Inria Project Labs, major interdisciplinary research programmes
Inria Project Labs' initiatives enable the launch of ambitious research projects directly linked with the institute. These programmes are often interdisciplinary and call on a wide range of skills. Aim: mobilising and highlighting the expertise of Inria researchers around key challenges.
Inria Project Labs (IPL) operate as inter-team project teams. They are therefore peer-reviewed—in general by foreign experts—and launched for a four-year period. Led by a science officer, Inria Project Labs' initiatives are formalised around a specific research issue with a predefined programme and objectives. They call on the combined "brain power" of all researchers in Inria's various project teams, as well as the intellectual resources of academic or industrial partners.
IPL initiatives allow researchers to organise their work around major issues the Institute wants to concentrate on. A small number of initiatives are launched at a time and benefit from considerable resources. Proposals are examined by the Research Department. Initiatives are reviewed at the halfway mark. A second review, which presents the results obtained, takes place at the end of the project.
AVATAR : The next generation of our virtual selves in digital worlds
In years to come, avatars (i.e., users’ anthropomorphic representation in virtual environments), strongly pushed by major industrial actors, will massively spread in immersive media, e.g., video games, virtual communities, or sport training. But current avatars mostly fail at ensuring a proper feeling of “virtual embodiment”, due to both technological limitations and a lack of perceptual/psychological understanding. Our project aims at designing the next generation of avatars for digital worlds. We want to obtain avatars that are better embodied, but also more interactive and more social. This ambitious objective implies tackling in priority 3 main scientific challenges: 1) the acquisition, modelling and simulation of avatars with novel capacities; 2) the design of novel 3D interaction paradigms for avatar-based interaction, and 3) the design of multi-sensory feedbacks to better feel the subsequent interactions. By leveraging the complementary expertise of 6 Inria teams, and associating a world expert on fundamental psychological aspects (Prof. Mel Slater), we will end up with outstanding scientific and technological assets for Inria, illustrated by means of relevant demonstrators in the field of immersive cinema developed in collaboration with a leading industrial partner: Technicolor.
Inria Project Teams: GRAPHDECO, HYBRID, MIMETIC, MORPHEO, POTIOC, LOKI
BetterNet: An Observatory to Measure and Improve Internet Service Access from User Experience
BetterNet aims at building and delivering a scientific and technical collaborative observatory to measure and improve the Internet service access as perceived by users. In this Inria Project Lab, we will propose new original user-centered measurement methods, which will associate social sciences to better understand Internet usage and the quality of services and networks. Our observatory can be defined as a vantage point, where:
- tools, models and algorithms/heuristics will be provided to collect data,
- acquired data will be analyzed, and shared appropriately with scientists, stakeholders and civil society,
- and new value-added services will be proposed to end-users.
Inria Project Teams: Diana, Dionysos, Inria Chile, Madynes, Muse, Spirals
Partners: ENS-ERST, ip-label
COSY - Real-time COntrol of SYnthetic microbial communities
Recent advances in experimental monitoring and genome engineering techniques have enabled the directed modification of the metabolic pathways and regulatory networks of the cell at an unprecedented scale, and the monitoring of microbial behavior over time at the level of single cells. This has paved to the way to addressing real-time control of microbial communities, both for fundamental research and biotechnological objectives. Today, exploitation of natural or synthetic microbial communities for the accomplishment of processes of societal interest is being pursued in a vast range of scenarios, including the pharmaceutical industry as well as medical and environmental applications, to name a few.
Effective control of microbial communities remains difficult to achieve due to inherent variability in cellular response. Microbial cells are extraordinarily complex on the molecular level, with many processes occurring that are understood in part or simply unknown. No two individual cells of the same species are identical in their molecular contents and sometimes also in their genetic make-up, leading to heterogeneous cellular behaviors. In addition, interactions between different species, such as competition for limited resources or cross-feeding, make control of a community of microorganisms an especially rich and complex problem. Current control solutions are often basic and mostly limited to regulating the average system behavior.
