Ville Kolehmainen is a Professor at the Department of Technical Physics within the Faculty of Science, Forestry and Technology at the University of Eastern Finland (UEF). His research focuses extensively on computational inverse problems and uncertainty quantification , with applications in advanced medical imaging techniques such as X-ray tomography , diffuse tomography , and MRI . He actively collaborates with clinical experts and engineering specialists to develop novel imaging modalities for 3D/4D imaging with sparse data Electrical impedance tomography (EIT) Multi-energy CT reconstruction Thermal tomography Ville Kolehmainen leads the Inverse Problems research group (active since 2010) and contributes to the Neuro-Innovation project (2021-2026). His work integrates Bayesian statistical inversion , parallel level sets , and nonlinear reconstruction methods to address challenges in Medical tomography Optical diffusion tomography Thermal conductivity estimation Atmospheric remote sensing Recent publications highlight his contributions to electrical impedance tomography for hemorrhagic stroke monitoring, dual-modality imaging of two-phase flows, and deep learning post-process corrections in remote sensing. His methodological innovations include model error compensation , sparsity-promoting inversion , and anatomical prior integration in image reconstruction. Collaborations span University of Eastern Finland , University College London , and Harvard Medical School researchers.
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