Lunchlezing Rijkswaterstaat

To give you a flavor of the sort of work mathematicians and information engineers do at Rijkswaterstaat, we will present you with a few recent examples. Daniel van der Maas (Bachelor in Physics and Mathematics and Mastered in Mathematical Physics) works at Rijkswaterstaat as a Data Scientist since January 2017. He will outline the approach he devised for automatic geographical map generation from aerial and satellite pictures, using deep learning methodologies. He will briefly introduce the techniques involved and will pay special attention to the way he got involved in the project and why a mathematical background proved to be extremely useful. Quirine de Kloet also started in January 2017 at Rijkswaterstaat to extend our Applied Data Science capabilities. She graduated as a Bachelor in Applied Mathematics followed by a Master in Applied Mathematics, specializing in Mathematical Physics. Before joining us as an employee, Quirine completed her Master Thesis at Rijkswaterstaat, titled ‘Modeling of Traffic on Fairways (Optimizing the Allocation of Traffic) on which she will elaborate today: although a lot of research has been conducted on road traffic and multiple models have been invented and applied, the topic of traffic on fairways has been largely neglected. The research goal for the graduation project was therefor to define a model that can simulate traffic on fairways, using it to optimize traffic allocation.