The aim of this conference is to bring together the applied mathematics, statistics, machine learning, engineering, physics and industrial communities around the topic of inverse problems to discuss recent developments and open challenges in theory, methodology, computational algorithms, and applications. The event will welcome industrial representatives, doctoral students, early career and established academics working in this field to attend.

Topics of interest include, for example:

• Inverse problems in mathematical and computational imaging;
• Inverse problems in science, medicine, engineering, and other fields;
• Model‐based and data‐driven methods for solving inverse problems;
• Optimisation, statistical, and machine learning methods for solving inverse problems;
• Mathematical theory for inverse problems;
• Deterministic and stochastic computational methods and algorithms.

Luca Calatroni  CNRS & Nice University
Andrew Duncan  Imperial College London
Jason McEwen  University College London & Kagenova
Thomas Pock  Graz University of Technology
Gabriele Steidl  Berlin Institute of Technology
Yi Yu  University of Warwick