Applied Harmonic Analysis and Data Science

Abstract

Data science is a field of major importance for science and technology nowadays and poses a large variety of challenging mathematical questions. The area of applied harmonic analysis has a significant impact on such problems by providing methodologies both for theoretical questions and for a wide range of applications in machine learning, as well as in in signal and image processing. Building on the success of four previous workshops on applied harmonic analysis in 2012, 2015, 2018, 2021, this workshop focused on several exciting directions, such as mathematical theory of deep learning, phase-retrieval time-frequency analysis, and sampling on t-design curves, and discussed open problems in the field.