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Universitetet i Bergen
Anna Oleyniks bilde

Anna Oleynik

Forsker
Matematisk institutt
  • E-postanna.oleynik@uib.no
  • Besøksadresse
    Allégaten 41
    Realfagbygget
    5007 Bergen
  • Postadresse
    Postboks 7803
    5020 Bergen

Anna Oleynik's main research interests are mathematical modelling, dynamical systems, optimization, and marine monitoring. She has a long experience in mathematical analysis of neural field models, and a more recent interest in inverse problems, optimization methods, numerical analysis and simulations.  Anna Oleynik is a part of the Academia agreement project: AMOFF, Assurance Monitoring for Offshore CO2 storage sites; a member of the ACTOM project team on developing a web-based toolkit that will collect algorithms for optimal monitoring design for offshore CCS; and a collaborator of the FACTS project on predicting microplastic distribution and localizing plastic aggregation zones, based on numerical models and simulations and of the CRIMAC project on developing machine learning methods for target classification in fisheries acoustics.

Vitenskapelig artikkel
  • Vis forfatter(e) (2022). Assuring the integrity of offshore carbon dioxide storage. Renewable & Sustainable Energy Reviews. 9 sider.
  • Vis forfatter(e) (2021). Towards improved monitoring of offshore carbon storage: A real-world field experiment detecting a controlled sub-seafloor CO2 release. International Journal of Greenhouse Gas Control.
  • Vis forfatter(e) (2021). Semi-conditional variational auto-encoder for flow reconstruction and uncertainty quantification from limited observations. Physics of Fluids. 23 sider.
  • Vis forfatter(e) (2021). Pattern formation in a 2-population homogenized neuronal network model . The Journal of Mathematical Neuroscience. 38 sider.
  • Vis forfatter(e) (2021). Efficient marine environmental characterisation to support monitoring of geological CO2 storage. International Journal of Greenhouse Gas Control. 16 sider.
  • Vis forfatter(e) (2021). Detection and quantification of CO2 seepage in seawater using the stoichiometric Cseep method: Results from a recent subsea CO2 release experiment in the North Sea. International Journal of Greenhouse Gas Control.
  • Vis forfatter(e) (2020). Optimal sensors placement for detecting CO2 discharges from unknown locations on the seafloor. International Journal of Greenhouse Gas Control.
  • Vis forfatter(e) (2020). Binary time series classification with Bayesian convolutional neural networks when monitoring for marine gas discharges . Algorithms. 24 sider.
  • Vis forfatter(e) (2018). Single bumps in a 2-population homogenized neuronal network model. Physica D : Non-linear phenomena. 40-53.
  • Vis forfatter(e) (2018). Localized stationary solutions of a 2-population homogenized neural field model. AIP Conference Proceedings.
  • Vis forfatter(e) (2017). Greedy Gauss-Newton algorithms for finding sparse solutions to nonlinear underdetermined systems of equations. Optimization. 1201-1217.
  • Vis forfatter(e) (2016). Spatially localized solutions of the Hammerstein equation with sigmoid type of nonlinearity. Journal of Differential Equations. 5844-5874.
  • Vis forfatter(e) (2015). Iterative Schemes for Bump Solutions in a Neural Field Model. Differential Equations and Dynamical Systems. 79-98.
  • Vis forfatter(e) (2013). On the properties of nonlinear nonlocal operators arising in neural field models. Journal of Mathematical Analysis and Applications. 335-351.
  • Vis forfatter(e) (2013). Iterative schemes for bump solution in a neural field model. Differential Equations and Dynamical Systems.
  • Vis forfatter(e) (2011). Stability of bumps in a two-population neural-field model with quasi-power temporal kernels. Nonlinear Analysis: Real world applications. 3073-3094.
