Fields of research
Exploratory actions: opening up new lines of research
Exploratory actions aim to promote the emergence of new research themes. They give scientists the means to test out original ideas. These test runs can then be extended, leading to the creation of a fully-fledged Inria project-team. Presentation of the exploratory actions put in place by Inria.
Exploratory actions provide an opportunity to trust in researchers' intuition. The system allows Inria to mobilise resources to address very innovative, risky subjects that represent a departure from the institute's traditional approaches. It provides the means to examine a subject in detail and prove its scientific relevance: a vital stage before creating a project-team. It can also mean exploring unusual themes at the margins of Inria's sphere of action, such as subjects concerning social sciences or legal issues. This is the case with the ongoing LICIT and STEEP projects.
Exploratory actions provide an opportunity to trust in researchers' intuition
Exploratory actions provide an opportunity to trust in researchers' intuition. The project, which is financed for two years, is led by one heavily involved researcher, who is supported by a small number of teammates. The organisational structure is flexible, as is its assessment. The results are presented during an open day aimed at a wide audience. The first exploratory actions, FLOWERS and NANO-D, have led to the creation of project-teams. Pierre-Yves Oudeyer, head of the Flowers team, has also been recognised by the European Research Council and will receive a grant of 2 million euros for 5 years to launch his project. Stéphane Redon, head of the Nano-D team, was also shortlisted, which shows the quality of his project.
The aim of the Cognitive Computing team is to reverse engineer human learning abilities, i.e., to construct effective and scalable algorithms which perform at least as well as humans, when provided with similar data, to study their mathematical and algorithmic properties and to test their empirical validity as models of humans by comparing their output with behavioral and neuroscientific data. The expected results are more adaptable and autonomous machine learning algorithm for complex tasks, and quantitative models of cognitive processes which can used to predict human developmental and processing data.
ELAN has the ambition to become a unique simulation team at Inria with an original positioning across Computer Graphics and Computational Mechanics. The team is focussed on the design of predictive, robust, efficient and controllable numerical models for capturing the shape and motion of visually rich mechanical phenomena, such as the buckling of an elastic plate, the flowing of a sand pile, or the entangling of large fiber assemblies. Target applications encompass the digital entertainment industry (e.g., feature animation, special effects), as well as virtual prototyping for the mechanical
engineering industry (e.g., aircraft manufacturing, cosmetology); though very different, these two application fields require predictive and scalable models for capturing complex mechanical phenomena at the macroscopic scale. An orthogonal objective is the improvement of our understanding of natural physical and biological processes involving slender structures (such as plant growth, granular flows, DNA supercoiling), through active collaborations with soft matter physicists. To achieve its goals, the team is striving to master as finely as possible the entire modeling pipeline, involving a pluridisciplinary combination of scientific skills across Mechanics and Physics, Applied Mathematics, and Computer Science.
InBio is an interdisciplinary research group, combining wet and dry biology in the same lab.
Our main goal is to develop a comprehensive methodological framework supporting the development of a quantitative understanding of cellular processes. Given a process of interest and current knowledge on the system, the problem is to iteratively decide which strain to construct and which experiment to run to characterize the process in an optimal manner, perform the chosen experiment, and update the current knowledge on the process.
We combine systems and synthetic biology approaches with active learning and control methods, together with stochastic and statistical modeling frameworks.
InBio is an Inria / Pasteur Institute joint research group. It is hosted at Institut Pasteur and affiliated to the Lifeware team at Inria Saclay - Ile-de-France.
Imagine if we could control nanoscale matter in the sophisticated way we control information using computers. This form of ultimate control would lead to fancy drugs that act like molecular doctors to diagnose and cure patients and efficient chemical manufacturing processes that exploit nanoscale logical interactions. The Inria TAPDANCE team focuses on both the theory and practical implementation of such molecular computers:
- We invent new models of molecular computers and mathematically characterise their computationally power.
- We design and engineer molecular computers in the wet-lab, using DNA as a building material.
TAPDANCE is an approximate acronym for Theory and Practice of DNA Computing Engines.
Exploratory actions completed
Ctrl-A: Control Techniques for Autonomic, Adaptive and Reconfigurable Computing systems
Computing systems are more and more ubiquitous, at scales from tiny embedded systems to large-scale cloud infrastructures. They are more and more adaptive and reconfigurable, for resource management, energy efficiency, or by functionality. Furthermore, these systems are increasingly complex and autonomous: their administration cannot any longer rely on a strong interaction with a human administrator. The correct design and implementation of automated control of the reconfigurations and/or their tuning is recognized as a key issue for the effectiveness of these adaptive systems.
