Niek Tax
Staff Research Scientist at Meta
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolNiek Tax is a Staff Research Scientist at Meta with nine years of experience bridging academic rigor and production machine learning systems. He holds a PhD in Computer Science and built a strong research portfolio at Philips and universities, authoring 30 peer-reviewed papers (23 as first author) on sequence analysis, RNNs, Markov models and process mining. At Booking.com he shipped fraud-detection ML systems and taught internal courses on causal inference and process mining, showing an ability to translate theory into impactful engineering. At Meta’s Central Applied Science he focuses on foundational, long-term research and active collaboration with academia, supervising interns and publishing work that informs product teams. Colleagues describe him as a researcher-engineer who combines deep methodological expertise with practical deployment experience across large-scale data platforms.
10 years of coding experience
15 years of employment as a software developer
Master's Degree Computer Science, Master's Degree Computer Science at University of TwenteDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Eindhoven University of TechnologyPre-University Secondary Education Profiel Natuur & Techniek, Pre-University Secondary Education Profiel Natuur & Techniek at Etty Hillesum Lyceum
Dutch, English
Stackoverflow
841reputation
44kreached
9answers
25questions
Github Skills (24)
conda9
meta-learning9
calibration8
minecraft8
conda-forge7
automl7
machine-learning7
automated-machine-learning7
hyperparameter-tuning7
scala-collections6
hyperparameter-optimization6
hibernate6
scikit-learn6
lucene6
indexing6
Programming languages (5)
Github contributions (5)
TaXxER/rnnalpha
Feb 2018 - Sep 2018
Contributions:7 commits, 12 pushes, 1 branch in 7 months
facebookincubator/MCGrad
Jan 2026 - Jun 2026
MCGrad is a scalable and easy-to-use tool for multicalibration. It ensures your ML model predictions are well-calibrated not just globally (across all data), but also across virtually any segment defined by your features
Contributions:12 PRs, 24 pushes, 10 branches in 5 months
mlmodelcalibrationmachine-learningmulticalibration
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