IRL IPAL
International Research Laboratory between France and Singapore in Artificial IntelligenceIRL IPAL
Creation date: 2007
Contact:
Dr. Christophe Jouffrais
christophe.jouffrais(at)ipal.cnrs.fr
![](https://cnrssingapore.cnrs.fr/wp-content/uploads/2020/05/IPAL-logo-2020-text.jpg)
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
RELATED PROJECTS
- DesCartes Program: IPAL is involved in this CNRS@CREATE program on Intelligent Modelling for Decision-making in Critical Urban Systems.
Program DesCartes aims to develop disruptive hybrid AI to serve the smart city and to enable optimized decision-making in complex situations, encountered for critical urban systems.
Learn more about it on the CNRS@CREATE website here.
![](https://cnrssingapore.cnrs.fr/wp-content/uploads/2020/05/SINFRA-group-photo-long.jpg)
SINFRA symposium on Artificial Intelligence in December 2019. Credits: IPAL