Chairs

Co-pilots : Leïla Amgoud & Marjorie Allain-Moulet

AI for physical models with geometric tools
Fabrice Gamboa
#learning with little or complex data, fair learning, AI and physical models

Developing AI to Improve Global Governance
César A.Hidalgo
#AI & society

Empowering Data-driven AI by Argumentation and Persuasion
Leïla Amgoud
#explainability, fair learning

Fair & Robust Machine 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

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 Machine 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

New certification approaches of critical AI based systems 
Claire Pagetti
# safe development and embedability, fair learning, robotics and AI

Polynomial Optimization
Jean-Bernard Lasserre
#learning with little or complex data, optimization and game theory for AI, Data and anomalies

Pushing the frontier of nonconvex optimization to more general settings and understanding why it works
Marc Teboulle
#Optimization and game theory for AI

More information about Certifiable AI research program

Co-pilots : Nicolas Mansard & christophe Merle

Artificial Vision
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 techniques for reducing complexity of algorithms for solving problems with uncertainty and preferences
Hélène Fargier
#Automatic reasoning and decision

Motion Generation for Complex Robots 
Nicolas Mansard
#Neuroscience and AI, robotics and AI

Neuroadaptive technology
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