M1 - M2 Internship In Computer Science - Artificial Intelligence - Machine Learning M - F H/F - 95

Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat.

Il apporte des solutions concrètes à leurs besoins dans quatre domaines principaux : transition énergétique, transition numérique, technologies pour la médecine du futur, défense et sécurité sur un socle de recherche fondamentale. Le CEA s'engage depuis plus de 75 ans au service de la souveraineté scientifique, technologique et industrielle de la France et de l'Europe pour un présent et un avenir mieux maîtrisés et plus sûrs.

Implanté au coeur des territoires équipés de très grandes infrastructures de recherche, le CEA dispose d'un large éventail de partenaires académiques et industriels en France, en Europe et à l'international.

Les 20 000 collaboratrices et collaborateurs du CEA partagent trois valeurs fondamentales :

- La conscience des responsabilités
- La coopération
- La curiositéThis internship is designed for Master 1 students (duration 3 to 4 months), but can be extended (duration 6 months) for Master 2 students.
The main objective of this internship is to introduce the notion of Hierarchical Classification in CAISAR, and use it to verify AI systems with PyRAT. The main steps are:
to define a file format to represent the hierarchy of classes
to modify how the provers are called by CAISAR and their outputs to determine when the AI system is abstract safe
to experiment on at least one case study (e.g. CIFAR-10)
if the intership is exended, there will also be a theoretical part (Abstract Interpretation framework)
CAISAR is an open-source platform that focuses on the characterization of AI systems' Robustness and Safety. In order to ensure the safety of an AI system, this platform can call several provers including PyRAT, a Python tool based on Abstract Interpretation techniques also developed at CEA in the AISER team. Those two tools are under active development, as new features are added to improve their accuracy and the expressivity of their specification language. CaiSAR is written in Ocaml, PyRAT is written in Python3.

This work will have contributions to the field of automata learning and to neural networks verification. The internship will likely conclude by publishing a paper (workshop, conference) depending on the quality of the work to be carried.