As a researcher, I develop machine learning methods for biogenetics. The objective of my current project is to identify new treatment targets (proteins) in neuropsychiatric disorders using causal machine learning.

My main PhD project focused on clustering time-series data in the context of ensemble weather prediction. From there, I became increasingly interested in broader clustering-related research questions, notably accounting for uncertainty in the number of clusters, evaluating clustering with cluster validity indices, and studying the impact of different distance metrics and averaging methods when working with time-series data.

Before my PhD, I worked at the Nansen Center in Bergen, Norway, as a research assistant. There, I conducted research on machine learning applied to oceanography, using Self-Organising Maps and Hidden Markov Models to infer subsurface data from surface observations.

I have notably been a teaching assistant in machine learning courses (Introduction to Machine Learning INF265 and Deep Learning INF265) and a lecturer in introductory programming and Python courses (DIGI111 and DIGI611).