Mathematics is not a static field of knowledge, but rather a multifaceted, dynamic, and expanding discipline, in which areas seemingly far from applications suddenly become indispensable and applications stimulate challenging foundational mathematical research. Moreover, many application-driven mathematical developments are also motivated and triggered by developments in other scientific and humanities fields.
The research agenda for MATH+ has not been fixed in advance for several years, but is designed to be dynamic. New fields and opportunities emerge over time, or need to be actively developed. The Topic Development Lab (TDL) is a central part of MATH+ that, based on this dynamic view of mathematics, provides a platform for developing new topics, for building bridges between different fields of mathematics (e.g., between “pure” and “applied”), and for reaching out to other areas of science and potential cooperation partners outside of mathematics. The main activity of the TDL consists of Thematic Einstein Semesters funded by the Einstein Foundation Berlin.
The current Thematic Einstein Semester (Summer 2023):
Mathematical Optimization for Machine Learning
The Thematic Einstein Semester Mathematical Optimization for Machine Learning aims at unlocking the potential of mathematics within the extremely large and diverse fields of study that constitute modern Computer Science and Data Science. It is intended to bring together young researchers and experienced scholars from mathematics and other disciplines and will consist of specific events, continuous activities over the semester, and research visits.
Past Thematic Einstein Semesters: