Summary
Chace Ashcraft is an AI/ML engineer with nine years of experience applying mathematics and computer science to research-driven problem solving, currently working at Johns Hopkins APL. He specializes in multi-agent systems, deep reinforcement learning, neuro-symbolic methods, agent-based simulation, and agentic applications of large language models, with applied work in climate modeling and optimization. Comfortable translating technical research into clean Python implementations, he bridges theory and practice while emphasizing scientific integrity and measurable results. His background includes graduate research on human-swarm interaction and designing swarm simulators, plus early work in materials simulation and military team leadership, giving him a pragmatic systems perspective. He brings interdisciplinary interests—game theory, behavioral economics, cognitive science, and evolutionary algorithms—that inform creative approaches to AI problems. Outside of work he balances rigorous thinking with hands-on hobbies like weight training and drumming, reflecting a steady blend of discipline and creativity.
9 years of coding experience
5 years of employment as a software developer
Master's degree (Transferred), Computational and Applied Mathematics, Master's degree (Transferred), Computational and Applied Mathematics at University of Nevada-Las Vegas
Brigham Young University-Idaho
Master's degree, Computer Science, Master's degree, Computer Science at Brigham Young University
Spanish, English