The main aim of the conference is to explore the intersection of Random Matrix Theory and Machine Learning, Big Data, and more generally, massive information flows. As in previous "Matrix" meetings, we wish to encourage informal discussion and the exchange of expertise between scientists using Random Matrix theory in various areas of research spanning the above topics.

This year, we additionally have a broader goal of bridging the gap between the traditional natural sciences and the fields of Machine Learning, Information Theory and Data Science.
We are thus interested in novel applications of the latter to such fields as physics or biology as well as in examples of innovative use of methods from mathematics and statistical physics allowing progress in the areas of Machine Learning and Data Science.