Additive manufacturing, commonly referred to as 3D printing, is a technology that could revolutionize a diverse array of applications, from personalized products to medical implants. One of the most powerful 3D printing techniques for making plastic objects uses patterned illumination of a resin to define the shape of a printed part. While light-based 3D printing is currently limited to a single material, this project aims to develop new resins that allow for printing multiple materials with varying properties, such as stiffness or elasticity, in a single step. The research will combine a feedback loop spanning materials chemistry, computational science, machine learning (ML), and physical characterization aligning with principles of the Materials Genome Initiative (MGI). The primary target for materials optimization will be the design of structured surfaces with varying mechanical properties for directing cell growth. Such surfaces are essential for both fundamental studies and practical applications. The integration of experiments, data analytics, and manufacturing methods in the research will prepare graduate and undergraduate students with diverse backgrounds for the future workforce. Public outreach and K-12 outreach to improve awareness in the science and engineering of advanced materials manufacturing methods will be carried out.