Domain decomposition is an active interdisciplinary area of research in the mathematical analysis and computational implementation of decoupling and coupling strategies for models of natural and engineered physical systems, networks, and graphs.  Since the advent of distributed-memory supercomputers, it has been motivated by considerations of concurrency and locality for a wide variety of large-scale problems, continuous and discrete.  Historically, it emerged from the analysis of partial differential equations, beginning with the work of Schwarz in 1870.  This volume contains fifty papers originally presented at the 28th International Conference on Domain Decomposition Methods at the King Abdullah University of Science and Technology in Saudi Arabia in 2024 by scientists from 24 countries, updated post-conference to 2026, spanning from fluid flow to Helmholtz problems, from optimization to neural networks.

Domain decomposition is an active interdisciplinary area of research in the mathematical analysis and computational implementation of decoupling and coupling strategies for models of natural and engineered physical systems, networks, and graphs.  Since the advent of distributed-memory supercomputers, it has been motivated by considerations of concurrency and locality for a wide variety of large-scale problems, continuous and discrete.  Historically, it emerged from the analysis of partial differential equations, beginning with the work of Schwarz in 1870.  This volume contains fifty papers originally presented at the 28th International Conference on Domain Decomposition Methods at the King Abdullah University of Science and Technology in Saudi Arabia in 2024 by scientists from 24 countries, updated post-conference to 2026, spanning from fluid flow to Helmholtz problems, from optimization to neural networks.