Event Details

With the aid of existing research and computer simulations, there are now very powerful numerical tools to solve PDEs. This summer school aims to equip young researchers interested in this field with the skills and knowledge necessary to tackle some of the challenges in this area

This event is being funded by the Prob_AI Hub, through the Network & Development Fund.

Partial differential equations (PDEs) are ubiquitous in mathematical modeling. They have applications in a wide variety of fields, including engineering, climate modeling, medicine, chemistry, and nuclear reactors. Along with this wide range of applications comes a continued interest in the research community to make use of PDEs in their work.

With the aid of existing research and computer simulations, there are now very powerful numerical tools to solve PDEs. However, many challenges still remain, particularly in the era of data science and high-performance computing.

This summer school aims to equip young researchers interested in this field with the skills and knowledge necessary to tackle some of the challenges in this area. On each day, the event will focus on one of these four topics:

• Data Assimilation
• High-Dimensional PDEs
• Scientific Machine Learning
• PDE-Constrained Optimization