Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

Electromagnetic (EM) imaging is widely applied in sensing for security, biomedicine,
geophysics, and various industries. It is an ill-posed inverse problem whose solution is …

Recent breakthroughs in deep learning have ushered in an essential tool for optics and
photonics, recurring in various applications of material design, system optimization, and …

Invisibility has been a topic of long‐standing interest owing to the advent of metamaterials
and transformation optics, but still faces open challenges after its tremendous development …

The physical basis of a smart city, the wireless channel, plays an important role in
coordinating functions across a variety of systems and disordered environments, with …

Optical illusion has always attracted extensive attention, as it provides a superior self‐
protection ability for both natural animals and human beings. A decade ago, this motivated …

With the rapid growth in intelligent metasurfaces in the recent years, deep learning has
attracted attention to transform the ways in which metasurfaces are simulated and designed …

Invisibility has been a long-standing topic, owing to its crucial importance in both academia
and industry. At the close of the last century, the advent of metamaterials unprecedentedly …

In this work, we design an iterative deep neural network to solve full-wave inverse scattering
problems (ISPs) in the 2-D case. Forward modeling neural networks that predict the …

Electrical Impedance Tomography (EIT) has emerged as a valuable medical imaging
modality, which visualizes the conductivity distribution of a subject by performing multi …