MS1801 @ WCCM2018 -> Data-driven Methods and Applications: from Physics-informed Learning Machines to Optimization Under Uncertainty

Dear colleagues,

We encourage you to submit your abstracts to minisymposium 1801 of the 13th World Congress on Computational Mechanics (New York City, from July 22 to 27 of 2018). This minisymposium focuses on:

1. recently developed methods for data-driven approaches;

2. data-driven applications to fluids, structures and materials involving (but not limited to) machine learning, uncertainty quantification and/or optimization.

Contributions addressing specific challenges relevant to this topic such as reduced order modeling and high-performance computing are also strongly encouraged. Ideally, this minisymposium will reflect the generality of data-driven science and its broad applicability to the computational mechanics and materials science communities.

Best regards,

Miguel Bessa, Delft University of Technology

George Karniadakis, Brown University

Julien Yvonnet, Université Paris-Est