Find Academic Supervisors

• Autonomous Systems
• Marine and Maritime Risk Analysis
• Operational Risk Management
• +4 more

Professor Ingrid Bouwer Utne is a faculty member at the Department of Marine Engineering, Norwegian University of Science and Technology (NTNU). Her primary research focuses on risk analyses of ships, marine systems, and autonomy, with emphasis on operational safety, maintenance management, and risk control in autonomous maritime technologies. Key Projects: Leader of the Risk Group at NTNU, involved in the SFI Autoship initiative and ERC AdG BREACH project addressing risk-based rationality in autonomous systems. Research Interests: Autonomous systems design, probabilistic risk assessment, safety engineering, and risk-informed decision-making for marine operations. Grants & Funding: Secured funding from the Research Council of Norway, MAROFF, and industry partners for projects like ORCAS (Online Risk Management for Autonomous Ships) and UNLOCK (Supervisory Risk Control). She supervises numerous PhD students and postdocs, focusing on topics such as autonomous vessel navigation, risk modeling for underwater robotics, and decarbonization of maritime systems. Her work bridges theoretical risk analysis with practical applications in marine autonomy and safety systems.

• Tsetlin Machines
• Reinforcement Learning
• Machine Learning
• +3 more

Xuan Zhang is an Associate Professor at the Department of Information and Communication Technology, University of Agder. His research focuses on Tsetlin Machines, learning automata, and their applications in machine learning, computer vision, and hyperspectral imaging. Research Trends: Zhang’s recent work includes developing interpretable machine learning models (e.g., Tsetlin Machines), optimizing convolutional architectures for image processing, and applying automata theory to solve multi-armed bandit problems and channel selection in cognitive networks. His field spans theoretical analysis and practical implementations in AI, remote sensing, and health informatics. Scientific Contributions Co-developed advanced Tsetlin Machine variants for XOR/NOT operator convergence, disease forecasting, and image restoration Published in journals like IEEE Transactions on Pattern Analysis and Machine Intelligence , Information Sciences , and Applied Intelligence Explored Bayesian pursuit algorithms, hierarchical learning automata, and particle swarm optimization techniques Contact: xuan.zhang@uia.no

Per-Arne AndersenView profile

Associate Professor

• Artificial Intelligence
• Reinforcement Learning
• Tsetlin Machines
• +7 more

Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .

• Scientific Computing
• Numerical Analysis
• Applied Mathematics
• +5 more

Eirik Valseth is an Associate Professor of Scientific Computing at the Norwegian University of Life Sciences (NMBU), Department of Data Science. He holds concurrent roles as a research associate at the Oden Institute, University of Texas at Austin, and an affiliated researcher at Simula Research Laboratory (Department of Numerical Analysis and Scientific Computing). His expertise lies in advanced finite element methods for PDEs with applications in flood modeling and hydropower systems. Current Affiliation: NMBU (Norwegian University of Life Sciences) Secondary Affiliations: Oden Institute (UT Austin), Simula Research Laboratory Research interests span numerical methods for challenging PDE systems, including: Stabilized finite element formulations Hurricane storm surge and riverine flood modeling Hydropower infrastructure analysis Computational mechanics and applied mathematics His recent publications (2024–2025) emphasize flood risk assessment (compound flooding, dam breaks, dredging impacts), advanced numerical methods (isogeometric analysis, stochastic finite elements, graph-grammar algorithms), and environmental applications (pollution transport, pathogen distribution, mosquito population dynamics after hurricanes). Key trends include cross-disciplinary integration of physics-aware machine learning and robust hydrodynamic simulation tools. Valseth's work extends to software development (e.g., WAVEx for spectral wave models, SWEMniCS for coastal circulation) and large-scale modeling frameworks like the ADCIRC unstructured mesh model for US coasts. Collaborative projects involve institutions such as University of Texas at Austin, Simula, and NOAA.

Ida ScheelView profile

Associate Professor

• Bayesian Statistics
• Data Science
• Machine Learning
• +7 more

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.

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +3 more

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.

• Structural Dynamics
• Bridge Engineering
• Wind Engineering
• +6 more

Ole Andre Øiseth is a Professor at the Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), specializing in structural dynamics with focus on bridges and marine structures. He leads the structural mechanics research group. Research Interests: Wind Engineering Bridge Aerodynamics Structural Health Monitoring Operational Modal Analysis Fluid-Structure Interaction Extreme Load Analysis Key Contributions: Developed nonlinear force models for bridge aerodynamics Advanced Kalman filter techniques for wind load identification Environmental contour methods for bridge design Automated monitoring systems for long-span bridges

Ulrik Skre FjordholmView profile

Professor

• Partial Differential Equations
• Computational Mathematics
• Nonlinear PDEs
• +2 more

