Team members

Permanent researchers (PIs)

• Gaël Varoquaux (team leader), Research Director
• Marine Le Morvan, Research Scientist (chargée de recherche)
• Jill-Jênn Vie, Research Scientist (chargé de recherche)
• Judith Abécassis, Research Scientist (ISFP)

Senior research members

• Léa Hoisnard (APHP)

Junior research members

Students

• Félix Lefebvre – PhD Student. Working on large-scale graph-embedding methods to represent large relational stores.
• Samuel Girard – PhD Student. Reinforcement learning in education.
• Julie Alberge – PhD Student. Modeling trajectories of diabetic patients from AP-HP.
• Jovan Stojanovic – PhD Student. Targeting Strategies in Political Networks: machine-learning insights on Twitter data.
• Marie Generali – Fairness in educational data mining
• Sébastien Melo – Grouping losses
• Célestin Eve

Post-docs

• Riccardo Cappuzzo – Post-doc, working on assembling features across relational databases
• Jun Kim – Post-doc, working on graph neural networks for relational databases
• Lihu Chen – Natural Language Processing and Large Language Models
• Jingang Qu – Tabular foundation models
• David Holzmüller – Tabular machine learning 

Engineers

• Jérôme Dockès – Research software engineer. Working on skrub
• Hiba Bederina – Research engineer. Working with Pass Culture

Interns

• Anav Agrawal

Collaborators

• Linus Bleistein
• Julie Josse
• Clémence Réda
• Jean Vassoyan

Research Team Assistant

• Ekaterina “Katia” George

Alumni

• Samuel Brasil de Alburquerque – Working on diabetes epidemiology from observational health informatics.
• Alexis Cvetkov-Iliev – Working on statistical analysis across relational databases with embeddings.
• Bénédicte Colnet – Working on causal inference, with a focus on assessing randomized controlled trials’ external validity.
• Julien Jerphanion – Research software engineer. Core developer to scikit-learn since 2021.
• Lilian Boulard – Software engineering apprentice. Working on skrub.
• Matthieu Doutreligne – Working on transfer learning and causal inference for public health, in partnership with HAS.
• Tomas Rigaux – Research engineer. Working on recommendations for the job market.
• Léo Grinsztajn – PhD Student. Working on neural networks for tabular and relational data.
• Alexandre Perez – PhD Student. Working on supervised learning in the presence of missing values and assessment of classification confidences through calibration and grouping loss.
• Clémence Réda – Marie Skłodowska-Curie post-doc on project Robust Explainable Controllable Standard for drug Screening (RECeSS), now at CNRS

Scikit-learn team

Soda hosted the core scikit-learn development team up to 2024.

• Arturo Amor-Quiroz – Research software engineer and PhD in physics. Focused on the scikit-learn documentation.
• Jérémie du Boisberranger – Research software engineer and physicist. Core developer to scikit-learn since 2019.
• Franck Charras – Research software engineer. Working on a GPU programming project, within a partnership with Intel®.
• Vincent Maladière – Research software engineer, focusing on data wrangling, survival analysis, and MLOps. Working on scikit-learn, skrub, and hazardous. Collaboration on health data with AP-HP.
• Loïc Estève – Research software engineer and physicist. Core developer to scikit-learn since 2016.
• Olivier Grisel – Research software engineer. Core developer to scikit-learn since 2010.
• François Goupil – Research software engineer.  Animates our community, manages the operations of the consortium and the relationship with our patrons
• Guillaume Lemaître – Research software engineer. Core developer to scikit-learn since 2017.