diiP Projects
From 2021, the Data Intelligence Institute of Paris (diiP) selected 74 interdisciplinary projects using data science and machine learning.
Cosmologie – amas de galaxies – intelligence artificielle
Nicolas Cerardi ➔
Exploration intelligente de lames histologiques.
Zhuxian Guo ➔
Prediction of demographic indicators from remote sensing images
Basile Rousse ➔
Dark energy studies with the Vera Rubin observatory LSST & Euclid-developing a combined cosmic shear analysis with bayesian neural networks
Justine Zeghal ➔
Statistical and machine learning methods for survival data: prediction, performance assessment and interpretability
Ariane Cwiling ➔
Design principles of property graph languages
Alexandra Rogova ➔
Leveraging multivariate geophysical and geochemical time series for monitoring volcanic systems: can we use machine learning?
Matthieu Nougaret ➔
Learning the magneto-ionic side of the turbulence in the interstellar medium in radio-astronomy
Jack Berat ➔
Metamorphoses and optimal transport for the multimodal registration of brain tumor images
Guillaume Serieys ➔
Deeply Learning from Neutrino Interactions with the KM3NeT neutrino telescope
Santiago Pena Martinez ➔
Digital Pathology: when AI meets with anatomo-pathology
Nicolas Loménie ➔
PARKER — Planetary lidAR seeKing for lifE signatuRe
Antoine Lucas ➔
Autoimmunity/inflammation Through RNAseq Analysis at the single Cell level for Therapeutic Innovation – ATRACTion
Mickaël Ménager ➔
Inferring cultural transmission of reproductive success through machine learning methods
Frédéric Austerlitz ➔
Large image time series analysis for updating vineyard geographic databases
Camille Kurtz ➔
Smoothing of incomplete air pollution regions of interest from satellite observations
Laurent Wendling ➔
Combining visual and textual informations for enhancing image retrieval systems in radiological practices
Florence Cloppet ➔
Automatic production of environmental indicators from freely available remote sensing data: from a global to a local scale
Sylvain Lobry ➔
Digital Pathology: when AI meets with anatomo-pathology
Nicolas Loménie ➔
Machine learning model of volcanic lava properties helps understanding the dynamics of volcanic eruptions
Charles Le Losq ➔
ComplexNeuroViz: Complexity Visualisation for Neural Machine Translation
Nicolas Ballier ➔
Machine learning for the study of EEG data recorded during general anesthesia
Laurent Oudre ➔
Influence of blood pressure and aqueous humor dynamics on the response to glaucoma medication: a data-driven computational study
Marcela Szopos ➔
Machine Learning techniques applied to eye movement analysis for early screening of learning disorders in young children
Zoï Kapoula ➔
Artificial Intelligence for source deblending in the next generation of astrophysical big data imaging surveys – Combining Euclid and LSST
Marc Huertas-Company ➔
Malvasia – MAchine Learning to VAlue Single Interferometer Analysis
Agata Trovato ➔
Study the ability of teenagers to spot fakes news over their usage time on the social networks
Salima Benbernou ➔
Language-Independent Massive Network Attitudinal Embedding
Pedro Ramaciotti Morales ➔
Learning from deep sea light with KM3NeT
Joao Coelho ➔
Optimization of a physical force-field for simulations of non-coding RNA molecules
Samuela Pasquali ➔
The diffusion of technology during the last five millennia
Johannes Boehm ➔
Monitoring the seismic activity of Mayotte through image processing of fiber optic signals
Lise Retailleau ➔
Automatic detection and location of hydro-acoustic signals linked to Mayotte submarine eruption
Jean-Marie Saurel ➔
Investigating regulatory B cell differentiation and their therapeutic effect in neuroinflammatory disease through single cell analyses and computational biology
Simon Fillatreau ➔
Transcriptomic Analysis using Intensive Randomization
Dorota Desaulle ➔
Random projections for the reduction of gravitational wave template banks
Eric Chassande-Mottin ➔
