The goal of this workshop is to bring together PhD students and early career researchers in Mathematics, Statistics, and related fields, with the aim of contributing to the further development of mathematical foundations for data science. Specifically, our aim is to create a collective platform for the development of a strong theoretical understanding of the interaction between modern problems in data science (such as the representation of complex spatio-temporal dynamics using topological and geometric summaries, adversarial learning and its connections to regularization and generalization, and the design of novel objective functions for robust data analysis) and areas in pure and applied mathematics such as spectral geometry, metric measure space geometry, optimal transportation, and topological data analysis. Each of these areas has been steadily gaining maturity and prominence in applied domains including neuroscience, machine learning, sociology, and materials science.
In preparation for the workshop, we will organize mini-courses on relevant/concomitant aspects of the following topics:
The emphasis of the minicourses will be on showcasing specific open problems related to data analysis. These topics will form the basis for the discussion during the workshop.
Please note that you may apply to more than one MRC conference if they match your research interests. A separate application is needed for each one. However, you can only be selected as a participant in one conference.
Applications were accepted on MathPrograms with a deadline of February 15, 2022. No new applications are being accepted at this time.
For questions about the application process, please contact the Programs Department at the AMS.