SIAM Conference on Applied Linear Algebra (LA27)

About the Conference

This is the conference of the SIAM Activity Group on Linear Algebra.

Numerical linear algebra drives advances across technology, science, and engineering. Matrix operations and decompositions are used to train and power large language models. Quantum simulation depends on massive eigenvalue problems. In engineering applications, digital twins lead to large systems of equations to, for instance, predict structural behavior and ensure safety. Medical imaging and climate modeling depend on solving inverse problems.

Research in applied and numerical linear algebra includes novel techniques for matrix computations across application domains, methods for efficiently learning from voluminous data, and the design of algorithms for advanced computer architectures, 

The SIAM Conference on Applied Linear Algebra, organized by SIAM every three years, is a premier international conference on applied linear algebra.  It brings together international researchers and practitioners from academia, research laboratories, and industry to present their latest work, learn about new challenges, and point to new developments in the field of applied and numerical linear algebra.

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Included Themes

• AI and machine learning
• Data integration and assimilation
• Dynamical systems and model reduction
• Eigenvalue problems
• High-performance computing (HPC)
• Imaging and inverse problems
• Iterative methods, multigrid, and preconditioning
• Large language models (LLMs)
• Low-rank approximation
• Mixed-precision computation
• Network science
• Optimal transport
• Quantum computing
• Randomized algorithms
• Streaming data and online algorithms
• Tensor decompositions and applications