Structured optical materials create new computing paradigms using photons, with
transformative impact on various fields, including machine learning, computer vision …

Many exciting terahertz imaging applications, such as non-destructive evaluation,
biomedical diagnosis, and security screening, have been historically limited in practical …

Under spatially coherent light, a diffractive optical network composed of structured surfaces
can be designed to perform any arbitrary complex-valued linear transformation between its …

Nonlinear encoding of optical information can be achieved using various forms of data
representation. Here, we analyze the performances of different nonlinear information …

Releasing pre-strained two-dimensional nanomembranes to assemble on-chip three-
dimensional devices is crucial for upcoming advanced electronic and optoelectronic …

Complex field imaging, which captures both the amplitude and phase information of input
optical fields or objects, can offer rich structural insights into samples, such as their …

Image denoising, one of the essential inverse problems, targets to remove noise/artifacts
from input images. In general, digital image denoising algorithms, executed on computers …

We introduce an information-hiding camera integrated with an electronic decoder that is
jointly optimized through deep learning. This system uses a diffractive optical processor …

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path
length information of transparent specimens for various applications in biology, materials …

Quantitative phase imaging (QPI) is a label-free computational imaging technique used in
various fields, including biology and medical research. Modern QPI systems typically rely on …