Imaging can take many forms—from optical microscopes and telescopes through
ultrasonography to X-ray tomography. However, regardless of the imaging modality, the …

Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …

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 …

The last decade has seen the development of a wide set of tools, such as wavefront
sha**, computational or fundamental methods, that allow us to understand and control …

Medical microrobots (MRs) have been demonstrated for a variety of non-invasive biomedical
applications, such as tissue engineering, drug delivery, and assisted fertilization, among …

Optical imaging has had a central role in elucidating the underlying biological and
physiological mechanisms in living specimens owing to its high spatial resolution, molecular …

Imaging through scattering is an important yet challenging problem. Tremendous progress
has been made by exploiting the deterministic input–output “transmission matrix” for a fixed …

How to image objects that are hidden from a camera's view is a problem of fundamental
importance to many fields of research 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 …

Optical techniques offer a wide variety of applications as light-matter interactions provide
extremely sensitive mechanisms to probe or treat target media. Most of these …

The newly emerging field of wave front sha** in complex media has recently seen
enormous progress. The driving force behind these advances has been the experimental …