AFRL / AFOSR Center of Excellence: 
Data-Driven Discovery of Optimized Multifunctional Material Systems (D3OM2S)

Arising at the nexus of data science, computer vision, cognitive science, and machine learning, machine intelligence (MI) has revolutionized robotics and autonomous systems, social media, marketing, security, finance, and a host of other fields. However, the impact of MI on science and technology, including materials science and engineering (MSE), has been more muted. This discrepancy arises in part because of the diverse problems and data types encountered in the physical domain, and more critically because of the specialized knowledge required to apply MI to physically-based problems. For an MI approach to have impact on a materials research problem, the materials scientist and the MI expert must develop a mutual vocabulary and transfer domain-specific knowledge in both directions.

Carnegie Mellon University occupies a sweet spot to make the materials science – machine intelligence connection, with internationally renowned programs in both disciplines and a critical nucleus of investigators who can participate in both fields across the four thrust areas. The goal of the CMU D3OM2S CoE is to create and sustain a community of materials and MI scientists who apply the most current MI concepts to the most significant AFRL materials problems to create profoundly new approaches to materials science challenges.