Hi Iβm Jan. I believe in the beauty π and power πͺ of mathematics. By teaming up with like-minded people π₯, I love to translate math into code π» to find intelligent solutions for real world problems.
This mission led me to study Data Science for my Masterβs at ETH and Harvard, which I finished at the end of 2023.
During two research projects at these institutions, I worked on problems in computer vision and scientific computing:
π Throughout my 9-month full-time research stay with Petros Koumoutsakos at Harvard, I tackled the problem of data-driven turbulence models in computational fluid dynamics. To that end, I developed a new method to learn such a turbulence model using reinforcement learning. The resulting paper is currently under review. You can find the preprint here [Link].
π³ During my 3-month research project at Stefano Mintchevβs lab at ETH, I worked on depth estimation solutions to infer occluded tree branches from RGB-D imagery. The resulting paper is accepted in IEEE RA-L [Link].
Currently, I am actively seeking a PhD position and am particularly excited about representation learning and scientific ML.
If this text resonates with you, feel free to reach out. I love meeting new people. You can reach me at vbjan[at]ethz[dot]ch.
You can find an up-to-date collection of my publications on Google Scholar.
Autograd: [Link]: Automatic differentiation and gradient descent from scratch for arbitrary optimization problems.
Tree Branch Detection [Link]: Depth estimation of leafless branch structure given RGB-D image of tree using CNN.
Bachelor Thesis on Neural ODEs [Link]: Depth estimation of leafless branch structure given an RGB-D image of a tree using CNN.
Gaussian Processes for Control [Link]: Studying Gaussian Processes and writing a comprehensive report on methods of propagating uncertainty for control purposes.
Webscraping Bot [Link]: Automation of gym reservations.
2D-FEM on L-shape Domain [Link]: Numerical approximation of the stationary reaction diffusion equation on L-shape domain.