Materials modeling and simulation approaches continue to provide valuable insights and guidance for researchers working on new materials and product development across a wide range of industries. It is becoming clear that by encoding the physics of materials behavior, and capturing the domain knowledge from many decades of materials development and testing, these techniques may provide even greater value in machine learning and AI approaches.
This symposium will highlight the latest advances in AI, machine learning and autonomous research approaches for materials development.
We will also highlight applications-focused theoretical developments, industry applications and case studies in materials modeling and simulation (across all length scales).
Submit your abstract today and plan to share your research results and insights at this exciting event.
Please first review the information for authors — abstract submission guidelines.