This thesis addresses the growing demand for sustainable ship design by focusing on the optimization of hull forms. The hull form geometry directly influences the ship's hydrodynamic resistance, and consequently its fuel consumption and emissions. As the maritime industry faces increasingly stringent environmental regulations, there is a pressing need for design methodologies that can deliver high-performance hull forms across diverse operational conditions, while remaining computationally efficient and producing physically meaningful geometries. Taken together, the contributions of this thesis provide a framework for hull form optimization that is data-efficient and generalizable. By enabling the reuse of simulation data across different designs and parameterizations, the proposed methods establish a more sustainable and scalable foundation for future ship design workflows. The results support design exploration that is fast, interpretable, and regulation-compliant, helping to align the maritime industry’s operational and environmental goals.