Opening Tutorial: Mathematical, Statistical, and Computational Foundations of Digital Twins

This week-long tutorial, held during the first week of the long program, will provide PhD students and postdocs with an introduction to the mathematical, statistical, and computational concepts that underlie DTs, along with exposure to several scientific and engineering applications of DTs. The lectures will provide them with the core knowledge they will need to follow the subsequent workshop talks. The topics of the three foundational workshops—data assimilation and inverse problems, optimal control and decision making under uncertainty, and model reduction and surrogates—will be covered through lectures and demonstrations. These will be augmented with hands-on sessions in which the students and postdocs will have a chance to put into practice the material from the lectures, using open-source software libraries. The organizing committee will recruit several lecturers who are known for being particularly effective in communicating the material to a broader audience. The tutorial week will feature a poster session that provides the students and postdocs with an opportunity to showcase their research. The tutorial program will be aimed at PhD students and postdocs in the mathematical,statistical, and computational sciences and engineering who possess a sufficient background in PDEs, numerical linear algebra, statistics, and optimization.