MSNE 532: MODELING AND AI FOR MATERIALS
Fall 2026 · Section 001 · CRN 16587
Advances in first-principles simulation, high-throughput computation, and artificial intelligence have transformed modern materials science. This course introduces the methods and workflows used in computational materials design and discovery, with emphasis on density functional theory, materials databases, automated workflows, machine learning, machine-learned interatomic potentials, and emerging generative AI approaches. Students will gain practical experience using modern computational tools to set up, run, and interpret simulations and data-driven models for materials problems. Hands-on exercises using state-of-the-art codes, literature discussions, and a final project will reinforce the major concepts and applications.
- Credits
- 3
- Instructors
- Geoffroy Hautier