Our objective is to build methods and tools for the design of safe controllers for autonomic, adaptive, reconfigurable computing systems. To attain this goal, we propose to combine Computer Science and Control Theory, followinf the axes corresponding to the different levels of of this co-design problem: adaptive systems infrastructures, programming support, and modeling and control techniques.
Our team groups complementary competences, from different laboratories, in order to contribute more efficiently to the topic of hardware/softxare interfaces, particularly active locally to Grenoble, and more widely nationally and internationally in the emerging community on Feedback Computing.
ESTASYS: developping brand new formal methods for Systems of Systems
Computer systems play a central role in modern societies and their errors can have dramatic consequences. Industry and academics thus invest a considerable amount of effort developing techniques to prove the correctness of these systems. Among such techniques, one finds (1) testing, the traditional approach to detect bugs with test cases, and (2) formal methods, e.g., model checking (Turing award), that can guarantee the absence of bugs. Both approaches have been largely deployed on static systems, whose behaviour is entirely known. ESTASYS focuses on developping
brand new formal methods for Systems of Systems.
FLOWERS: Baby robot learning
Can a robot learn like a baby and explore the world around it without being programmed by an engineer? This is the incredible proposition being explored by a team at Inria Bordeaux Sud-Ouest. Without imitating human intelligence in the same way as artificial intelligence, these researchers in behavioural and social robotics are trying to create a system capable of learning and developing by itself, in the same way that a child does.
Developmental psychologists have deciphered the logic behind these complex processes, based on spontaneous exploration. Implementing a "curiosity function" of this kind in robots' "brains" would allow them to learn for themselves. The team has already put this concept to the test. It is now attempting to pair this learning about the body and space with language learning, thus paving the way for autonomous social interaction of robots with humans. Such robots would be better able to cope with unknown spaces and situations. They could also be used to test the pertinence of psychologists' theories.
LICIT: An ethical approach to computer science
Information technology is everywhere: in a large number of devices, from washing machines to aeroplanes, in the RFID chips that control access to buildings, in car locking systems and, of course, in Internet systems, but also in transport cards, biometric passports and video surveillance. How can collective and individual freedoms be protected against this wave of new services and uses of information technology?
A team from Inria Grenoble - Rhône-Alpes has decided to tackle this challenge by opening up a new field of research, taking legal and ethical criteria into account when designing computer systems. Along with lawyers, they are revisiting the principles of privacy and inventing a formal framework for a data protection infrastructure. They are also proposing methods for establishing legal responsibilities in terms of software.
MUSE: Measuring networks for enhancing USer Experience
Muse stands for “Measuring networks for enhancing User Experience”. Our research is mostly in the area of network measurements. We focus on developing new algorithms and systems to improve user experience online. In particular, we are addressing two main problems of today's Internet users:
- Technology is too complex. Most Internet users are not tech-savvy and hence cannot fix performance problems and anomalous network behavior by themselves. The complexity of most Internet applications makes it hard even for networking experts to fully diagnose and fix problems. Users can't even know whether they are getting the Internet performance that they are paying their providers for.
- There is too much content. Users are often lost when deciding which articles to read or which movie to watch, for instance.
NANO-D: Virtual mock-ups on an atomic scale
Many manufactured goods, from cars to aeroplanes, are designed and tested using computers. This approach has undeniable advantages in terms of production costs and lead times. The aim of the researchers at Inria Grenoble - Rhône-Alpes is to design effective algorithmic methods to do the same on an atomic scale. Why? To model and simulate complex nanometric systems, be they natural nano-systems, such as proteins, or artificial ones, such as miniature mechanical structures.
The problem is difficult, given the large number of atoms involved as well as the duration and complexity of the phenomena to be simulated. All these barriers make such simulations too expensive. Efficient methods are therefore a very attractive proposition. In particular, researchers are developing new, adaptive approaches which automatically concentrate computing resources on the most relevant parts of the nano-systems under consideration.
STEEP: Modelling sustainable development
Making decisions about the construction of a dam, estimating the impact of an urbanisation project, choosing a waste processing technology: all these technological choices will have repercussions in terms of sustainable development. Yet local and regional authorities are cruelly lacking in tools to help them make these choices.
To address this problem, researchers at Inria Grenoble - Rhône-Alpes are exploring two new types of decision aids. The first simulates complex systems in which numerous factors, particularly human factors, interact. The objective is to anticipate the impacts of such policy choices on biodiversity and local resources… based on a variety of scenarios in respect of climate change and global economic developments. The second tool developed aims to optimise choices in terms of costs, not only from an economic point of view but also from an environmental and social perspective.