Kajsa Møllersen

Kajsa Møllersen is a statistician with a postdoc position at UiT-Arctic University Norway. Her current research is focused on exploratory statistical methods applied on gene expression/methylation data. In particular, she works on clustering methods, multiple instance learning and divergence measures. Exploratory statistical methods aim at extracting information, recognising patterns and generating hypotheses when previous knowledge about the data is lacking. The goal of her project is to develop new statistical methods for exploratory analysis of this kind of data. Her research interests include: Applied statistics; Image analysis; Clustering; Divergence functions; Feature selection; Machine learning; Multiple instance learning; Melanoma; Breast cancer; Gene expression. She is a Board member of NOBIM (Norwegian Society for Image Analysis and Pattern Recognition).

Kajsa Møllersen contributes with the lecture The Aesthetics of the Statistics during the High Tides weekend programme Maths, matter & body on September 14 (in Norwegian).