IRL IPAL

International Research Laboratory between France and Singapore in Artificial Intelligence

IRL IPAL

Creation date: 2007
Contact:
Dr. Christophe Jouffrais
christophe.jouffrais(at)ipal.cnrs.fr

IRL IPAL 
Website

Introduction

The partners of the IRL IPAL are CNRS, Université Grenoble Alpes, Institut Mines Telecom, National University of Singapore and A*Star. The IRL IPAL is currently directed by Dr Christophe JOUFFRAIS (CNRS).

Mission and research themes

Mission: Bridge top researchers and labs of CNRS, UGA, IMT, NUS and A*Star into fruitful collaborative links and networks around selected topics in computer science with a strong hold on Artificial Intelligence (project 2021-2025).

Research Axes : Core AI, Explainable and Trustable AI, AI & HCI, Natural Language Processing, Data Science and Applications, Wearable AI.

MAIN RESEARCH PROJECTS

Theme 1: Explainable and Trustable AI

This theme covers techniques that lead to AI model/systems that would lead to better human trusts towards outputs from an AI system, in particular where the learnt models can be explained in a human-understandable manner, and/or can be certified correct.

Theme 2: AI & HCI

This theme deals with new HCI paradigms that integrate AI techniques, or AI techniques that involve human-in-the-loop interactions.

Theme 3: Natural Language Processing

The Natural Language Processing (NLP) is a multidisciplinary field involving linguistics, computer science and artificial intelligence, which aims to create natural language processing tools for various applications. In the last decades, the NLP research domain benefited from the strong improvements made in AI tools and methods, and sometimes led to novel approaches based on neural networks.

Theme 4: Data Science and Applications

The Data Science and Applications theme focuses on data analysis techniques, data management and their applications.

Theme 5: Efficient AI

This theme covers techniques that aim to improve the computational efficiency of AI, through improved hardware, mathematical and algorithmic techniques, or systems design. Examples include neuromorphic or bio-inspired techniques.

laboratories involved

France:
CNRS,
Université Grenoble Alpes,
Institut Mines Telecom,

Singapore:

National University of Singapore,
A*Star

SINFRA symposium on Artificial Intelligence in December 2019. Credits: IPAL