Paul Roujansky
Applied AI Engineer at Mistral AI
Paris, Ile-de-France
Summary
👤
Senior🎓
Top SchoolPaul Roujansky is an Applied AI Engineer based in Paris with nine years of hands-on experience building ML and MLE systems for medical and neuroscience applications. He has led data science and ML engineering teams at BioSerenity and Zoī, designing cloud platforms and a company-wide medical ontology to productionize physiological AI workflows. His background spans research-grade BCI work at ENS and NextMind to enterprise-grade AWS/GCP architectures, bringing both algorithmic depth and production rigor. An active contributor to the mne-python project, he has improved EDF file handling and annotation integrity for a widely used EEG/MEG library—reflecting a practical focus on data fidelity. Earlier experience in quantitative trading and actuarial studies gives him a strong foundation in probabilistic modeling and high-stakes production impact.
9 years of coding experience
8 years of employment as a software developer
Licence Économie-gestion, Licence Économie-gestion at Université Jean Monnet Saint-EtienneEngineer's degree Ingénieur Civil des Mines Engineering Applied Mathematics Statistics Industrial Management IT, Engineer's degree Ingénieur Civil des Mines Engineering Applied Mathematics Statistics Industrial Management IT at École des Mines de Saint-ÉtienneMaster 2 (M2) Data Sciences - Machine Learning Big Data Computing & Analytics, Master 2 (M2) Data Sciences - Machine Learning Big Data Computing & Analytics at Université Paris-SaclayActuarial Mathematics Finance, Actuarial Mathematics Finance at Institut de Science Financière et d'Assurances (I.S.F.A)BAC+2 Classes préparatoires scientifiques (MPSI - MP*), BAC+2 Classes préparatoires scientifiques (MPSI - MP*) at Lycée KleberEngineer's degree Ingénieur Statisticien-Économiste Economics Statistics and Financial Mathematics, Engineer's degree Ingénieur Statisticien-Économiste Economics Statistics and Financial Mathematics at ENSAE Paris
Github Skills (15)
file-handling10
megaparsec10
python10
annotate10
annotations10
testing9
neuroscience9
el8
ec8
ceph8
n8
visualizations5
visualization5
statistics5
machine-learning4
Programming languages (1)
Github contributions (5)
mne-tools/mne-python
Jun 2019 - Jun 2019
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:12 reviews, 1 commit, 5 PRs in 1 day
Contributions summary:Paul primarily contributed to the `mne-python` repository by implementing features related to EDF file handling, particularly focusing on annotations and subject information. They addressed bugs in how subject information is loaded from and exported to EDF files, including handling channel-specific information. Furthermore, the user implemented changes to the handling of annotations and resolved an issue related to channel information for missing channels. These changes involved modifications across multiple files, demonstrating a focus on core functionality and data integrity related to the reading, processing, and exporting of EEG/MEG data.
visualizationneuroimagingneurosciencepythonstatistics
paulroujansky/mne-python
Jun 2019 - Oct 2023
MNE : Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Contributions:48 pushes, 7 branches in 4 years 3 months
pythonelectroencephalographymneeegmagnetoencephalography
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.