Imaging and Sensing in Extreme Conditions

Imaging through scattering is arguably the most important open problem in optics. If one could overcome scattering, one could (a) see through tissue to observe "biology in action" at cellular scale; (b) see through fog, smoke, and inclement weather to safely navigate in adverse conditions; (c) see through the atmosphere and allow ground-based telescopes to outperform James Webb for a fraction of the cost; and (d) see through thin fiber bundles to enable minimally invasive endoscopy. This talk will describe how we have combined computational optics with machine learning to enable breakthrough imaging-through-scattering capabilities. I will also briefly discuss how we have applied recent advances in machine learning to improve the resolution, robustness, speed, and survivability of various sensing platforms.