Nos chercheuses et chercheurs

Sao Mai Nguyen

Unité d'Informatique et d'Ingénierie des Systèmes (U2IS)

Enseignante-Chercheuse

Interested in robotics, artificial intelligence and cognitive science, I try to bridge these 3 aspects in my work, and started working in cognitive developmental robotics. I have special interest in linking research of machine learning, robotic embodiment, child development psychology and neuroscience. I also explore possibilities to make robots adapt to their physical and social environments.
This is why I strive to answer the questions: Can a robot learn like a child? How do children learn? How do human beings or other species learn? Can a robot learn through social interaction with humans?

Activités de recherche et de formation

Latest publication :

Nicolas Duminy, Sao Mai Nguyen, Junshuai Zhu, Dominique Duhaut, Jerome Kerdreux. Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy. Applied Sciences, MDPI, 2021, 11 (3), pp.975. ⟨10.3390/app11030975⟩. ⟨hal-03118190⟩

See list of publications on : https://hal.inria.fr/search/index/?q=%2A&authIdHal_s=sao-mai-nguyen&sort=producedDate_tdate+desc

Nos chercheuses et chercheurs

Sao Mai Nguyen

Activités de recherche et de formation

Publications HAL

Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy

Découverte et exploitation de la hiérarchie des tâches par motivation intrinsèque

How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD

Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills

A Curious Robot Learner for Interactive Goal-Babbling : Strategically Choosing What, How, When and from Whom to Learn

Learning to recognize objects through curiosity-driven manipulation with the iCub humanoid robot

Object learning through active exploration

Self-Organization of Early Vocal Development in Infants and Machines: The Role of Intrinsic Motivation

Interactive Learning Gives the Tempo to an Intrinsically Motivated Robot Learner

Properties for Efficient Demonstrations to a Socially Guided Intrinsically Motivated Learner

Whom Will an Intrinsically Motivated Robot Learner Choose to Imitate from?

Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner

Socially Guided Intrinsically Motivated Learner

Bootstrapping Intrinsically Motivated Learning with Human Demonstrations

Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations.

Real-time face swapping as a tool for understanding infant self-recognition

Nos chercheuses et chercheurs

Sao Mai Nguyen

Activités de recherche et de formation

Publications HAL

Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy

Découverte et exploitation de la hiérarchie des tâches par motivation intrinsèque

How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD

Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills

A Curious Robot Learner for Interactive Goal-Babbling : Strategically Choosing What, How, When and from Whom to Learn

Learning to recognize objects through curiosity-driven manipulation with the iCub humanoid robot

Object learning through active exploration

Self-Organization of Early Vocal Development in Infants and Machines: The Role of Intrinsic Motivation

Interactive Learning Gives the Tempo to an Intrinsically Motivated Robot Learner

Properties for Efficient Demonstrations to a Socially Guided Intrinsically Motivated Learner

Whom Will an Intrinsically Motivated Robot Learner Choose to Imitate from?

Active Choice of Teachers, Learning Strategies and Goals for a Socially Guided Intrinsic Motivation Learner

Socially Guided Intrinsically Motivated Learner

Bootstrapping Intrinsically Motivated Learning with Human Demonstrations

Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations.

Real-time face swapping as a tool for understanding infant self-recognition

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