Mathematical breakthroughs have historically driven advances in technology, national security, and economics. Examples of these breakthroughs include cryptography methods that protect digital infrastructure or algorithms that power modern computing, such as planning, supply chain, and navigation optimization. However, the pace of mathematical discovery is limited by the capacity of human mathematicians to explore increasingly complex problems. This project addresses a critical need by developing artificial intelligence (AI) systems that can accelerate mathematical research and theorem proving at scale. The goal is to create the first AI system capable of proving graduate-level mathematical theorems and tackling unsolved problems that challenge even world-class mathematicians. One motivating observation is that current AI systems for theorem-proving are trained in a way vastly different from how mathematicians learn. In reality, mathematicians develop their skills by working collectively within an ecosystem by taking on different roles at various times. Mathematicians also specialize in various areas and skill sets while actively collaborating across areas to build connections and transfer knowledge. The key approach is to train AI systems that imitate the evolution and interactions of mathematicians. This research would serve the national interest by accelerating scientific discovery across fields that depend on advanced mathematics, from quantum computing and cybersecurity t