Research
Research
I develop mathematical and computational methods for learning from complex temporal and longitudinal data. My research combines the development of new methodology with applications to high-dimensional, multivariate and irregular real-world data.
My work is organised around three connected research themes.
Research themes
Mathematical methods for learning systems
I study reservoir computing through free probability and dynamical systems, using mathematical structure to understand learning behaviour and develop computationally efficient methods for model and hyperparameter selection. More broadly, I am interested in learning methods that are statistically and mathematically grounded and applicable beyond a single domain.
Learning representations of temporal data
I develop and evaluate methods for time-series and longitudinal modelling, including representation learning, generative models and foundation models. A particular focus is learning from irregular, heterogeneous and sparsely observed temporal data.
Learning from complex multivariate systems
I develop graph-based learning and anomaly-detection methods for high-dimensional multivariate systems. This work considers complex dependencies across sensors, network elements and temporal signals, with an emphasis on methods that remain effective and computationally tractable at real-world scale.
Projects and research networks
- ML4ITS — Machine Learning for Irregular Time Series (IKTPLUSS, Research Council of Norway, grant no. 312062)
Telenor lead in a collaborative project developing machine-learning methods for irregular and heterogeneous temporal data.
Project website - NorwAI — Norwegian Research Center for AI Innovation (SFI, Research Council of Norway, grant no. 309834)
Telenor representative in the Hybrid AI and Data work package.
Project website - SURE-AI — More sustainable, risk-averse and ethical AI technologies (Norwegian AI centre, Research Council of Norway, project no. 357482)
Telenor industry partner representative in research on sustainable, reliable and ethical AI.
Project website