Research areas

Research areas

The inverse problems research at the Department of Applied Physics has strong ties with the Finnish Center of Excellence in Inverse Problems. The associated research consortium has been the leading group, among other topics, in the modelling of model uncertainties and especially the Bayesian approximation error approach, which provides computationally efficient implementations of inversion algorithms. In addition, the consortium is well known for the theory and applications of non-stationary inverse problems, that is, problems in which the unknown changes rapidly in time. The applications include various biomedical, industrial, geophysical and environmental problems.

Biomedical inverse problems

We develop computational methods and modelling for inverse problems in the field of medical imaging and biomedical research. The research topics include, for example, developing novel tomographic techniques and advancing computational methods for existing modalities.

Industrial inverse problems

Industrial applications include various different opportunities for utilizing the advanced computational inverse problems techniques. The most prominent area of research includes development of diffuse tomographic imaging for industrial process and non-destructive testing. These imaging modalities can be used for example in monitoring of pipe flows or testing of concrete structures or designing and optimizing of process vessels.

Inverse problems in geophysics and atmospheric sciences

Our research on environmental applications covers geophysical and atmospheric inverse problems, and estimation of forest resources. We aim at solving grand challenges related to natural resources and climate change.

Theoretical studies on inverse problems

The research has several foci: computational models for observations, typically partial differential equations, modelling the underlying unknowns and uncertainties, and computing estimates for the inverse (parameter estimation) problems.