The DirtyData team is multi-disciplinary. Composed of mathematicians, computer scientists, software engineers, and industry data scientists.
Partners
- INRIA, parietal team
- Polytechnique, CMAP
- Data Publica
- Laboratoire de l’accélerateur linéaire, AppStat group
- Télécom ParisTech Institut Mines-Télécom – Data, Intelligence and Graphs group
Senior members
- Gael Varoquaux – INRIA, research director, PI of the DirtyData project
- Marine Le Morvan – INRIA, tenured researcher. Working on supervised learning with missing values.
- Julie Josse – INRIA Montpellier, senior researcher
- Erwan Scornet – CMAP, researcher
- Fabian Suchanek – Télécom Paritech, professor
- Clément Chastagnol – Sidetrade, head of data science
Junior members
- Bénédicte Colnet – INRIA, PhD student. Working on causal inference.
- Matthieu Doutreligne – INRIA-HAS, PhD student. Working on transfer learning for public health.
- Alexis Cvetkov-Iliev – INRIA, PhD student. Working on statistical analysis across relational databases with embeddings.
- Leo Grinsztajn – INRIA, PhD Student. Working on neural networks for tabular and relational data
- Alexandre Perez – INRIA, PhD Student. Working on neural networks for classification in the presence of missing values.
- Lilian Boulard – INRIA, software engineering apprentice. Working on dirty_cat.
Former members
- Nicolas Prost – INRIA/CMAP, PhD student
- Patricio Cerda – INRIA, PhD student
- Maxime Cuny – INRIA, developer intern
- Balázs Kégl – CNRS, senior researcher (on leave at Huawei Data Science)
Associated teams
Many in the DirtyData project share offices and work culture with the Parietal research group, and the scikit-learn consortium @ Inria.
