With increasing advancements in information and manufacturing technologies, there is an ever‑growing need for innovative integration and application of computational design and robotic fabrication in architecture. Hybrid Intelligence in Architectural Robotic Materialization (HI-ARM) provides methods and frameworks that target this need. HI-ARM introduces methodologies and technologies that incorporate computational, fabrication and material intelligence in integrated design-to-robotic-production workflows. The intelligence is explored at multiple architectural scales (Macro, Meso, Micro) through hybridization of building processes or multi-mode robotic production and multi-materiality. Porosity, Hybridity, and Assembly are introduced as main constituents for materialization frameworks relying on computational design and robotic production. These are tested in a series of original experiments that are presented in this thesis together with four peer-reviewed published papers discussing the process of developing integrated design-to-production methodologies in detail. The contributions show how both architectural materialization processes and building products can be customized in different phases and scales. Moreover, the developed discourse and definitions address the impacts of this research through the lenses of computation and automation in research, education, and practice in the fields of Architecture, Engineering, and Construction.