Jovan Stojanovic
PhD Student - Soda Team at Inria
Paris, Ile-de-France
Summary
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Rockstar🎓
Top SchoolJovan Stojanovic is a PhD candidate at Inria’s Soda team with six years of experience at the intersection of econometrics, political economy and machine learning. He maintains the Python open-source library skrub, contributing practical data-preprocessing tools like GapEncoder enhancements and robust tests that help prepare tabular data for ML workflows. Previously a data scientist and software engineer at Inria and a statistical editor at the OECD, he blends rigorous academic training (Université Paris-Saclay, Paris School of Economics, Panthéon-Sorbonne) with hands-on engineering. Based in Paris, he also teaches causal inference and brings a pragmatic attention to reproducibility and documentation often missing in research code.
6 years of coding experience
Magistère d'économie, Magistère d'économie at Paris School of EconomicsMaster's degree Econometrics and Statistics, Master's degree Econometrics and Statistics at University of Paris I: Panthéon-SorbonnePhD Candidate, PhD Candidate at Université Paris-Saclay
French, Serbian, English
Github Skills (11)
scikit10
data-preprocessing10
data-analysis10
data-wrangling10
machine-learning10
dataprep10
data-cleaning10
python10
data-science10
scikit-learn10
testing9
Programming languages (2)
Github contributions (5)
skrub-data/skrub
Mar 2022 - Jan 2023
Prepping tables for machine learning
Role in this project:
Data Scientist
Data ScientistContributions:2 releases, 305 reviews, 61 commits in 10 months
Contributions summary:Jovan primarily focused on enhancing the `skrub` library, a tool for prepping tables for machine learning. Their contributions include correcting typos and fixing links in documentation, as well as adding and testing functionalities. A significant portion of the work involved modifying the `GapEncoder`, including adding tests and correcting options, indicating an involvement in the development and testing of data preprocessing tools. They also contributed to examples, illustrating the use of the library.
autoencoderdata-preprocessingdatadata-sciencetabular-data
jovan-stojanovic/Animal-sound-recognition
Sep 2021 - Jan 2023
Contributions:6 commits, 9 pushes, 1 branch in 1 year 4 months
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