“Search for features in astrophysical objects close to cosmic neutrinos”. An indirect approach to cosmic neutrino association with astrophysical objects
Yvonne Becherini ➔
Multiple imputation for heterogeneous biological data
Matthieu Resche-Rigon➔
Tracking auto-immune diseases in electronic health record
Maud De Dieuleveult ➔
Modeling genetic pleiotropy using machine learning to understand the human genetic architecture
Marie Verbanck ➔
Veracity assessment framework for discovering social activities in urban big datasets
Soror Sahri ➔
Combining visual and textual information for enhancing pathologic case retrieval systems in radiological practices
Florence Cloppet ➔
Deep Learning-based EEG Epilepsy Detection and Analysis
Jerome Cartailler ➔
Multimodal assessment of the depth of sedation of severely ill patients in intensive care unit
Laurent Oudre ➔
Semantic coherence integration for optimizing imaging retrieval systems in radiology
Florence Cloppet
Deep Learning-based EEG Epilepsy Detection and Analysis
Qitong Wang ➔
OpenStreetMap and Sentinel-2 data for the production of environmental indices for demographic studies
Sylvain Lobry ➔
Mining molecular dynamics open data
Pierre Poulain ➔
Prediction of protein-carbohydrate binding sites using deep learning methods
Tatiana Galochkina ➔
Enhancing earthquake location with domain adapation
Leonard Seydoux ➔
Exploration of press articles related to Covid-19 at the European level within the Covid-19 Museum
Yves Rozenholc ➔
Machine Learning for Photometric redshift estimation of LSST galaxies
Simona Mei ➔
Deep learning to model genetic pleiotropy to understand the human genetic architecture
Marie Verbanck ➔
Generalization of a method enabling to update vineyard geographic databases from satellite data
Camille Kurtz ➔
Diffusion Models Based Unpaired Image-to-Image Translation to Reveal Subtle Phenotypes
Valérie Mezger ➔
Diffusion Models Based Visual Counterfactual Explanations
Valerie Mezger ➔
EStimation of Pollutant Emissions from REmote sensing data and deep Learning (ESPEREL)
Gaëlle Dufour ➔
A Simulated body approach to MRI-based fetal monitoring
Jean-Baptiste Masson ➔
Accelerate Discoveries (boosting) Astroparticle Physics (analysis) Techniques – ADAPT
Yvonne Becherini ➔
Maintaining fairness for decision-making under social considerations
Soror Sahri ➔
Quantifying the interaction between grammatical gender and social gender roles at a worldwide scale
Marc Allassonnière-Tang ➔
Deep learning-based prediction of protein-carbohydrate interactions
Tatiana Galochkina ➔
Automated segmentation and clustering of spICP-ToF-MS time series
Mickael Tharaud ➔
DNA methylation in patients: A new meta-analysis of EPIC data across borders
Maud De Dieuleveult ➔
Identification of image circulation by AI in large collections of historical photographs
Daniel Foliard ➔
Deep learning for estimating gas concentration maps from satellite or airborne hyperspectral images
Andrés Almansa ➔
Blind Image Deblurring via Latent Diffusion Models
Andrés Almansa ➔
Investigating Diffusion Models for Astronomical Image Deconvolution – boosting the synergy between Euclid and LSST
Alexandre Boucaud ➔
Biomarker prediction from images of histological slides of cancerous tissues
using modern AI techniques: comparisons of different neural architectures
Nicolas Loménie ➔
Compact representations to detect gravitational waves from extreme-mass ratio inspirals
Quentin Baghi ➔
Towards design of protein knottin using deep learning
Jean-Christophe Gelly ➔
Exploring the similarities of a large bank of protein pockets in a perspective of
multiple protein-ligand interactions prediction
Anne-Claude Camproux ➔
Deep Mendelian Randomization: explaining causality between different hereditary traits at genome-wide scale
Marie Verbanck ➔
Modeling conditioned place preference test for evaluation of addictiveness of substances: toward experimental design optimization & smart data analysis
Emmanuel Curis ➔