Inverse problems are omnipresent in many disciplines including the sciences and engineering. Most commonly these are inverse imaging problems where an image is to be reconstructed from indirect and noisy measurements. In this talk, I will review modern challenges in the field and highlight connections to other disciplines such as optimization and machine learning. The presentation will be concluded with a few of my contributions to solve these challenges.