The field of computational modeling is rapidly evolving, enabling researchers to tackle increasingly complex problems that span vast temporal and spatial scales. This workshop will explore the exciting frontiers of multiscale modeling, where disparate phenomena are linked together through a hierarchical approach. Our aim is to present a cohort responding to the above challenges and opportunities by encompassing modeling, simulations across scales, and machine learning algorithms to advance discovery and innovation through computation.

 

Key topics to be covered include the following:

• Bridging the gap between atomistic, meso-, and continuum scales
• Techniques for coarse-graining and upscaling
• Multiscale simulations for materials science, engineering, and biological systems
• Machine learning and artificial intelligence in multiscale modeling of materials
• Validation and verification of multiscale models
• Emerging trends and future directions in multiscale computing

This workshop is designed for researchers and students with an interest in computational modeling, as well as scientists and engineers working in materials science, physics, chemistry, biology, and engineering.

 

The workshop will provide a platform for sharing knowledge and expertise in multiscale modeling, discussing the latest advances and challenges in the field, and fostering collaboration between researchers from different disciplines.

 

The workshop will include a strong line up of national and international speakers on advanced testing techniques and computational methods of materials by crossing the scale from the atomistic scale to the engineering scale.  Agenda to follow.

 

We invite researchers at all levels to join us for this exciting workshop and explore the power of computational modeling across scales!