The rapid rise of advanced manufacturing methods—such as additive manufacturing, nanotechnology, and bioinspired design—has enabled the development of next-generation materials with complex architectures and tailored functionalities, including architected lattices, fibre-reinforced composites, shape-memory materials, electroactive polymers, and metamaterials. While these materials offer vast potential across sectors like biomedicine, aerospace, and energy, their complex microstructures and behaviours—marked by anisotropy, inelasticity, and multiphysical coupling—pose major challenges for traditional modelling and simulation approaches, calling for new, more capable computational strategies. This mini-symposium aims to bring together researchers working at the forefront of material modelling, characterisation, and computational design. We are particularly interested in contributions that integrate machine learning and AI, physics-informed modelling, multiscale and multiphysics approaches, and advanced numerical methods. We also welcome experimental, data-driven, and hybrid strategies that inform, validate, or augment computational models. We invite submissions across a wide spectrum of topics, including but not limited to: • Advanced constitutive modelling of complex and functional materials • Multiscale and multiphysics modelling techniques • Data-driven and AI-enhanced material models • Inverse design and topology optimisation of materials and structures • Computational design of mechanical and multifunctional metamaterials • Bioinspired, programmable, and soft materials modelling • Integrated experimental–computational approaches for model calibration and validation • Digital twins for materials and structures • Emerging methods for uncertainty quantification and robust material design This symposium aims to foster interdisciplinary discussion and cross-pollination of ideas between mechanics, materials science, computational engineering, and data science communities.