Controlling electromagnetic waves and information simultaneously by information
metasurfaces is of central importance in modern society. Intelligent metasurfaces are smart …

Artificial intelligence tasks across numerous applications require accelerators for fast and
low-power execution. Optical computing systems may be able to meet these domain-specific …

Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability. Deep-learning …

Ghost imaging (GI) facilitates image acquisition under low-light conditions by single-pixel
measurements and thus has great potential in applications in various fields ranging from …

Modern cameras typically use an array of millions of detector pixels to capture images. By
contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with …

Capturing high-dimensional (HD) data is a long-term challenge in signal processing and
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …

Recent work in machine learning shows that deep neural networks can be used to solve a
wide variety of inverse problems arising in computational imaging. We explore the central …

Spatial light modulators (SLM), capable of dynamically and spatially manipulating
electromagnetic waves, have reshaped modern life in projection display and remote …

Optical imaging is commonly used for both scientific and technological applications across
industry and academia. In image sensing, a measurement, such as of an object's position or …

Over the past several decades the dramatic increase in the availability of computational
resources, coupled with the maturation of machine learning, has profoundly impacted …