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Samuel Kaski is Professor of Computer Science and the Director of Helsinki Institute for Information Technology HIIT. He also directs the Finnish Centre of Excellence in Computational Inference Research COIN.

Samuel Kaski develops computational methods for interactive multi-source data analysis and machine learning. They will be applied first to personalised medicine, but they will also be applicable to the ever widely available collections of datasets in science and data-based services. Current data analysis methods are ill prepared for the challenges underlying personalised medicine. Responses to treatments need to be predicted based on very small samples, even from only one, with avery large number of variables. Kaski is a pioneer in many areas of machine learning technology and applications, and he has contributed to several significant scientific breakthroughs in this multidisciplinary field

The aim of the Academy of Finland’s funding for research posts as Academy Professor is to facilitate full-time scientific research for internationally leading-edge researchers. Academy Professors are expected to greatly contribute to the progress of research in their fields and develop a creative research environment. At present, the Academy funds 44 five-year Academy Professorships in a number of disciplines. Two of the Academy Professorships are targeted posts, open for application every five years: the Minna Canth Academy Professorship and the Martti Ahtisaari Academy Professorship.