BRIANCEAU Camille

ICM Institute

camille.brianceau [at] icm-institute.org

Short bio

Master degree (Diplôme d’ingénieur) at Institut d’Informatique d’Auvergne (ISIMA)

Master degree in imaging and technology for medicine (Université Clermont Auvergne)

Research project

ClinicaDL

Short abstract

ClinicaDL is an open-source software for deep learning processing on neuro-imaging data. My works consists in extending this software with new features and standard deep learning tools of the community, and providing PhD students and researchers with support.

VAILLANT Ghislain

Research Software Engineer

Université Paris Dauphine-PSL

ghislain.vaillant [at] icm-institute.org

Short bio

PhD, King’s College London

Research project

Clinica

Short abstract

Clinica is the software platform for clinical neuroimaging studies involving processing of multimodal data (imaging and phenotypic) for patients with cognitive diseases. My work consists in extending this platform to provide its functionalities as a service in the Cloud in order to serve a wider scientific audience.

WALLEZ Théophile

Research Engineer

INRIA

theophile.wallez [at] inria.fr

Short bio

Master of Computer Science, ENS Ulm

Research project

A verification framework for privacy-preserving machine learning

Short abstract

Machine learning is known to be hungry for data, which is often private. Recent advances in privacy-preserving machine learning use new cryptographic techniques to avoid exposing private data. However, such cryptographic implementations are error-prone, resulting in information leakage. Therefore, I use the F* software verifier to implement modern multiparty computation protocols, such as SPDZ2k.

RIABI Arij

Research Engineer

INRIA

arij.riabi [at] inria.fr

Short bio

Master,  Sorbonne University

Research project

NLP for low-resource, non-standardised language varieties, especially North-African dialectal Arabic written in Latin script.

Short abstract

DI FOLCO Cécile

Research Engineer

ICM Institute

cecile.difolco [at] icm-institute.org

Short bio

Engineer diploma (AGROPARISTECH)

Master of Data science («INFORMATIQUE: SYSTEME INTELLIGENTS»-UNIVERSITE PARIS-DAUPHINE)

Master of Cognitive Sciences (ENS, UNIVERSITE DE PARIS, EHESS)

Research project

Modelling neurodegenerative diseases.

Short abstract

I study the modeling of neurodegenerative diseases’ progression using imaging and clinical data. In particular, I investigate the influence of various cofactors, including genetics, on Parkison’s Disease progression.

YGER Florian

Machine learning

florian.yger [at] dauphine.fr

Florian Yger

Short bio

Associate professor at Université Paris-Dauphine since 2015. JSPS fellow in the laboratory of Pr. Sugiyama (from 2014 to 2015) and visiting researcher, RIKEN AIP (summer 2017-).

Topics of interest

Trustworthy machine learning, Causal inference, interpretable AI

Project in Prairie

Florian Yger will address the questions of trust, explainability and interpretability in machine learning models (including deep learning) with a focus on the robustness to adversarial examples and counterfactual reasoning on data. This project has natural and practical applications in the medical field.

Quote

In the last decade, deep learning has made possible breakthrouhgts in several domains (e.g. computer vision, machine translation, games, …). Yet those hardly interpretable algorithms are fed with huge amounts of -sometimes sensitive- data and can suffer from malicious attacks: attacks on the privacy of the data and attacks on the robustness where adversarial examples are generated to fool the algorithm. This is a critical issue (especially in medical applications) and we feel that an effort toward a deeper theoretical analysis is needed.