Stefan Wunsch
Forward Deployed Engineer at Palantir Technologies
Geneva, Geneva, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolStefan Wunsch is a Forward Deployed Engineer at Palantir with 12 years of experience building high-throughput, production-ready software at the intersection of scientific computing and machine learning. He holds a PhD in Physics from KIT and spent years contributing to CERN’s ROOT framework—improving Python/ML integrations and fixing memory leaks—bringing domain expertise in data-intensive analysis. His open-source QA and backend work includes testing contributions to the widely used GNU Radio project and ML enhancements to ROOT’s TMVA, reflecting a strong focus on reliability and scientific tooling. Past roles span radar signal processing and autonomous driving, where he designed novel detection methods (patented) and deployed neural networks in real-time systems. Stefan combines low-level C++ performance engineering with Python-driven ML workflows, making him effective at shipping robust, scalable solutions for complex, data-rich environments.
12 years of coding experience
4 years of employment as a software developer
Doctor of Natural Sciences - PhD Physics, Doctor of Natural Sciences - PhD Physics at Karlsruhe Institute of Technology (KIT)
French, German, English
Github Skills (27)
unit-testing10
xgboost10
c-language10
python10
testing10
deep-learning10
randomization10
cprogramming-language10
gnuradio10
data-structure9
dspic9
algorithm9
algorithms9
numpy9
dspace9
Programming languages (9)
Github contributions (5)
root-project/root
Oct 2016 - Apr 2021
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:148 reviews, 363 commits, 465 PRs in 4 years 7 months
Contributions summary:Stefan's contributions focused on enhancing the machine learning capabilities within the ROOT project, specifically within the TMVA (Toolkit for Multivariate Analysis) framework. Their work involved improving and adding features to machine learning methods based on Python, including refactoring of existing methods like PyRandomForest, PyGTB, PyAdaBoost and adding PyKeras for deep learning. The user also implemented new helper functions for the RVec class, allowing for enhanced functionality in the tree inference context, and addressed various minor issues and memory leaks.
pythonroot-cernmathematicsc-plus-plusscientific-visualization
gnuradio/gnuradio
Sep 2015 - Aug 2016
GNU Radio – the Free and Open Software Radio Ecosystem
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 PRs, 20 comments in 1 year
Contributions summary:Stefan primarily contributed to the quality assurance and testing aspects of the GNU Radio project. They added unit tests, focusing on the `random` module, including tests for uniform, Gaussian, Laplacian, and Rayleigh distributions. The user also implemented and updated test cases, addressing issues and enhancing the testing coverage within the codebase. Furthermore, the user adapted test cases for reseed functionalities in the `random` module.
pythonwirelessc-plus-pluscybersecuritycommunications
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