Sebastian Strasser
Machine Learning Engineer at Vexcel Data Program
Graz, Styria, Austria
Summary
👤
Senior🎓
Top SchoolSebastian Strasser is a Machine Learning Engineer with nine years of software and research experience, currently advancing Vexcel's AI Lab after shaping deep learning pipelines for aerial imagery and semantic segmentation. He brings six years of domain expertise in GNSS and a PhD-level background in geodesy, having processed the world's most precise GNSS time series and implemented high-performance C++/Python algorithms for trillion‑scale datasets. Habitually bridging research and production, he has deployed dense stereo and segmentation models in commercial mapping software and co-developed the open-source GROOPS geodetic toolkit. Known for squeezing more accuracy and efficiency from data—improving some orbit models by an order of magnitude—he thrives on turning complex geospatial science into scalable ML systems. Based in Graz, Austria, he combines rigorous academic publishing with hands-on engineering and user-facing documentation and support.
9 years of coding experience
3 years of employment as a software developer
Doctor of Technical Sciences (equivalent to PhD) Geodesy, Doctor of Technical Sciences (equivalent to PhD) Geodesy at Technische Universität Graz
German, English
Github Skills (28)
gravity10
recovery10
jupyterlab9
segmentation8
jupyterlab-extension8
jupyter8
image-processing7
jupyter-widget7
image-segmentation7
music7
google-play7
object-detection6
player6
machine-learning6
python6
Programming languages (5)
Github contributions (5)
sestras/issue-template-test
Mar 2022 - Mar 2022
This is just a test.
Contributions:2 PRs, 20 pushes, 2 branches in 1 day
testing
groops-devs/groops
Nov 2020 - Jul 2022
A software toolkit for gravity field recovery and GNSS processing
Contributions:52 commits, 42 comments, 25 issues in 1 year 8 months
gravityrecoveryfieldgnssgravity-field
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