Partial Differential Equations (PDEs) are fundamental tools for modeling natural phenomena across physical, biological, and social sciences. This CIMPA Summer School offers a comprehensive exploration of classical theoretical foundations alongside the expanding frontier where PDEs intersect with data science and machine learning. Designed for graduate students from East African universities whose research focuses on PDEs, the school features interactive, hands-on sessions using free software and PDE solvers. Through presentations from international participants and guest speakers, the event fosters a collaborative environment for sharing research and professional networking.
Detailed information about planned scientific activities can be found at the CIMPA webpage for the school.
Develop a solid understanding of classical PDEs and integro-differential equations.
Learn techniques such as finite difference and finite element discretization schemes.
Explore applications in image processing, mesh generation, fluid dynamics, and biological systems.
Understand how machine learning architectures approximate and accelerate PDE solutions.