Universality in high-dimensional probability

The talk will introduce some statistical problems with a high-dimensional flavor. We will then explain how to approach such problems by finding universal sources of randomness. The problems we shall care about include on one hand detecting geometry in random geometry graphs and on the other hand approximation of random neural networks.