Inverse problems arise whenever one tries to detect causes based on observations of their effect and have relevance in many fields like medical imaging, nondestructive testing of materials, seismology, geophysics, astronomy, environmental sciences, signal processing to mention but a few.

The advancement of the mathematical theory of inverse problems coupled with the the development of Artificial Intelligence (AI) allows nowadays to bridge the gap between theory and practice which represents a breakthrough in applications. In many situations the mathematical modelling of inverse problems is based on linear and nonlinear PDEs and reduces to determine unknown parameters or sources from indirect measurements.

Recently, the community of inverse problems has been exposed to fundamentally new mathematical techniques, which stimulated exciting theoretical developments and new computational algorithms for solving complex large scale inverse ill-posed boundary value problems for linear and nonlinear partial differential equations modelling processes of big impact in applications.

The aim of this conference is to bring together top leaders in the field of inverse problems for PDEs to discuss recent developments and open challenges in the mathematical theory, methods, algorithms, and applications.