Lassi Roininen is an associate professor (tenure track) in applied mathematics in the School of Engineering Science in Lappeenranta University of Technology. He is also an adjunct professor in applied mathematics in University of Oulu, Finland. He works on a broad spectrum from the fundamental mathematical inverse problems theory to applications in near-space remote sensing and subsurface imaging. He collaborates with high-level international research groups both in academia and industry. His research highlight is the development of the methodology of discretisation-invariant and computationally feasible priors for Bayesian inversion of function-valued unknowns. Applications include e.g. tomography (ionospheric, electrical impedance, X-ray) and radar pulse-compression coding and analysis methods.