Artificial intelligence inspired design of non-Hermitian systems

Aim: to develop generative deep learning models to offer on-demand optical functionalities of non-Hermitian structures 

Goals
Develop GANs models to solve the complex inverse scattering problems in non-Hermitian Systems;
Develop CycleGANs models for retrieval of structure’s geometry to obtain desired far field patterns
Develop Variational Autoencoders (VAEs) architectures for inverse design of non-Hermitian spatial filters


Investigator: