This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support fundamental research to accelerate the discovery, design, and implementation of new engineered photonic materials using a data-driven deep learning approach. The $375,000 award to the Georgia Tech Research Corporation will integrate materials science, photonics, engineering, physics, and artificial intelligence to develop photonic metamaterials with user-defined spatial, spectral, linear, non-linear, and quantum properties. The research aims to establish deep learning frameworks for efficient photonic metamaterial design, integrate tailorable optical properties into reconfigurable metamaterial models, and investigate hybrid material systems coupling topological photonic structures with quantum emitters and optical nonlinearities. This interdisciplinary effort is expected to generate new insights on the relationships between material structure, properties, performance, and processing at different scales, ultimately driving transformative applications of photonic metamaterials for classical and quantum information processing.