Summary
Fabian Rathke is a Berlin-based data scientist with 12 years of experience applying classical ML, probabilistic graphical models, and deep learning to medical imaging and embedded vision. He has a strong research background—PhD and postdoc work on retina segmentation with multiple publications—and practical expertise in high-performance numerical coding in C, CUDA and SIMD to accelerate non-parametric density estimation. Fabian has transitioned research into industry roles at HELLA Aglaia, Volkswagen’s Car.SW Org and CARIAD, developing neural-network-based object detection for SoCs and production software stacks. Comfortable across Python, Matlab, R and low-level C, he blends theoretical rigor with production-minded optimization and a knack for squeezing performance from constrained hardware. An interesting detail: beyond model design he routinely tackles low-level implementation challenges (AVX/CUDA) to turn statistical ideas into deployable, high-performance solutions.
12 years of coding experience
10 years of employment as a software developer
M.Sc, Bioinformatics, M.Sc, Bioinformatics at Freie Universität Berlin
English