1 Jan 2014–31 Dec 2018 and 1 Jan 2019–31 Dec 2023
University of Helsinki
Matti Lassas’ research plan moves from linear models to non-linear, more practical applications. His goal is to develop geometric methods for machine learning. The applications in the area of medical imaging concern identification of different types of stroke and rapid selection of suitable treatments. In exploration geophysics, the methods allow for a new way to improve seismic imaging. The research may also be applied in the mapping of oil and groundwater deposits. Modern geometry is utilised in imaging different kinds of waves, which will also help in analysing gravitational waves.
Lassas also served as Academy Professor in 2014–2018. He has made important, breakthrough contributions in the areas of invisibility cloaking and electromagnetic wormholes. During his first term as Academy Professor, Lassas continued his theoretical analysis of invisibility cloaking and studied linear hyperbolic equations.
Lassas heads the Centre of Excellence of Inverse Modelling and Imaging.