Kaspar Sakmann
Machine Learning Research Engineer at Bosch Center for Artificial Intelligence (BCAI)
Stuttgart, Baden-Württemberg, Germany
Summary
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Senior🎓
Top SchoolKaspar Sakmann is a Machine Learning Research Engineer at the Bosch Center for Artificial Intelligence with 11 years of experience bridging physics and applied ML, focusing on robustness for computer vision—including anomaly segmentation, out-of-distribution object detection, and conformal prediction. He brings a strong physics pedigree (PhD and postdoctoral work at Heidelberg, Stanford, and Vienna) with publications in ICLR, ICCV, Nature Physics and PRL, and a practical history building big-data geolocation services at T‑Mobile Austria. Kaspar’s work uniquely combines many-body quantum simulation techniques and experimental imaging expertise with production-minded ML research, enabling novel approaches to uncertainty and robustness. Based in Stuttgart, he maintains an active research portfolio and public presence (ksakmann.github.io, Google Scholar), reflecting both deep academic rigor and hands-on engineering.
11 years of coding experience
3 years of employment as a software developer
Doctor of Science Theoretical and Mathematical Physics, Doctor of Science Theoretical and Mathematical Physics at Heidelberg UniversitySelf-Driving Car Nanodegree Program Autonomous Driving, Self-Driving Car Nanodegree Program Autonomous Driving at Udacity
German, English, French
Github Skills (25)
kubernetes9
python9
simulator7
ethereum5
cpp4
pybind113
poisson3
evm3
neural-network3
capstone3
image-processing2
reduction2
cuda2
python-bindings2
openmp2
Programming languages (4)
Github contributions (5)
ksakmann/CarND-BehavioralCloning
Dec 2016 - Feb 2017
Contributions:53 commits, 1 PR, 43 pushes in 2 months
driving-behaviorconvolutional-neural-networkconvolutionalclonessimulator
ksakmann/CarND-Vehicle-Detection
Feb 2017 - Feb 2017
Contributions:51 commits, 48 pushes, 1 branch in 23 days
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