Joost Berkhout

Assistant Professor Of Analytics And Optimization

Amsterdam, North Holland, Netherlands
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Summary

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Senior
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Top School
Joost Berkhout is an assistant professor in analytics and optimization with eight years of experience turning operations research into practical solutions for industry and teaching. Based in Amsterdam, he researches mathematical optimization under uncertainty, with deep expertise in Markov chain theory and simulation optimization applied to problems like PageRank and dynamic production scheduling. His work bridges academia and industry — notably developing robust scheduling algorithms for biomaterials manufacturing that handle machine downtime and urgent orders. He teaches optimization courses at Vrije Universiteit Amsterdam while supervising research that connects theoretical insights to real-time decision making. Joost combines rigorous PhD-level theory with hands-on project experience, making complex stochastic models actionable for planners and engineers. An underappreciated strength is his knack for translating Markov-chain-based analysis into scalable heuristics that practitioners can deploy in live operational settings.
code8 years of coding experience
job4 years of employment as a software developer
bookDoctor of Philosophy - PhD, Econometrics and Operations Research, Doctor of Philosophy - PhD, Econometrics and Operations Research at Vrije Universiteit Amsterdam
bookVWO Atheneum, Natuur en Techniek, VWO Atheneum, Natuur en Techniek at Jan Arentsz
languagesDutch, English
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Github Skills (30)

cp-sat10
xai9
operations-research9
constraint-programming9
optimization9
python8
scheduling7
scientific-computing6
numpy6
pipeline5
sql5
machine-learning5
dataflow5
coin-or4
artificial-intelligence4

Programming languages (3)

C++Jupyter NotebookPython

Github contributions (5)

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JoostBerkhout/XAI

Jun 2018 - Jul 2020

Prototyping about eXplainable Artificial Inteligence (XAI)
Contributions:4 PRs, 30 pushes in 2 years 1 month
xaideep-learningartificialmachine-learningprototyping
JoostBerkhout/PyKDA

Feb 2024 - Nov 2025

Contributions:10 releases, 68 pushes, 2 branches in 1 year 8 months
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