Machine learning applied to inverse systems design

In this work, we will give an overview of some of the most recent and successful applications of machine learning-based inverse system designs in photonic systems. Then, we will focus on our recent research on the Raman amplifier inverse design. We will show how the machine learning framework is optimized to generate on-demand arbitrary Raman gain profiles in a controlled and fast way and how it can become a key feature for future optical communication systems.