This project aims at exploiting the potential of state-of-art biological modelling, control techniques, synthetic biology and experimental equipment to achieve a paradigm shift in control of microbial communities. We will investigate, design, build and apply an automated computer-driven feedback system for control of synthetic microbial communities, not just accounting for but rather leveraging population heterogeneity and interactions in the optimal accomplishment of a community-level task. The development of methodologies of general applicability will be driven by two different applications closely connected with real-world problems in the biomedical and biotechnological industry. A highly interdisciplinary consortium joining microbiologists, control theorists, bioinformaticians, biophysicists, and applied mathematicians will provide the diverse competences required by the endeavor.
Inria Project Teams : Ibis, Biocore, Lifeware, Non-A
DISCOVERY : DIstributed and COoperative management of Virtual Environments autonomousLY
To accommodate the ever-increasing demand for Utility Computing (UC) resources, while taking into account both energy and economical issues, the current trend consists in building larger and larger Data Centers in a few strategic locations. Although such an approach enables UC providers to cope with the actual demand while continuing to operate UC resources through centralized software system, it is far from delivering sustainable and efficient UC infrastructures for future needs.
The DISCOVERY initiative aims at exploring a new way of operating Utility Computing (UC) resources by leveraging any facilities available through the Internet in order to deliver widely distributed platforms that can better match the geographical dispersal of users as well as the ever increasing demand. Critical to the emergence of such locality-based UC (LUC) platforms is the availability of appropriate operating mechanisms. The main objective of DISCOVERY is to design, implement, demonstrate and promote the LUC Operating System (OS), a unified system in charge of turning a complex, extremely large-scale and widely distributed infrastructure into a collection of abstracted computing resources which is efficient, reliable, secure and at the same time friendly to operate and use.
To achieve this, the consortium is composed of experts in research areas such as large-scale infrastructure management systems, network and P2P algorithms. Moreover two key network operators, namely Orange and RENATER, are involved in the project.
By deploying and using such a LUC Operating System on backbones, our ultimate vision is to make possible to host/operate a large part of the Internet by its internal structure itself: A scalable set of resources delivered by any computing facilities forming the Internet, starting from the larger hubs operated by ISPs, government and academic institutions, to any idle resources that may be provided by end-users.
Inria Project Teams
ASAP, ASCOLA, Avalon, Myriads, Kerdata
Partners : ORANGE, RENATER
HAC SPECIS : High-performance Application and Computers, Studying PErformance and Correctness In Simulation
In the last decades, both hardware and software of modern computers have become increasingly complex. Multi-core architectures comprising several accelerators (GPUs or the Intel Xeon Phi) and interconnected by high-speed networks have become mainstream in the field of High-Performance. Obtaining the maximum performance of such heterogeneous machines requires to break the traditional uniform programming paradigm. To scale, application developers have to make their code as adaptive as possible and to release synchronizations as much as possible. They also have to resort to sophisticated and dynamic data management, load balancing, and scheduling strategies. This evolution has several consequences:
- First, this increasing complexity and the release of synchronizations is even more error-prone than before. The resulting bugs may almost never occur at small scale but systematically occur at large scale and in a non deterministic way, which makes them particularly difficult to identify and eliminate.
- Second, the dozen of software stacks and their interactions have become so complex that predicting the performance (both in term of time, resource usage and energy) of the system as a whole is extremely difficult. Understanding and configuring such systems has therefore become a key challenge.
We believe these two challenges related to correctness and performance can be answered by gathering the skills from experts of *formal verification*, *performance evaluation* and *high performance computing*. The goal of the *HAC SPECIS* project is to answer the methodological needs raised by the recent evolution of HPC architectures by allowing application and runtime developers to study such systems both from the correctness and performance point of view.
Inria Project Teams : AVALON, HIEPACS, MEXICO, MYRIADS, SUMO, VERIDIS, POLARIS, STORM.