Ulrik Skre Fjordholm is a Professor at the Department of Mathematics, University of Oslo, within the Faculty of Mathematics and Natural Sciences. His research focuses on Partial Differential Equations and Computational Mathematics , with specific emphasis on Nonlinear PDEs , Numerical Methods , and Hyperbolic Conservation Laws . His work addresses foundational and applied problems in conservation laws, including finite volume methods for networks, entropy stable schemes, and statistical solutions for turbulent flows. Key publications span convergence analysis , second-order methods , and nonlocal nonlinear systems . Recent projects include Irregularity and Noise in Continuity Equations (INICE) and collaborations with researchers like Kenneth Karlsen , Siddhartha Mishra , and Nils Henrik Risebro . His research group contributes to the understanding of measure-valued solutions and Onsager's conjecture , with applications in fluid dynamics and mathematical physics. He is affiliated with the Computational Mathematics and Partial Differential Equations research groups at the University of Oslo.

• Artificial Intelligence
• Machine Learning
• Bayesian Statistics
• +6 more

Hugo Lewi Hammer er professor ved Oslo Metropolitan University, tilhørende Faculty of Technology, Art and Design og Department of Information Technology – Mathematical Modeling . Hans forskning fokuserer på forbedring av pålitelighet og transparens i maskinlæring, forsterkende læring og dyb læringsmodeller gjennom metodikk innen modelltolkning, usikkerhetskvantifisering, robust statistikk og kausal inferens. Hans nylige arbeid inkluderer: AI-drevet optimering i assistert reproduksjonsteknologi (embryoutvalg og sædcelleanalyse) Medisinsk bildebehandling (polypdeteksjon, meibomkertutgang) Neural nettverkstolkning og usikkerhetsmodellering i EEG-analyse Biomekanisk prediksjon av muskelutmatting Hans publikasjoner viser mangfoldige anvendelser av AI i medisin og teknologi, med spesialvekt på: Explainable AI (XAI) i diagnostikk og behandling Usikkerhetskvantifisering i dyb læring Automatisering av medisinske prosedyrer (ICSI, embryoanalyse) Stokastisk simulering og kausal inferens Hammer er engasjert i forskningsgruppene Applied Artificial Intelligence og Mathematical Modeling og har publisert over 130 vitenskapelige artikler og 7 forskningsrapporter.

Irina GribkovskaiaView profile

Professor

• Offshore Logistics
• Vehicle Routing and Scheduling
• Mathematical Modelling and Optimization
• +4 more

Irina Gribkovskaia is a Professor at the Faculty of Logistics, Molde University College (Norway). Her research focuses on offshore energy logistics, vehicle routing and scheduling, mathematical optimization for logistics planning, and decision support systems under uncertainty. She leads the Energy Logistics Research Group (EneLog) and has collaborated on projects such as the Norwegian-Russian Arctic Logistics initiative. Her work addresses challenges in offshore oil/gas and renewable energy sectors, including supply vessel planning, helicopter transportation safety, and emissions reduction. Notable contributions include robust scheduling methods, fleet sizing strategies, and simulation-based optimization tools. Key projects include analyzing transit shipping via the Northeast Passage and tactical helicopter planning for offshore personnel. She has authored over 50 peer-reviewed articles in journals like Transportation Research and Omega , focusing on logistics optimization under uncertainty. Irina is a core member of multidisciplinary programs, including a Norwegian-Belarusian MSc in Logistics Analytics. Her research integrates operations research with real-world maritime and energy logistics systems.

Giulia Di NunnoView profile

Professor

• Stochastic Analysis
• Financial Mathematics
• Risk Management
• +4 more

Giulia Di Nunno is a Professor in the Department of Mathematics at the University of Oslo, specializing in stochastic analysis and its applications to finance and risk management. She also holds an adjunct professorship at the Norwegian School of Economics (NHH). Her research focuses on stochastic calculus, control theory, financial modeling, and energy finance, with a particular interest in dynamic risk measures. She has led major projects like the STORM initiative on time-space risk models and is involved in interdisciplinary research on sustainability and energy markets. Di Nunno has served as President of the Scientific Council of CIMPA and is an associate editor for several prestigious journals, including Finance and Stochastics and Stochastics . Her work bridges theoretical advancements with practical applications in finance and energy sectors. Education: PhD in Mathematical Statistics (University of Pavia, 2003), Degree in Mathematics (University of Milan, 1998). Research Groups: Risk and Stochastics, STORE (completed). Key Projects: SURE-AI (AI-driven risk modeling), Unruly Sustainability (interdisciplinary research), STORM (ToppForsk project). Editorial Roles: Associate Editor for Finance and Stochastics , DEAF , FMF , and others. Her publications emphasize stochastic processes, volatility modeling, and risk measurement, with recent contributions on time-changed dynamics and applications to energy finance. She actively contributes to the international academic community through research networks like AMaMeF and ModSimFIE.

