Dataia

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Awarded the Institut DataIA Paris-Saclay label, this new research chair in health brings together the expertise of CentraleSupélec and Servier to develop new therapeutic approaches and contribute to advances in precision medicine.

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Putting mathematics and artificial intelligence at the service of healthArtificial intelligence and applied mathematics are opening up new prospects f

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Research

On Friday, November 7th, 2025, Institut DataIA Paris-Saclay had the pleasure of hosting the DeMythif.AI Welcome Day, marking the arrival of the new PhD fellows of the DeMythif.AI COFUND program at Université Paris-Saclay.

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Organised by Arnaud Maury, Project Manager of DeMythif.AI, the event offered a comprehensive introduction to the Horizon Europe MSCA COFUND program an, Learn more about DeMythif.AI COFUND

Program, 09:15am - Welcome Coffee10am - Presentation of DataIA Institute, by Demian Wassermann (Deputy Director for Research)10:15am - Presentation of the COFU

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The COFUND DeMythif.AI project, selected by the European Commission and led by the DATAIA Institute for the Paris-Saclay University, is pleased to announce the success of the 2023 call. This funding will enable 14 new theses to be co-financed for the start of the 2024 academic year and prepare the new call in September-October 2024.

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Call contextBy the start of the 2024 academic year, the COFUND DeMythif.AI project will fund 14 theses on the theme of "AI and uncertainties": control, Contact, 0, Learn more

5 Doctoral Schools involved, - Ecole Doctorale de Mathématiques Hadamard (EDMH)- INTERFACES- Particules Hadrons Energie et Noyau : Instrumentation, Image, Cosmos et Simulation (PH

11 laboratories represented, - Centre Borelli- Centre de Vision Numérique, CentraleSupélec (CVN)- Centre Inria de Saclay- Département de Physique des Particules, DRF/IRFU (DPhP)-

9 nationalities represented, - Algeria- China- Colombia- Germany- Italy- Lebanon- Spain- Ukraine- Uruguay

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Innovation

A language model (LLM: Large Language Model) has been developed by the MICS laboratory and Illuin Technology.

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Named "Croissant LLM", the main features of this model are:- Sovereign: trained on the Jean Zay calculator with open data- Accountable: fully sourced , Read the paper (ARXIV)

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Focus on the launch of Tower, a multilingual 7B parameter large language model (LLM) optimized for translation-related tasks, developed in part by Nuno Guerreiro and Pierre Colombo at CentraleSupélec's MICS laboratory.

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We are thrilled to announce the release of Tower, a multilingual 7B parameter large language model (LLM) optimized for translation-related tasks. Towe, Learn more

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NeuroLang, a language to better question brain activity

Developed at the Inria center in Saclay, NeuroLang is a query language specific to the neurosciences. It helps researchers and clinicians to formalize their questions in order to analyze functional neuroimaging data more efficiently. These data often require a highly mathematical formulation before revealing their secrets.

©MIND - Read figure legend at bottom of article

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86 billion neurons. 150,000 billion synapses. 180,000 kilometers of nerve fibers. And information circulating at over 400 kilometers/hour. The human b

MIND develops methods for exploiting neuroimaging data, Created in September 2023, MIND is a joint Inria project-team with CEA and Université Paris-Saclay. It is the partial successor to the former Parietal

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Research

For several years, and in particular since July 2021 within the DATAIA institute, the Paris-Saclay Center for Data Science has been organizing data science challenges for students and researchers on the Saclay plateau. Here is a look at the latest collaborations.

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Implemented by the Paris-Saclay Center for Data Science (CDS) and co-organized with the DATAIA Institute, these various machine learning challenges ar

Challenge 1 | Prediction of the isotopic inventory in a nuclear reactor core, This challenge, organized in August 2021, was carried out with the support of DATAIA Institute, in collaboration with the Institut de Radioprotection

Challenge 2 | Detection and classification of ovarian follicles, This challenge was realized with the support of DATAIA Institute, in collaboration with INRIA, CNRS, INSERM and INRAE.

Challenge 3 | Predict age from brain grey matter (regression), This challenge was realized with the support of DATAIA Institute, in collaboration with CEA NeuroSpin. This challenge gathered 31 participants and 33

Challenge 4 | Brain age regression with deep learning, This challenge was realized with the support of DATAIA Institute, in collaboration with CEA NeuroSpin. Edouard Duchesnay, Antoine Grigis (Universit

Challenge 5 | ATLAS Stroke Lesion Segmentation, This challenge was realized with the support of DATAIA Institute, in collaboration with University of Southern California (USC).

Challenge 6 | Brain age prediction and debiasing with site-effect removal in MRI through representation learning, This challenge was realized with the support of DATAIA Institute, in collaboration with CEA NeuroSpin. Antoine Grigis, Benoît Dufumier, Edouard Duc

Challenge 7 | Bovine embryos survival prediction, This challenge was realized with the support of DATAIA Institute, in collaboration with the Institut National de Recherche pour l'Ag

CDS@DATAIA, 0

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STREAMER, a software platform for machine learning for data streams

As part of the StreamOps project, funded by the DATAIA Institute in 2018, the open source software STREAMER was created: the first search and integration platform for retrieving, manipulating and analysing streamed data in realistic streaming operational contexts.

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The researchers from CEA List (Université Paris-Saclay, CEA) and the DAVID laboratory (Université Paris-Saclay, UVSQ) working on the StreamOps projec, Read the full article

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Matthieu Nastorg and Tamon Nakano join the ML4CFD team, the research project co-funded by DATAIA, which applies machine learning to computational fluid dynamics simulation.

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Within the scope of the collaborative project IFPEN-Inria "Machine Learning for Computational Fluid Dynamics" (ML4CFD), a PhD student and a post-doc w

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The ML4CFD project, The ML4CFD project, winner of the call for research projects DATAIA 2020, is the result of a long collaboration between the Inria team TAU and IFPEN.T

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The HistorIA project, selected at the call for research projects launched in 2018 by the DATAIA Institute, will present two papers and a challenge at the conference IEEE VIS 2020.

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The IEEE VIS conference, the most important international conference in the field of visualization, will take place virtually from the 25th to the 30t

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Le projet « HistorIA », Directed by Jean-Daniel Fekete (Inria) and Christophe Prieur (Télécom Paris), the HistorIA project aims to develop large historical databases by apply

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