EMS - Topical Activity Group on Applied and Numerical Linear Algebra, Matrix Analysis and Applications

Applied Numerical Linear Algebra is a very active area of research that is fundamental to many fields in science and engineering. In scientific computing,  the discretization of (stochastic) partial differential equations often leads to large-scale linear algebra problems. Other sources of challenging matrix problems include data science and data analysis applications as well as graph and network analysis. Data intensive applications in many scientific disciplines frequently give rise to large scale tensor computations. Linear and nonlinear eigenvalue problems are fundamental to many applications in engineering, physics, chemistry, and other fields.

Topics of current interest include: 

• Nonlinear eigenvalue problems

• Tensor algorithms and analysis

• Krylov subspace methods for linear systems and eigenvalue problems

• Algorithms for structured matrices

• Model order reduction

• Computation of matrix functions

• Randomized algorithms

• Inverse problems

The analysis of matrix problems and algorithms interface with many other mathematical disciplines, including functional analysis, stochastic analysis, discrete mathematics, approximation theory, and optimization.

The motivation of the Topical Activity Group of the European Mathematical Society is to bring together European scientists who work in the area of (numerical and applied) linear algebra, matrix analysis and applications. Here are the bylaws of the TAG.

Here are the by-laws of the EMS Topical Activity Group E-ANLAMA.