Workshop on Applied Algebra in Data Science

Due to the Corona pandemic this Workshop is postponed to 2021. Further information will be communicated in time.
We thank you for your understanding and apologize for any inconvenience this may cause.

Algebraic models play an ever more important role in the mathematical sciences. The path from the fundamental investigation of such models to their application in the real world is a vibrant field of research. The huge impact of data science in our lives calls for a diverse portfolio of approaches, including those from algebra.

The aim of this workshop is to make this connection. It brings together researchers working in applied algebra, with particular focus on data science. The program features overview talks about machine learning, optimization, signal processing, statistics, and related fields, as well as "hands-on" problem sessions. In addition, we intend to discuss important developments in the coming years, to foster cooperation and collaboration.

Confirmed speakers are:

• Laurent Busé (Inria Sophia-Antipolis)
• Marta Casanellas Rius (UPC Barcelona)
• Venkat Chandrasekaran (Caltech)
• Emily King (Colorado State University)
• Delaram Kahrobaei (University of York)
• Guido Montufar (MPI MiS Leipzig/UCLA)

Travel and accommodation support can be provided for early-career participants such as postdoctoral researchers and PhD students. Applicants are expected to kindly agree to present their work in the form of a poster. All relevant application data must be submitted in the registration form.

Workshop postponed to 2021 - further details follow later.