This mini-symposium highlights emerging topology and shape optimization techniques that are advancing the computational design of materials and structures. It brings together researchers and practitioners working on innovative algorithms, machine learning-assisted and data-driven approaches, and optimization under uncertainty. Applications span aerospace, biomedical, automotive, and civil infrastructure, with emphasis on additive manufacturing, multiscale and multifunctional design, and multiphysics integration. Contributions on architected, nonlinear, bioinspired, and smart materials, as well as supporting software tools, are also welcome. Topics of interest include, but are not limited to: • New topology and shape optimization algorithms • Topology optimization for aerospace, biomedical, automotive, and civil infrastructure applications • Topology and shape optimization for additive manufacturing • Machine learning-assisted, data-driven, and surrogate-based topology and shape optimization • Multiscale, multifunctional, multi-objective design of materials and structures • Multiphysics and multidisciplinary optimization • Stress-constrained topology optimization • Reduced-order multiscale modeling for design • Simultaneous material and structure optimization • Optimization under uncertainty • Design of architected materials • Design of nonlinear materials • Bioinspired design of composites • Design of metamaterials • Smart material design • Software