Michael Osthege
Lead Automation Engineer
Jülich, North Rhine-Westphalia, Germany
Summary
🤩
Rockstar🎓
Top SchoolMichael Osthege is a Lead Automation Engineer with 12 years of experience at the intersection of bioprocess engineering, laboratory automation, and probabilistic data science. He leads automation efforts at Mibiolab after a PhD focused on digitalization and Bayesian analysis of bioprocesses at Forschungszentrum Jülich, combining hands-on lab systems integration with statistical modeling. An active open-source contributor to heavyweight projects like PyMC, PyTensor and Aesara, he brings backend rigor—fixing broadcasting/log-probability bugs, strengthening type hints, and improving config robustness—to scientific Python tooling. Michael’s background in systems biology and molecular biotechnology, plus applied work in CNNs for microscopy, gives him a rare blend of wet-lab domain knowledge and production-quality software engineering. He’s particularly adept at turning probabilistic models into reliable automation pipelines that accelerate experimental design and interpretation.
12 years of coding experience
Master's degree, Systems Biology, Master's degree, Systems Biology at Ruprecht-Karls-Universität HeidelbergBachelor of Science (B.Sc.), Molecular and Applied Biotechnology, Bachelor of Science (B.Sc.), Molecular and Applied Biotechnology at RWTH Aachen University
German, English
Stackoverflow
621reputation
459kreached
10answers
1question
Github Skills (29)
probabilistic-programming10
python10
mypy10
statistics10
configuration-management10
numpy10
mcmc10
pymc10
bayesian10
refactoring10
bayesian-inference10
theano10
py9
code-optimization9
statistic9
Programming languages (19)
Github contributions (5)
pymc-devs/pymc
Aug 2017 - Jan 2023
Bayesian Modeling and Probabilistic Programming in Python
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:13 releases, 1016 reviews, 287 commits in 5 years 5 months
Contributions summary:Michael contributed to the Bayesian Modeling and Probabilistic Programming in Python project, pymc. The user's commits focused on fixing issues related to broadcasting and log probability computations within the distributions of the project. The user also worked on implementing new distribution-related features, such as creating distributions and related tests. The contributions include work on the DiscreteUniform function and the plotting of KDE plots to improve visualization.
bayesianprobabilistic-programmingpythonstatistical-analysisbayesian-inference
aesara-devs/aesara
Oct 2020 - Jun 2022
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
Role in this project:Backend Developer
Backend DeveloperContributions:1 release, 83 reviews, 78 commits in 1 year 8 months
Contributions summary:Michael primarily focused on refactoring and improving the codebase related to configuration parameters and the Theano library's internal structure. Their contributions involved changing how config parameters are defined and accessed, including unifying their types and updating internal code. The user also addressed specific areas like deprecating older functionalities and replacing outdated calls, contributing to code maintainability and clarity. This involved making internal code more robust by removing unnecessary dependencies.
mathematical-expressionsmultidimensional-arrayspythonsymbolic-computationtensors
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