معرفی
Tommi Heikkilä is a Visiting Professor in the Department of Mathematics and Statistics at the University of Helsinki. His research focuses on inverse problems, dynamic X-ray tomography, and spatio-temporal regularization methods. He is a core member of the Centre of Excellence in Inverse Modelling and Imaging (2018–2025), contributing to advancements in optimization algorithms and imaging techniques.
Key projects include developing the STEMPO dynamic X-ray tomography phantom and advancing regularization methods with optimal space-time priors. His work bridges applied mathematics and computational imaging, with applications in medical and engineering domains. He has contributed datasets for dynamic tomography experiments, including gel phantom studies and cone-beam imaging.
His doctoral thesis (2024) explores spatio-temporal regularization in dynamic tomography, reflecting his expertise in both theoretical and applied aspects of inverse problems. Collaborations span international teams in optimization, machine learning, and biomedical imaging.
