The field of numerical methods for complex systems is rapidly evolving, with a focus on developing innovative techniques for solving large-scale problems. Recent developments have centered around improving the performance and scalability of existing methods, such as adaptive mesh refinement and parallel-in-time algorithms. Notably, new approaches have been proposed for handling heterogeneous problems, including optimized Schwarz methods and Nitsche-type formulations. Additionally, there has been significant progress in the development of high-order compact schemes and space-time finite element methods, which have shown promising results in terms of accuracy and efficiency. These advances have the potential to significantly impact various fields, including engineering, physics, and materials science. Noteworthy papers include: A Parareal Algorithm with Spectral Coarse Solver, which introduces a new class of Parareal algorithms with improved performance and parallelism. Large-Scale Topology Optimisation of Time-dependent Thermal Conduction Using Space-Time Finite Elements and a Parallel Space-Time Multigrid Preconditioner, which presents a novel space-time topology optimization framework with excellent scalability.