  • Vis forfatter(e) (2010). The weakly nonlocal limit of a one-population Wilson-Cowan model. Physica D : Non-linear phenomena. 1766-1780.
Rapport
  • Vis forfatter(e) (2019). Underpinning data for monitoring activities (including current statistics and carbon tracer quantifications). .
Vitenskapelig foredrag
  • Vis forfatter(e) (2022). Modelling the fate of sinking microplastics in an urban fjord in western Norway .
  • Vis forfatter(e) (2022). ACT on Marine Monitoring, project presentation.
  • Vis forfatter(e) (2020). Monitoring offshore CO2 storage projects, aligning capabilities with regulations and public expectations. .
  • Vis forfatter(e) (2019). Utility of the Cseep method in the vicinity of Goldeneye. .
  • Vis forfatter(e) (2019). Combining models and measurements for identifying aggregation zones in marine waters.
  • Vis forfatter(e) (2019). Bayesian convolutional neural networks as a tool to detect discharges of pollutants to marine waters through time series classification.
  • Vis forfatter(e) (2018). The need for proper environmental statistics to design adequate monitoring for offshore geological storage of CO2 projects.
  • Vis forfatter(e) (2018). PATTERN FORMATION IN A HOMOGENIZED NEURAL FIELD MODEL.
  • Vis forfatter(e) (2018). Machine Learning in CO2 leak detection.
  • Vis forfatter(e) (2018). LOCALIZED STATIONARY SOLUTIONS AND PATTERN FORMATION IN A HOMOGENIZED NEURAL FIELD MODEL.
  • Vis forfatter(e) (2018). Ensuring efficient and robust offshore storage – the role of marine system modelling.
  • Vis forfatter(e) (2018). Combining Models and Machine Learning Techniques to Design Leak Detection Monitoring .
  • Vis forfatter(e) (2018). Combining Environmental Statistics and Marine Process Modelling to Design Monitoring Programs for Offshore CO2 Storage.
  • Vis forfatter(e) (2017). Research visit.
  • Vis forfatter(e) (2017). Localized stationary solutions of a 2-population homogenized neural field model.
  • Vis forfatter(e) (2017). Localized stationary solutions of a 2-population homogenized neural Field model.
  • Vis forfatter(e) (2010). Weakly nonlocal limit of a one population neuronal field model.
  • Vis forfatter(e) (2010). The Weakly Nonlocal Limit of a One-Population Wilson-Cowan Model.
Mastergradsoppgave
  • Vis forfatter(e) (2020). GRADIENT METHODS FOR SOURCE IDENTIFICATION PROBLEMS.
  • Vis forfatter(e) (2019). Dynamic Mode Decomposition and Koopman Operator (Data-Driven Modeling of Complex Dynamical Systems).
Annet
  • Vis forfatter(e) (2010). Stability of Bumps in a Two Population Neural Field Model. 407-410.
Sammendrag/abstract
  • Vis forfatter(e) (2009). The weakly nonlocal limit of a one-population Wilson - Cowan model. AIP Conference Proceedings. 3.
Poster
  • Vis forfatter(e) (2023). Deep Learning for Acoustic Target Classification: Addressing Class-Imbalance with a Similarity-Based Sampling Approach.
  • Vis forfatter(e) (2020). Reconstruction of Currents Based on Sparse Observations with Deep Learning.
  • Vis forfatter(e) (2019). Ensuring efficient and robust carbon storage: marine modelling for environmental monitoring.
  • Vis forfatter(e) (2018). Stationary periodic solutions in the Amari model.
  • Vis forfatter(e) (2018). Model Reduction for Tracer Transport and Applications.
  • Vis forfatter(e) (2018). Mathematical methods for detection and localization of CO2 leaks.
Fagartikkel
  • Vis forfatter(e) (2022). Demonstration of a Semi-Automated Decision Support Toolbox to Aid Operators in the Design of Efficient Environmental Offshore Monitoring Programs for Co2 Storage Sites. Social Science Research Network (SSRN).
  • Vis forfatter(e) (2020). Semi Conditional Variational Auto-Encoder for Flow Reconstruction and Uncertainty Quantification from Limited Observations. arXiv.

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