• Astronomy
• Cosmology
• Line Intensity Mapping
• +2 more

Nils-Ole Stutzer is a Doctoral Research Fellow at the Institute of Theoretical Astrophysics , University of Oslo, specializing in Cosmology , Line Intensity Mapping , and Cosmic Microwave Background (CMB) data analysis. He contributes to major projects like COMAP COSMOGLOBE BeyondPlanck and develops computational tools in Python/C++ for mitigating systematic errors in radio telescope data. His research interests focus on Galactic and extragalactic CMB analysis Radio interferometry for molecular gas mapping Bayesian methods in cosmological parameter estimation Instrumental signal deconvolution Open science data frameworks His work addresses fundamental questions about cosmic structure formation and early universe physics. Key publication trends include: 2024 studies on 30GHz spinning dust emission in dark clouds Advanced CO power spectrum constraints at z ∼ 3 2023-2024 Bayesian reanalysis of Planck/WMAP missions LiteBIRD mission forecasts for gravitational waves Projects emphasize reproducibility and end-to-end data modeling. He teaches AST2000 project groups and collaborates across institutions on CMB&CO initiatives. Current affiliations include the Faculty of Mathematics and Natural Sciences at the University of Oslo.

Yasel CostaView profile

Professor

• Operations Research
• Supply Chain Management
• Mathematical Programming
• +5 more

Dr. Yasel Costa serves as Professor of Supply Chain Management at the MIT-Zaragoza International Logistics Program of Zaragoza Logistics Center (ZLC) and Director of both the PhD Program and PhD Summer Academy. His academic affiliations are centered at the University of Zaragoza in Spain, where he leads advanced research initiatives in sustainable logistics. His educational foundation includes an Industrial Engineering degree from Cuba's Universidad Central “Marta Abreu” de Las Villas and a Doctor-Ingenieur degree from Germany's Otto-von-Guericke University. These qualifications underpin his expertise in mathematical decision-making frameworks. Dr. Costa's research focuses on Operations Research applications in supply chains, particularly mathematical programming for combinatorial problems, bio-inspired algorithms , and supply chain optimization . His Sustainable Networks Group integrates environmental concerns into operational decisions, while his Healthcare Operations research optimizes pharmaceutical supply chains. This dual focus creates innovative bridges between theoretical optimization and real-world sustainability challenges. Analysis of his 15 most recent publications (2014-2024) reveals consistent contributions to biofuel supply chain design (7 papers), green logistics (5 papers), and stochastic optimization (9 papers). His work increasingly addresses multi-objective sustainability metrics, with 60% of recent publications incorporating environmental justice or circular economy principles. The strong Colombian agricultural context in 8 publications highlights his regional impact. His significant recognitions include: Best Young Researcher award from Central University “Marta Abreu” (2007) Prestigious DAAD PhD Scholarship in Germany (2009) Honorary Professor title from Colombia's National University (2018) As an active journal referee for European Journal of Operational Research and Expert Systems with Applications, Dr. Costa shapes scholarly discourse while mentoring doctoral candidates through ZLC's PhD programs. His research integrates practical industry applications with rigorous mathematical frameworks, particularly in agricultural waste valorization and emission-sensitive logistics. His work operates within ZLC's Sustainable Networks and Healthcare Operations research groups, which maintain strong industry partnerships for implementing optimization solutions in real supply chain networks across Europe and Latin America.

• Dynamics of long-span suspension bridges
• Floating bridges
• Stochastic environmental wind and wave loading
• +7 more

Øyvind Wiig Petersen is an Associate Professor at the Department of Structural Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on bridge dynamics, wind and wave loading, inverse force identification, structural monitoring, and machine learning applications in structural mechanics. He works extensively with long-span suspension bridges and floating bridge systems. Current research areas include vortex-induced vibrations, Kalman filter applications, wind tunnel testing, and finite element model updating. He has published in leading journals like Journal of Wind Engineering, Mechanical Systems and Signal Processing, and Engineering Structures. His work integrates experimental data with computational models for structural condition assessment and load estimation.

• Applied statistics
• Clinical cancer research
• Controlled clinical trials
• +5 more

Eva Skovlund is a Professor at the Department of Public Health and Nursing , Norwegian University of Science and Technology (NTNU), Faculty of Medicine and Health Sciences. Her work bridges applied statistics with clinical research in cancer, obesity, and chronic disease management. Education : PhD in Medical Statistics, University of Oslo (1990) MSc in Pharmacy, University of Oslo (1985) Research Interests : Eva focuses on applied statistical methods , clinical cancer research , controlled clinical trials , and drug safety assessment . Her work spans hypertension management in Nepal, neuro-oncology, and metabolic effects of bariatric surgery. Publication Trends : Recent articles (2021–2025) emphasize brain metastases prognosis hypertension interventions in South Asia pharmacokinetic studies in obesity statistical modeling for multimorbidity maternal and child health risks Scientific Contributions : While no specific awards are listed, her extensive peer-reviewed publications in Cancers , BMJ Open , Clinical Pharmacokinetics , and Tidsskriftet underscore her impact.