This Faculty Early Career Development (CAREER) grant supports research in data-driven robotic three-dimensional concrete printing to create materially efficient reinforced concrete building elements, enabling the rapid construction of multistory buildings and addressing urgent housing shortages. Current attempts at such printing suffer from a limitation of the printer’s depositing material only in layers parallel to the ground, restricting its application to simple forms and making it incompatible with the production of materially efficient parts that entail complex geometries. This technological limitation is exacerbated by the need for constant human monitoring and tuning of the process to eliminate defects. As a result, current applications are limited to single-family houses with simple geometries that use more concrete, not less, than if manufactured using traditional formwork methods, thus limiting widespread adoption by the industry. This project looks to develop new printing methods that reliably deposit material in complex geometries inherent to materially efficient parts. This research intends to transition its methods into education to combat the significant decline in youth interested in construction careers. The project strives to prepare future generations through courses in robotic three-dimensional printing, data modeling, and machine learning. It will engage youth through interactive puzzles and digital robotic workshops It positions the U.S. as a leader in r