Jona Sassenhagen
Senior ML Research Engineer at Neo Cybernetica
Andernach, Rhineland-Palatinate, Germany
Summary
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Rockstar🎓
Top SchoolJona Sassenhagen is a Senior ML Research Engineer in Andernach, Germany, with 12 years of experience combining academic neuroscience, linguistics, and production machine learning. He holds a summa cum laude PhD in linguistics and transitioned from postdoctoral neural time-series research to leading engineering efforts at DataRobot, where he managed a team of 10 and led federal NLP work while shipping model monitoring, explainability, and COVID-era forecasting features. In open source he has improved reliability for scientific ML tools—adding test automation for nilearn's surface plotting and fixing data-format and plotting issues in MNE‑Python. He blends statistical rigor from academia with pragmatic engineering to deliver robust, production-ready analytics and monitoring systems.
12 years of coding experience
8 years of employment as a software developer
The Philipp University of Marburg
German, English
Github Skills (14)
megaparsec10
pytest10
python10
test-automation10
testing10
plots9
filter9
data-analysis9
matplotlib9
plot9
filtering9
neuroimaging8
brain-imaging8
eeglab7
Programming languages (13)
Github contributions (5)
mne-tools/mne-python
Nov 2014 - May 2022
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 reviews, 528 commits, 227 PRs in 7 years 7 months
Contributions summary:Jona primarily contributed to the MNE-python repository by fixing bugs and adding support for new data formats within the EEG/MEG analysis framework. Their work included resolving issues with the reading and processing of BrainVision data, particularly handling events and channel locations. Furthermore, they added functionality to handle missing values for the lowpass filter in the epochs image, and extended the plotting capabilities of the software.
visualizationneuroimagingneurosciencepythonstatistics
nilearn/nilearn
Jun 2017 - Jul 2017
Machine learning for NeuroImaging in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:9 commits, 1 PR, 16 comments in 1 month
Contributions summary:Jona primarily focused on adding and modifying tests within the `nilearn` repository. Their contributions involved writing tests for plotting functions, particularly for surface plotting. The user implemented new test cases, integrated existing tests with axes, and introduced the use of temporary files for output. This work aimed to improve code coverage and ensure the reliability of the plotting functionalities.
neuroimagingpythondecodingbrain-connectivitymachine-learning
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