Thierry Mondeel

Chapter Lead Business Intelligence, Data Science & AI

Lisse, South Holland, Netherlands
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Summary

👤
Senior
🎓
Top School
Thierry Mondeel is a senior customer intelligence analyst and data scientist with a decade of experience bridging statistical rigor and practical product delivery in public sector analytics and computational biology. With a PhD in Computational Systems Biology and an MSc in Mathematics, he specializes in Python, R, SQL, Bayesian and causal inference, and interpretable ML techniques such as SHAP, while also exploring synthetic data methods like GANs and VAEs. At UWV he progressed from hands-on analytics to product ownership of the Data Science Team, translating large, heterogeneous datasets into actionable insights and scalable models. His research background includes predictive dynamical models and bioinformatics tools—he contributed backend improvements and tests to the well-known COBRA Toolbox for constraint-based metabolic modeling. Colleagues describe him as equally comfortable diving into differential equations or production SQL pipelines, and off-hours he plays drums, a hobby that mirrors his taste for rhythm and complex patterns.
code11 years of coding experience
bookMaster's degree, Mathematics (Biomedical track), Master's degree, Mathematics (Biomedical track) at Vrije Universiteit Amsterdam (VU Amsterdam)
bookVWO, Science & Technology, VWO, Science & Technology at Fioretti College
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Github Skills (6)

bioinformatics10
biom10
constraint10
matlab10
constraint-satisfaction10
testing8

Programming languages (5)

TeXJavaScriptJupyter NotebookMATLABPython

Github contributions (5)

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opencobra/cobratoolbox

Jul 2015 - Aug 2016

The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:
Role in this project:
userBack-end Developer
Contributions:6 commits, 3 PRs, 2 comments in 1 year 1 month
Contributions summary:Thierry primarily contributed to the `cobratoolbox` by modifying existing functions and improving the usability of the software. They modified `findTransRxns` to include a boolean vector output and fixed naming discrepancies between `xls2model` and `writeCbModel` for data import/export. Furthermore, the user commented out output statements in functions (`addReaction` and `changeGeneAssociation`) that could negatively impact performance and create clutter, especially when reading excel files. They also added a test function (`testXls2Model`) to validate the import of an excel model file.
microbiome-analysisgap-fillingmetabolic-reconstructioncobra-toolboxomics-data-integration
Contributions:2 releases, 19 commits, 17 pushes in 2 years 11 months
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