Arnaud Delaunoy
Machine Learning Engineer at CluePoints
Liège, Liège, Belgium
Summary
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Rockstar🎓
Top SchoolArnaud Delaunoy is a machine learning engineer and near-PhD researcher with seven years of experience bridging simulation-based inference, generative modeling and Bayesian methods. He has taught deep learning and statistics, led practical coursework at Université de Liège, and translated research into applied ML through internships and collaborations with domain scientists. His PhD work centers on simulation-based inference, giving him strong probabilistic modeling skills alongside practical deep learning expertise that enable rapid adaptation to new domains. At CluePoints he now applies this research-driven mindset to production ML problems, while maintaining an active portfolio of teaching-focused and open-source contributions such as implementing belief-state agents for an AI course project. Colleagues value his blend of rigorous research training, hands-on engineering, and clear communication with non-ML experts.
7 years of coding experience
Doctor of Philosophy - PhD, Machine learning, Doctor of Philosophy - PhD, Machine learning at University of LiègeMaster of Data science and Engineering, Magna Cum Laude, Master of Data science and Engineering, Magna Cum Laude at Université de Liège
French, English, Dutch
Github Skills (10)
machine-learning10
ai-agent10
python10
pacman10
data-structure9
algorithm9
data-structures9
algorithms9
numpy8
scipy7
Programming languages (2)
Github contributions (5)
glouppe/info8006-introduction-to-ai
Sep 2020 - Oct 2022
Lectures for INFO8006 Introduction to Artificial Intelligence, ULiège
Role in this project:
ML Engineer
ML EngineerContributions:42 commits, 27 PRs, 33 pushes in 2 years 1 month
Contributions summary:Arnaud primarily worked on the implementation and modification of a belief state agent within the context of an AI project. Their contributions involved updating the evidence function, incorporating ghost eaten parameters, and adding functionality for comparing agent behavior against an oracle. Further modifications included correcting a prior in the pacman module and integrating the agent with the game environment.
deep-learningartificialmachine-learningulinatural-language-processing
ADelau/proj0016-epidemic-data
Oct 2020 - Feb 2021
Contributions:88 commits, 6 PRs, 84 pushes in 4 months
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