Constantin Philippenko
Data & Machine Learning Scientist
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolConstantin Philippenko is a Data & Machine Learning Scientist and postdoctoral researcher based in Paris with nine years of experience bridging applied mathematics, optimization, and federated learning. He completed a PhD at École Polytechnique where he developed bidirectional compression methods to reduce communication costs in heterogeneous federated settings, contributing papers to NeurIPS and JMLR-adjacent venues. His research at Inria delivered practical tools and benchmarks—such as contributions to the FLamby cross-silo federated learning suite—and produced open-source repositories on matrix factorization and heterogeneity quantification. At AFP he applies research-grade ML to production data pipelines and ensures AI solutions meet regulatory and editorial constraints. Beyond academia and industry, he founded Phantasio to promote arts and culture, revealing a rare mix of rigorous quantitative expertise and creative leadership. Constantly blending theory with implementation, he codes in Python/PyTorch and focuses on turning mathematical insights into deployable, privacy-aware distributed learning systems.
9 years of coding experience
6 years of employment as a software developer
MP, Theoretical and Mathematical Physics, MP, Theoretical and Mathematical Physics at Lycée Saint LouisThèse de doctorat, Mathématiques Appliquées et Informatique, Thèse de doctorat, Mathématiques Appliquées et Informatique at École PolytechniqueDiplôme d'ingénieur, Applied Mathematics, Diplôme d'ingénieur, Applied Mathematics at Ecole Nationale Supérieure d'Informatique et de Mathématiques Appliquées de GrenobleMaster's degree, Mathematics and Computer Science, Master's degree, Mathematics and Computer Science at Московский Физико-Технический Институт (Государственный Университет) (МФТИ)
French, English, Russian, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (29)
convergence10
bidirectional10
artemis9
compression8
leaderboard8
federated-learning8
distributed-computing8
silo8
office3657
machine-learning7
differential-privacy7
data-privacy7
federated7
python7
powerbi6
Programming languages (4)
Github contributions (5)
philipco/structured_noise
Jan 2022 - Oct 2023
Contributions:29 PRs, 107 pushes, 17 branches in 1 year 9 months
philipco/artemis-bidirectional-compression
Jun 2020 - Feb 2022
Artemis: fast convergence guarantees for bidirectional compression in Federated Learning
Contributions:295 commits, 51 PRs, 271 pushes in 1 year 9 months
artemiscompressionmachine-learningdistributed-computingconvergence
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