Developed at the MIT Media Lab's Mediated Matter Group by Christoph Bader, Dominik Kolb, James C. Weaver, and Neri Oxman, Data-Driven Material Modeling refers specifically to the process of the creation of high-resolution, geometrically complex, and materially heterogeneous 3D printed objects at product scale.

This approach utilizes external and user-generated data sets for the evaluation of heterogeneous material distributions during slice generation, thereby enabling the production of voxel-matrices describing material distributions for bitmap-printing at the 3D printer’s native voxel resolution. This bitmap-slicing framework designed to inform material property distribution in concert with slice generation contrasts existing approaches by emphasising the ability to integrate multiple geometry-based data sources to achieve high levels of control. Whereas 3D printing generally uses meshes, these often ignore the design potential of heterogeneous material distributions that are volumetric in nature and are usually printed using specific and singular material. Data-Driven Material Modeling process on the other hand, enables precise spatial control over the deposition of individual material droplets, where material composition is controlled at the droplet level by defining— for each deposited material—a binary 3D voxel-matrix at the native resolution of the printer (Connex500 printers can 3D print in 16-micron resolution—hair thickness resolution).