HyAIAI : Hybrid Approaches for Interpretable AI
Recent progress in Machine Learning (ML) and especially Deep Learning has made ML pervasive in a wide range of applications. However, current approaches rely on complex numerical models: their decisions, as accurate as they may be, cannot be easily explained to the layman that may depend on these decisions (ex: get a loan or not). In the HyAIAI IPL, we tackle the problem of making “Interpretable ML” through the study and design of hybrid approaches that combine state of the art numeric models with explainable symbolic models. More precisely, our goal is to be able to integrate high level (domain) constraints in ML models, to give model designers information on ill-performing parts of the model, and to give the layman/practitioner understandable explanations on the results of the ML model.
Inria Project Teams : ACODAM, MAGNET, MULTISPEECH, ORPAILLEUR, SEQUEL, TAU.
- IPL HyAIAI website
- Leader: Alexandre Termier - + 33 2 99 84 71 13
HPC-BigData : High Performance Computing and Big Data
The HPC-BigData INRIA Project Lab (IPL) gathers several Machine learning, Big Data and HPC teams from INRIA as well as external partners such as Argone Nationa Lab, LBT/CNRS, ATOS/Bull, Esi-Group. HPC and Big Data evolved with their own infrastructures (supercomputers versus clouds), applications (scientific simulations versus data analytics) and software tools (MPI and OpenMP versus Map/Reduce or Deep Learning frameworks). But Big Data analytics is becoming more compute-intensive (thanks to deep learning), while data handling is becoming a major concern for scientific computing. The goal of this IPL is to work at the intersection between these domains. Research is organized along three main axes: high performance analytics for scientific computing applications, high performance analytics for big data applications, infrastructure and resource management.
Inria Project Teams : AVALON, HIEPACS, MEXICO, MYRIADS, SUMO, VERIDIS, POLARIS, STORM.
ICODA : Data Journalism : knowledge-mediated Content and Data Interactive Analytics
A major issue in data science is the design of algorithms that allow analysts to efficiently infer useful information and knowledge by collaboratively inspecting heterogeneous information sources, from structured data to unstructured content. Taking data journalism as an emblematic use-case, the goal of iCODA is to develop the scientific and technological foundations for knowledge-mediated user-in-the-loop collaborative data analytics on heterogenous information sources, and to demonstrate the effectiveness of the approach in realistic, high-visibility scenarios. The project stands at the crossroad of multiple research fields (content analysis, data management, knowledge representation, visualization), and counts on a club of major press partners.
Inria Project Teams : Graphik, Ilda, Linkmedia, Cedar
ModeliScale: Languages and compilation for Cyber-Physical System Design
The ModeliScale Inria Project Lab focuses on the modeling, simulation and analysis of large cyber-physical systems. It federates the research activities of several teams, covering a broad spectrum of topics, namely hybrid systems modeling & verification, numerical analysis, programming language design and automatic control. Our research agenda includes the following tracks:
- New compilation techniques for Modelica modelers: structural analysis of multimode DAE (Differential Algebraic Equations) systems, modular compilation, combining state-machines and non-smooth dynamical systems (complementarity dynamical systems and Filippov differential inclusions), contract-based specification of cyber-physical systems requirements, requirements capture using under-/over-determined DAE systems.
- Simulation of large cyber-physical systems: distributed simulation, discretization methods for non-smooth dynamical systems, space-/time-adaptive discretization methods for multimode DAE systems, quantized state solvers (QSS).
- Guaranteed numerics: guaranteed simulation of non-smooth and hybrid dynamical systems, numerical methods preserving invariant properties of hybrid systems, contract-based reasoning methods.
