of Bergen, thesis: Implementing and testing of different gravity current models). Key Research Areas: Fluid dynamics, environmental monitoring systems, carbon sequestration risk assessment, and marine pollution modeling. Collaborates with NORCE Norwegian Research Centre and international initiatives like STEMM-CCS. Publications: Over 80 peer-reviewed articles on topics like CO2 seep detection, Bayesian environmental modeling, and particle transport in oceanic waters. Recent work includes data-driven dynamical systems for disease modeling and reinforcement learning for environmental surveillance. Awards: While no specific awards listed, his work has been funded by EC H2020, Research Council of Norway, and JPI-Oceans. Grants: Active projects include ACTOM (2019-2022), MATH4SDG (2021-2026), and SFI CRIMAC (2020-2028). Former roles include leading ECO2 (FP7) and co-authoring technical reports on CO2 plume dynamics. Labs/Teams: Involved in Digital Life Norway's dCOD project (systems toxicology of Atlantic cod) and the Bergen Ocean Model development team.

• 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.

Irina Markinaمشاهده پروفایل

استاد

• Sub-Riemannian Geometry
• Sub-Lorentzian Geometry
• Partial Differential Equations (PDE)
• +۵ مورد دیگر

Irina Markina is a Professor at the Department of Mathematics, University of Bergen. Her research focuses on Sub-Riemannian and Sub-Lorentzian geometry, Partial Differential Equations (PDEs), and geometric analysis. She has contributed to studies on geometric control theory, Lie groups, and their applications in physics and mathematical physics. Her work spans theoretical frameworks like the analysis of measure-preserving diffeomorphism groups, Stokes graphs in the Rabi problem, and harmonic maps into sub-Riemannian Lie groups. She has led the NordForsk Research Network 'Analysis and Applications', promoting Nordic collaboration in analysis. Key research areas include ultra-hyperbolic operators on pseudo H-type groups, classification of pseudo H-type algebras, and geometric problems on Stiefel/Grassmann manifolds. Her grants include funding from NordForsk, Norwegian Research Council, and Chilean agencies. She has supervised doctoral theses, including those by Anastasia Frolova and Mauricio Godoy Molina.

Jakub Wiktor Bothمشاهده پروفایل

پژوهشگر

• Porous Media
• Numerical Methods
• Image Analysis
• +۵ مورد دیگر

Jakub Wiktor Both is a permanent researcher at the Department of Mathematics, University of Bergen (UiB). He is affiliated with the Porous Media Research Group and the Center for Modeling of Coupled Subsurface Dynamics. His research focuses on numerical methods for multiphysics problems in porous media, including image-based data analysis for laboratory experiments and mathematical modeling of CO2 storage. His work involves developing tools like the DarSIA (Darcy Scale Image Analysis) toolbox for fluid displacement analysis and PorePy, a Python simulation framework for fractured porous media. He leads projects on CO2 storage validation and has been awarded an NFR FRIPRO grant for his TIME4CO2 initiative, aiming to enhance CO2 storage capacity through mathematical modeling. Key research themes include optimal transport metrics, robust numerical solvers for coupled systems, and gradient flow structures in dissipative systems. His contributions span experimental validation frameworks (e.g., FluidFlower), digital twins (PoroTwin), and open-source software for subsurface dynamics. Notable awards include election as Chair of the Board of InterPore Norway (2024) and leadership in international projects like ERC CoG MaPSI and NFR Petrosenter CSSR. His interdisciplinary approach bridges mathematics, geoscience, and engineering for sustainable subsurface resource management.

• Environmental Engineering
• Biotechnology
• Mathematics
• +۳ مورد دیگر

Benedek Plosz is a Professor at Oslo Metropolitan University, affiliated with the Faculty of Technology, Art and Design and the Department of Built Environment . His research focuses on environmental engineering, biotechnology, and computational modeling, particularly in water systems and wastewater treatment. His work includes advancements in digital twin applications for water resource recovery, N2O emission modeling , and antimicrobial resistance in biological wastewater systems. Recent publications highlight collaborations with researchers like Vince Bakos and Yuge Qiu, with studies appearing in Water Research and Chemical Engineering Journal . The Smart Water Engineering Group (SWING) drives his research, integrating machine learning and CFD modeling to optimize settling tanks and aeration systems. He has presented at international conferences such as IWA WRRmod and WATERMATEX, addressing topics like biofilm dynamics and gas transfer mechanisms. Benedek Plosz can be reached at benedek.plosz@oslomet.no . No scientific awards are listed in the provided data.

Ahmed Khalid Kadhim Kadhimمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Machine Learning
• Hyperdimensional Computing
• +۳ مورد دیگر

Ahmed Khalid Kadhim Kadhim serves as a PhD Research Fellow at the Department of Information and Communication Technology, University of Agder (UiA), Norway. Based in office A2121 at Jon Lilletuns vei 9, 4879 Grimstad, he maintains active research contributions while pursuing doctoral studies under UiA's structured PhD program. His research centers on cutting-edge artificial intelligence methodologies, specifically investigating hyperdimensional computing applications within Tsetlin Machines. This work bridges theoretical computer science and practical machine learning, focusing on developing resource-efficient, interpretable AI systems through novel vector representations and Boolean logic frameworks. His approach emphasizes computational efficiency while maintaining model transparency—a critical advantage over traditional neural networks in constrained environments. Funded through UiA's competitive PhD Research Fellow position, his work contributes to the university's strategic research priorities in computational intelligence. Current projects explore how hyperdimensional vectors can optimize Tsetlin Machine performance in pattern recognition tasks, with potential applications in edge computing and IoT systems where processing power is limited.

