Deep Learning for Experimental Image Analysis

Cold atom experiments generate a huge number of images containing atom clouds. I use state-of-the-art deep learning methods to perform analysis of these images and extract useful data such as cloud locations/sizes. These can then be used to determine the temperature of the atoms and other relevant information.

Long-term I plan to use neural networks to extract information from ultracold atom images which cannot be determined with current methods thus allowing insight into the underlying quantum mechanics.