The summer school was focused on Uncertainty Quantification, specifically pretending to Inverse Problems.
We sat through hours of lecture and about half the days we managed to spend programming/implementing some of what we learned.
At the end of the summer school we had to perform a project, and I paired up with a couple of students to work on an inverse problem involving the Helmholtz equation.
I wanted to see how the methods I was researching and developing would be able to compare for a problem involving using sound to determine the shape of a region of different density (an occlusion) within the interior.
I learned a lot about Deterministic Optimization, Variational Calculus, and Bayesian methods for solving inverse problems, giving me a wealth of information about the other methods that people use to solve problems similar to those that I work on. It was a great exposure to a diverse range of research topics.
10⁄10 would recommend. Like a firehose of information, but truly an experience that greatly contributed to my maturity as a mathematician. I loved being able to talk to the professors who organized and taught the workshop. I learned so much from brief conversations over meals.
Unfortunately I am unable to show any results from this because I accidentally deleted the entire software environment where I was storing my data. This little accidents inspired me to learn more about docker and ensure that this would never happen again by learning how to properly segment data from application state.