I started studying mathematics in 2014 at the University of Antwerp. Here I developed a strong interest in abstract analysis, mostly topology and functional analysis. At the end of the bachelor, I got offered a summer intern job at Motulus, where I worked on a specific optimisation problem. This hands-on experience was very related, though, very different from what I previously had been doing. During my master, I studied a mix of the most abstract and most applied parts of mathematics. The interesting part is where they meet.
To complete my master, I wrote a thesis on finite topological spaces and their place in algebraic topology. Finite topological spaces sound useless to most mathematicians focussing on abstract analysis. They appear only as an artefact of the beautifully general definition of a topological space given by Hausdorff and Kuratowski. However, in algebraic topology they do have some potential, as they can be used as finite carriers of the abstraction of shape that is studied in this field.
Currently, I work in the field of Computed Tomography , better known as CT scanning. It is a great tool to get complete 3D visualisations of an object of interest. I focus specifically on the 4D tomography of the formation process of foam. Here, the goal is to create algorithms that yield moving 3D images of a foam while it is forming. In this way, this formation process can be better understood.
Campus Drie Eiken
2610 Antwerp, Belgium
I develop image reconstruction algorithms for Dynamic CT problems, which take motion and deformation during the scanning process into account. I focus on the formation process of foams, where I exploit the specific structure and shape of bubbles to improve spatial and temporal resolution.
I worked on shape optimization of sewing patterns, with the goal of adjusting clothing designs to different sizes.
Major: Pure mathematics with a focus on analysis. Minor: research. 36 ECTS credits in applied mathematics.
I have experience with optimizing objectives at all scales. Tens of variables or billions of variables. With constraints or without constraints, smooth or non-smooth, convex or non-convex, linear or non-linear...
This application area combines expertise in optimization with knowledge of signal processing.
A 3D image of dimensions 1000x1000x1000 has 1 billion voxels. Running a 1 second computation on each voxel sequentially takes over 30 years. It is only because of the massive parallelism of modern GPUs, that optimization and image processing at this scale is possible.