For over three decades, the Jyväskylä Summer School (JSS) has gathered students from all over the world to deepen their expertise on Science, Technology, Engineering, and Mathematics subjects and expand their professional and academic networks.
For the past two years, the FAME Flagship has joined JSS as an official partner to host inverse problems-related courses under distinguished experts from the field.
The 35th Jyväskylä Summer School will be organised on 3 – 14 August 2026. All courses are taught in English, and participation is free of charge.
Inverse problems summer school courses at JSS 2026
IP1: Electrical Impedance Tomography: Computation and Applications
Time: 10. – 14.8.2026
Study mode: In person
Lecturer: Melody Alsaker (Gonzaga University, United States)
Coordinators: Janne Nurminen and Joonas Ilmavirta
Course code: MATJ5129
Modes of study: Lectures (and project work for those who want credits)
Credits: 2 ECTS
Evaluation: Project work pass/fail
Contents: This course focuses on the applied and computational aspects of electrical impedance tomography (EIT), including modeling, EIT systems, reconstruction algorithms, and hands-on MATLAB implementation. We will examine how EIT is used in biomedical, industrial, and geophysical settings, how modeling choices influence image quality, and how to interpret reconstructed conductivity images. Modern reconstruction methods, including the use of Complex Geometrical Optics solutions in the direct D-bar method, will be explored both conceptually and through MATLAB demonstrations. It is recommended that participants bring a laptop with MATLAB installed, although a computer lab will be available. Recommended to take together with Mathematics of Electrical Impedance Tomography.
Learning outcomes: Insight into practical EIT modeling, applications, and reconstruction algorithms.
Prerequisites: Basics of linear algebra and numerical methods, introductory exposure to PDEs, and basic programming skills (preferably in MATLAB)
IP2: Mathematics of Electrical Impedance Tomography
Theme: Probability Theory
Time: 10.-14.8.2026
Study mode: In person
Lecturer: FAME Vice Director Samuli Siltanen (University of Helsinki, Finland)
Coordinator: Janne Nurminen and Joonas Ilmavirta
Code: MATJ5130
Modes of study: Lectures (and project work for those who want credits)
Credits: 2 ECTS
Evaluation: Project work pass/fail
Contents: This course focuses on mathematical aspects of electrical impedance tomography (EIT). A simple pixel-based diffusion model serves as a gentle introduction to the principle of EIT measurement, illustrating key challenges. Calderón’s inverse conductivity problem is then derived from Maxwell’s equations, and basic properties of the conductivity equation are discussed. Some knowledge of elliptic partial differential equations and Fourier transforms is useful here, but there is a strong effort to make the material as self-contained as possible. Analytic expressions are computed for the Dirichlet-to-Neumann map in case of rotationally symmetric conductivities. This makes it possible to study in concrete terms (i) Alessandrini’s example showing the ill-posedness of EIT, (ii) Calder’on’s original reconstruction approach, and (iii) Ikehata’s enclosure method. The rest of the course is devoted to the use of Complex Geometric Optics solutions for uniqueness proofs and reconstruction via the D-bar method. Recommended to take together with Electrical Impedance Tomography: Computation and Applications
Learning outcomes: Insight into the theory of EIT, including nonlinearity, ill-posedness, and reconstruction approaches.
Prerequisites: Introductory exposure to PDEs and Fourier transforms.
For further information, full course programme, and application instructions, please visit: https://www.jyu.fi/en/study-with-us/summer-and-winter-schools/jyvaskyla-summer-school
Photo: University of Jyväskylä
