The field of numerical methods for fluid dynamics and related fields is witnessing significant developments, with a focus on improving the accuracy, efficiency, and robustness of various numerical schemes. One of the notable trends is the development of new preconditioning techniques for complex problems, such as fluid-structure interaction and Navier-Stokes equations at high Reynolds numbers. Additionally, there is a growing interest in the use of hierarchical matrices and other matrix compression techniques to reduce the computational cost of large-scale simulations. The development of novel discretization methods, such as the Trefftz Continuous Galerkin method and the mixed discontinuous Galerkin method, is also an active area of research. These methods have shown promising results in terms of accuracy and stability for a wide range of problems, including Helmholtz equations and Oseen eigenvalue problems. Furthermore, the application of reduced-order models and self-adaptive timestepping techniques is becoming increasingly popular for efficient simulation of complex systems. Noteworthy papers in this regard include the introduction of a novel Trefftz Continuous Galerkin method for Helmholtz problems, which provides stable approximations with bounded coefficients and spectral accuracy for analytic solutions. Another significant contribution is the development of a self-adaptive timestepping technique for reduced-order models of incompressible flows, which allows for stable timestep increases without compromising accuracy.