Data Intelligence Institute of Paris

The Data Intelligence Institute of Paris (diiP) is an interdisciplinary initiative of Université Paris Cité. It is a laboratory that fosters and supports the emergence of interdisciplinary practices around data science and data intelligence. It gathers researchers from formal sciences, physical sciences, life sciences and social sciences.

“The mission of diiP is to foster a new wave of scientific discoveries by enabling scientists and practitioners to make sense of their large and complex data, and achieve breakthroughs that would not otherwise be possible.”

Prof. Themis Palpanas

Director of diiP

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diiP Projects

PhD Scholarships

 

Several PhD Scholarships (supported by the ANR Data Intensive Artificial Intelligence -DIAI- project) will be offered by diiP (starting on academic year 2021-2022) for students working on interdisciplnary projects on topics related to data intensive artificial intelligence.

Strategic projects

 

The diiP institute will host and partly finance a small number of interdisciplinary Strategic Projects, of duration up to 12 months each, with the goal to contribute to both the analysis and implementation aspects.

Master’s Internships

 

The diiP institute will organize and finance several six-month Masters students Internship Projects on data science, in connection to interdisciplinary collaborations.

Digital Pathology: when AI meets with anatomo-pathology

2021Masters Projects@Computer Science +Mathematics/Statistics+Engineering+Medicine #Digital Pathology#Computer Vision#Deep Learning#Immuno-therapy  Project SummaryThe fundamental question we address is: How to predict immunotherapy-related gene classes of tumor just...

Malvasia – MAchine Learning to VAlue Single Interferometer Analysis

2021Masters Projects@Physics and Astronomy +Computer Science+Mathematics/Statistics+Physics/Astronomy #gravitational wave#deep learning  Project SummaryThe direct observation of gravitational waves (GW) by the LIGO and Virgo detectors is one of the breakthrough...

PhD scholarships on Data Intensive Artificial Intelligence (DIAI), 2021

Data Intelligence Institute of Paris (diiP)PhD Scholarships on Data Intensive Artificial Intelligence Presentation of the DIAI projectExtracting knowledge from the data means that we need to perform analysis tasks that are becoming increasingly...

Transcriptomic Analysis using Intensive Randomization

2022Masters Projects@Computer Science +Mathematics/Statistics+Biology #Big data#RNA-seq#computational optimization#GPU parallelization#differential analysis Project SummaryNext-generation sequencing such as RNA-seq aims to quantify the transcriptome of biological...

Automatic production of environmental indicators from freely available remote sensing data: from a global to a local scale

2021Masters Projects@Computer Science +Earth Sciences/Geosciences+Demography #Remote sensing#Deep learning#Sentinel 2#Local climate zones#Africa Project SummaryThis collaborative project aims at studying the feasibility of automatically producing repeatable indicators...

Compact representations to detect gravitational waves from extreme-mass ratio inspirals

2024 Master's Projects@Physics/Astronomy #Gravitational waves#extreme-mass ratio inspirals#data representations#neural networks  Project Summary Extreme Mass Ratio Inspirals (EMRIs), detectable only by the future space-based detector LISA, provide a unique opportunity...

Semantic coherence integration for optimizing imaging retrieval systems in radiology

2023Strategic Projects@Computer Science +Medicine #medical imaging#computer vision#content-based image retrieval#deep learning#feature extraction#metric or ranking learning  Project Summaryto be updated. Florence Cloppet Projects in the same discipline

Deep Mendelian Randomization: explaining causality between different hereditary traits at genome-wide scale

2024 Master's Projects@Mathematics/Statistics #Mendelian Randomization#Deep Learning#Double Machine Learning#Genomics#Pleiotropy  Project Summary Mendelian Randomization is a method that infers the causality between risk factors and diseases using genetic variants as...

Automated segmentation and clustering of spICP-ToF-MS time series

2024 Strategic Projects@Earth Sciences/Geosciences #nanoparticles#spICP-ToF-MS#clustering#segmentation  Project Summary The detection and characterization of inorganic nanoparticles (NPs) in natural matrices has relied primarily on single-particle ICP-MS (spICP-MS)....

Dark energy studies with the Vera Rubin observatory LSST & Euclid-developing a combined cosmic shear analysis with bayesian neural networks

2021PhD/ DIAI Projects@ED 560 : Sciences de la Terre et de l’Environnement et Physique de l’Univers de Paris (STEP'UP) PhD studentJustine ZEGHAL (AstroParticule & Cosmologie, UPC) SupervisorsEric AUBOURG (APC, UPCAlexandre BOUCAUD (APC, UPC)Cécile ROUCELLE (APC,...