Fabrice Rossi
Professor at Université Paris Dauphine
France
Summary
👤
Senior🎓
Top SchoolFabrice Rossi is a professor and machine learning researcher with 12+ years of experience applying and teaching statistical learning, neural networks and support vector machines across both theoretical and real-world problems. He has a long academic trajectory at top French institutions (Dauphine, Paris 1, Télécom ParisTech) and a PhD in applied mathematics, combining rigorous research with practical high-performance Java development. His work spans spectrometric calibration to social network analysis, and he has advised industry on deploying ML solutions. An experienced back-end contributor to the Syncany open-source cloud storage project, he has hands-on experience improving CLI tooling and database efficiency—showing attention to production robustness as well as theory. He is fluent in R, Java and Linux and is particularly strong in feature selection, clustering and scalable implementations of learning algorithms.
12 years of coding experience
15 years of employment as a software developer
Ecole normale supérieureLycée Louis Le GrandHabilitation à diriger des recherches, Applied mathematics, Computer science, Habilitation à diriger des recherches, Applied mathematics, Computer science at Université Paris Dauphine - PSL
French, English
Github Skills (10)
javas10
java10
command-line9
cli9
database-design9
command-line-interface9
filesystem8
xml8
data-structures8
data-structure8
Programming languages (2)
Github contributions (5)
syncany/syncany
Nov 2013 - Dec 2013
Syncany is a cloud storage and filesharing application with a focus on security and abstraction of storage.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:16 commits in 23 days
Contributions summary:Fabrice primarily contributed to the back-end aspects of the Syncany project. Their work involved modifying the command-line interface (CLI) for the `log` command by adding new output formats and refining existing ones. The user also made changes to the database interaction, fixing a bug related to file size and migrating to a byte-based file ID storage for improved efficiency and reduced collision risk. These changes reflect their involvement in enhancing core functionalities and improving the underlying data handling.
filesharingsecuritycloudcloud-storagestorage
fabrice-rossi/mixvlmc
Mar 2023 - May 2024
Variable Length Markov Chains with Covariates
Contributions:2 releases, 8 reviews, 30 PRs in 1 year 1 month
machine-learningmarkov-chainmarkov-modelrstatistics
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