Multiphysics problems involve the interaction of multiple physical phenomena, such as fluid-structure interaction, conjugate heat transfer, or aeroacoustics and are prevalent in various fields, including aerospace engineering, biomedical applications, and environmental science. These problems often encompass multiple time and spatial scales; for instance, the heat transfer between a cooled surface and a hot turbulent flow exhibits small convective time scales in the fluid, while the heat transfer into a solid is governed by possibly orders of magnitude larger heat conduction time scales. Therefore, numerical simulations of multiphysics problems often become computationally expensive and require high-performance computing capabilities. Casting the complete multiphysics problem into a single unifying formulation can be challenging and expensive. Since the physical processes are usually governed by different sets of governing equations, individually optimized solution schemes are frequently used for their solution. While the performance of the dedicated solution schemes is important, the coupling between solvers and the required data exchange between numerical methods can create significant bottlenecks especially on parallel high-performance computing systems. On such systems, minimizing the time needed for communication of coupling information and synchronization of solvers is essential to achieve acceptable computational efficiency. This overhead can become even larger when adaptive mesh refinement is utilized in each solver, necessitating dynamic load balancing not only for each solution method, but also for the fully coupled problem. This minisymposium invites papers, that address numerical methods for solving multiphysics problems with a focus on their applicability to HPC systems. We welcome contributions related to unifying formulations, coupling algorithms and techniques from various areas of computational engineering sciences with an emphasis on their computational performance. By fostering discussions around innovative approaches and strategies in this domain, we aim to advance our understanding and capability in tackling complex multiphysics challenges effectively.