ANITI's scientific project revolves around three major research programs: Acceptable AI, Certifiable AI and Collaborative AI. Each research program brings together several chairs.
Discover the chairs by research program:
Acceptable AI program
Co-pilotes : Cesar Hidalgo et Marjorie Allain-Moulet
AI for physical models with geometric tools
Fabrice Gamboa
#learning with little or complex data, fair learning, AI and physical models
Augmented society
Cesar A.Hidalgo
#AI & society
Empowering Data-driven AI by Argumentation and Persuasion
Leïla Amgoud
#explainability, fair learning
Fair & Robust Learning
Jean-Michel Loubès
#Fair learning, explainability
Fusion-based inference from heterogeneous data
Nicolas Dobigeon
#learning with little or complex data
Law, Accountability and Social Trust in AI
Céline Castets - Renard
#Fair learning, AI & society
Moral AI
Jean-François Bonnefon
#AI & society
The effects of AI on competition in the marketplace
Bruno Jullien
#AI & society
More information about Acceptable AI research program
Certifiable AI program
Co-pilots : Serge Gratton & Grégory flandin
AI for air traffic management and large scale urban mobility-
Daniel Delahaye
#automatic reasoning and decision
Data Assimilation and Machine Learning
Serge Gratton
#safe development and embedability, data and anomalies, AI and physical models, Optimization and game theory for AI
Deep learner explanation & verification
Joao Marquès Silva
# safe development and embedability, fair learning, explainability, automatic reasoning and decision-making
Fair & Robust Learning
Jean-Michel Loubès
#Fair learning, explainability
Game Theory and Artificial Intelligence
Jérôme Renault
#Optimization and game theory for AI
Large Scale Optimization for AI
Jérôme Bolte
#AI and physical models, Optimization and game theory for AI
CertifAI – Towards the certification of ML-based systems
Claire Pagetti
# safe development and embedability, fair learning, robotics and AI
Polynomial Optimization for Machine Learning and data analysis
Jean-Bernard Lasserre
#learning with little or complex data, optimization and game theory for AI, Data and anomalies
More information about Certifiable AI research program
Collaborative AI program
Co-pilotes : Nicolas Mansard et Christophe Merle
Reverse-engineering the visual system
Thomas Serre
#learning with little or complex data, language, neuroscience and AI, Robotics and AI
Cognitive and interactive robotics
Rachid Alami
#language, neuroscience and AI, robotics and AI
Deep Learning with semantic, cognitive and biological constraints
Rufin van Rullen
#learning with little or complex data, language, neuroscience and AI, Robotics and AI
Design using intuition and logic
Thomas Schiex
#learning with little or complex data, AI and physical models, automatic reasoning and decision, explainability
Knowledge compilation,uncertainty,preferences
Hélène Fargier
#Automatic reasoning and decision
Artificial and Natural movement
Nicolas Mansard
#Neuroscience and AI, robotics and AI
Neuroadaptive technology for Human Machine Teaming
Fréderic Dehais
#Neuroscience and AI, Robotics and AI
Synergistic transformations in model based and data based diagnosis
Louise Travé-Massuyes
#Automatic reasoning and decision, explainability, data and anomalies
More information about Collaborative AI research program