Franz Király
Director at sktime
Germany
Summary
🤩
Rockstar🎓
Top SchoolFranz Király is a director and open-source AI leader based in Germany, currently heading the German Center for Open Source AI and co-organizing the European Summer of Code. With eight years of industry experience and a strong academic pedigree—including positions at UCL, The Alan Turing Institute, and fellowships at Oberwolfach—he blends ML research, engineering, and policy-minded technology governance. As founder and core developer of sktime, he has deep hands-on expertise in time series ML frameworks and a track record improving test infrastructure and maintainability in prominent repos. He has held senior data science and principal scientist roles in industry (Shell, GfK) and short strategic appointments, demonstrating an ability to translate research-grade methods into production-ready systems. Franz’s background spans physics, mathematics, medicine and computer science, a rare interdisciplinary foundation that informs his focus on technology sovereignty and democratically governed AI.
8 years of coding experience
10 years of employment as a software developer
Dipl. phys. (BSc & MSc equivalent German degree), Physics (Physik Diplom), Dipl. phys. (BSc & MSc equivalent German degree), Physics (Physik Diplom) at Ulm University
Github Skills (15)
pytorch10
machine-learning10
time-series10
blackboard10
time-series-forecasting10
sktime10
pytest10
python10
test-automation10
data-analysis10
statistical-models9
forecast9
forecasting9
deep-learning8
data-science8
Programming languages (12)
Github contributions (5)
sktime/sktime
Mar 2019 - Jan 2023
A unified framework for machine learning with time series
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:86 releases, 6151 reviews, 2239 commits in 3 years 10 months
Contributions summary:Franz's commits primarily focused on enhancing the test suite, particularly by expanding the scope of test execution to cover more components and configurations. They made code changes across various test files, including those for model evaluation, transformations, and annotation. In addition, the user's work involved addressing inconsistencies in test practices, and refactoring the test infrastructure by introducing more robust or convenient patterns for testing and validation.
forecastingtime-series-analysistime-series-regressiondata-sciencedeep-learning
sktime/pytorch-forecasting
Aug 2024 - Mar 2025
Time series forecasting with PyTorch
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 releases, 63 reviews, 138 PRs in 6 months
Contributions summary:Franz's commits primarily involve linting and code formatting changes using `black`. They've modified several Python files, including those related to data encoding, metrics, model implementations (Temporal Fusion Transformer, DeepAR, NHiTS), and testing. These changes suggest a focus on code style consistency and maintainability within the project. The edits touch different areas of the project suggesting the user is working on core functions.
forecastingpythonartifical-intelligensetimeseries-forecastingpytorch-lightning
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