Egor Dudyrev is a PhD candidate and Temporary Teaching Assistant based in Nancy, France, with a decade of experience bridging applied data science and symbolic AI. His research focuses on integrating Formal Concept Analysis with Explainable AI, while he teaches algorithms, databases and system requirements at TÉLÉCOM Nancy and delivers courses on Symbolic AI and data mining. He has industry experience building and optimizing rule-based ML models and pipelines for retail analytics, and has published research from roles at HSE and Loria. Comfortable working in both French and English, Egor combines hands-on data engineering with formal methods to make black-box models auditable and rule-centric explanations practical for real systems.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Universite de Lorraine
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Higher School of Economics
Contributions:2 releases, 27 reviews, 78 PRs in 2 years
python
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