Eivind Brodalمشاهده پروفایل

دانشیار

• Heat pumps
• Process modeling and optimization
• Energy efficiency
• +۳ مورد دیگر

Eivind Brodal is an Associate Professor at UiT The Arctic University of Norway, affiliated with the Department of Automation and Process Technology. His research focuses on heat pumps, process modeling and optimization, energy efficiency, and carbon capture technologies. Teaches Technical Thermodynamics and Heat Pumping Processes Supervises master's and PhD engineering students His work addresses energy challenges in cold climates, including CO2 liquefaction, LNG cascade processes, and hydrogen pre-cooling optimization. He contributes to advancing refrigeration technologies and sustainable energy systems through computational modeling and industrial applications. Brodal collaborates on energy efficiency projects and co-develops mathematical models for thermal systems. His recent publications emphasize heat exchanger optimization, pinch point analysis, and ambient temperature impacts on process performance. He is a member of the IR, Spectroscopy, and Numerical Modelling Research Group, operating from room 4.024 in Teknologibygget Tromsø.

Dongping Songمشاهده پروفایل

استاد

• Operations Management
• Supply Chain Management
• Maritime Transport
• +۷ مورد دیگر

Prof. Dongping Song is a Professor of Supply Chain Management at the University of Liverpool's Management School. His academic journey includes studies and affiliations with Nankai University, Zhejiang University, Newcastle University, Imperial College London, and Plymouth University. Education and academic background Senior Member of IEEE Associate Editor roles Grants from EPSRC, ESRC, Royal Society, British Council, and European Commission His research focuses on integrating data analytics , mathematical modeling , and machine learning to enhance supply chain , maritime logistics , and transportation systems . Recent work emphasizes container shipping optimization , disruption management , and maritime decarbonization . Recent publications span topics such as port operations , automated terminal strategies , and emission reduction in logistics , applying simulation-based tools and stochastic dynamic programming . He has secured funding from key UK and European research councils, contributing to maritime transport advancements. Collaborations include researchers from institutions like Liverpool John Moores University, Durham University, and others.

• Civil Engineering
• Structural Engineering
• Machine Learning Applications in Construction
• +۴ مورد دیگر

Afaq Ahmad is a Postdoctoral Fellow at Oslo Metropolitan University , affiliated with the Faculty of Technology, Art and Design and the Department of Built Environment. His research focuses on the intersection of civil engineering, structural analysis, and machine learning applications. Institution: Oslo Metropolitan University Department: Built Environment Afaq's work examines hybrid concrete technologies, fiber-reinforced composites, and structural health monitoring using advanced computational methods. He specializes in applying image processing and neural networks to evaluate concrete properties and defects. His recent publications highlight innovations in engineered cementitious composites for masonry, symbolic matrix structural analysis for beams, and machine learning-driven assessments of concrete columns and wooden structures. Key trends include non-destructive testing and predictive modeling for infrastructure resilience. Research activities span from 2022-2025 , with 15 representative articles demonstrating expertise in: Concrete material science and failure analysis Machine learning integration in structural engineering Seismic performance evaluation Hybrid composite reinforcement systems His work frequently combines computer vision techniques with civil engineering challenges, particularly in defect detection and load capacity prediction.

Morten Ottestadمشاهده پروفایل

مدرس ارشد

• Robotics
• Biomechatronics
• Artificial Intelligence
• +۴ مورد دیگر

Morten Ottestad serves as a Senior Lecturer in the Department of Engineering Sciences at the University of Agder, Norway. His research spans multiple interdisciplinary domains within engineering, with particular focus on robotics, biomechatronics, and control systems. He maintains an active research profile with publications spanning from 2009 to 2024, demonstrating sustained scholarly contribution to his fields. Dr. Ottestad's research interests center on Biomechatronics and Collaborative Robotics , with significant contributions to prosthetics and orthotics technology. His work integrates Artificial Intelligence with practical engineering applications, particularly in medical device development. Recent publications demonstrate expertise in open-source hardware design for medical applications and virtual reality rehabilitation systems. He has also made substantial contributions to hydraulic systems research, particularly in oil/water separation technology for petroleum applications, and has published extensively on multicopter/UAV design and control systems. His publication trends reveal a strategic evolution from traditional engineering domains like hydraulic systems and petroleum engineering toward more contemporary areas including biomechatronics, prosthetics, and educational applications of robotics. This trajectory demonstrates both technical versatility and responsiveness to emerging technological needs in healthcare and education sectors. Dr. Ottestad actively contributes to engineering education through innovative teaching frameworks, particularly in mechatronics education. His research groups include Artificial Intelligence, Biomechatronics and Collaborative Robotics and Robotics and automation , indicating leadership in these specialized laboratory environments where theoretical concepts are translated into practical applications.