Inria Project Teams:
Bipop, Hycomes, Parkas
Partners: Ecole Polytechnique (LIX, équipe Cosynus), CNRS / Centrale-Supélec (L2S), Université Grenoble-Alpes (Verimag, équipe Tempo)
Naviscope: Image-guided NAvigation and VIsusalization of large data sets in live cell imaging and microSCOPy
Nowadays, the detection and visualization of important localized events and process in multi-dimensional and multi-valued images, especially in cell and tissue imaging, is tedious and inefficient. Specialized scientists can miss key events due to complexity of the data and the lack of computer guidance. In the Naviscope IPL project, we plan to develop original and cutting-edge visualization and navigation methods to assist scientists, enabling semi-automatic analysis, manipulation, and investigation of temporal series of multi-valued volumetric images, with a strong focus on live cell imaging and microscopy application domains. We will build Naviscope upon the strength of scientific visualization and machine learning methods in order to provide systems capable to assist the scientist to obtain a better understanding of massive amounts of information. Such systems will be able to recognize and highlight the most informative regions of the dataset by reducing the amount of information displayed and guiding the observer attention.
We will address the three following challenges and issues:
- Novel machine learning methods able to detect the main regions of interest, and automatic quantification of sparse sets of molecular interactions and cell processes during navigation to save memory and computational resources.
- Novel visualization methods able to encode 3D motion/deformation vectors and dynamics features with color/texture-based and non-sub-resolved representations, abstractions, and discretization, as used to show 2D motion and deformation vectors and patterns.
- Effective machine learning-driven navigation and interaction techniques for complex functional 3D+Time data enabling the analysis of sparse sets of localized intra-cellular events and cell processes (migration, division, etc.).
Finally, we will have also to overcome the technological challenge of gathering up the software developed in each team to provide a unique original tool for users in biological imaging, and potentially in medical imaging.
Inria Project Teams: AVIZ, BEAGLE, HYBRID, MORPHEME, PARIETAL, SERPICO, MOSAIC
Neuromarkers: Design of imaging biomarkers of neurodegenerative diseases for clinical trials and study of their genetic associations
Neurodegenerative pathologies, such as Alzheimer’s disease (AD) and Parkinson’s disease, are major public health issues. A major barrier to the development and testing of new treatments is the difficulty to appropriately select the patient populations to include in clinical trials. Specifically, it is crucial to be able to identify patients that are: i) at the earliest disease stage (ideally presymptomatic); ii) at high risk of rapid progression; iii) possess homogeneous disease characteristics. Brain imaging and “omics” technologies (genomics, transcriptomics…) can provide biomarkers of progression and allow to identify disease risk factors. However, the analysis of such complex multimodal data is a hampered by the lack of appropriate methodologies. The Inria Project Lab Neuromarkers to develop new statistical and computational approaches to integrate multimodal imaging and “omics” data and to demonstrate their potential to identify early alterations and predict progression of neurodegenerative diseases. To tackle this challenge, the project brings together multidisciplinary expertise from Inria and ICM (Brain and Spine Institute, www.icm-institute.org) in the fields of statistical learning, brain imaging, bioinformatics, knowledge modeling, genomics and neurodegenerative diseases.
Inria Project Teams: Aramis, Bonsai, Dyliss, Genscale, Xpop
RIOT-FP : Reconcile IoT & Future-Proof Security
RIOT-fp is a research project on cyber-security targeting low-end, microcontroller-based IoT devices, on which run operating systems such as RIOT and a low-power network stack.
Taking a global and practical approach, RIOT-fp gathers partners planning to enhance RIOT with an array of security mechanisms. The main challenges tackled by RIOT-fp are:
- developing high-speed, high-security, low-memory IoT crypto primitives,
- providing guarantees for software execution on low-end IoT devices, and
- enabling secure IoT software updates and supply-chain, over the network.
Beyond academic outcomes, the output of RIOT-fp is open source code published, maintained and integrated in the open source ecosystem around RIOT. As such, RIOT-fp strives to contribute usable building blocks for an open source IoT solution improving the typical functionality vs. risk tradeoff for end-users.
Inria Project Teams: EVA, GRACE, INFINE, PROSECCO, TEA.
SPAI : Security by Program Analysis of the IoT
Inria Project Teams: ANTIQUE, CELTIQUE, INDES, PRIVATICS, KAIROS
SURF : Sea Uncertainty Representation and Forecast
The simulation of coastal and littoral oceanic flow can use many (competing) modelling systems. They differ by the represented geometry (discretisation grid, 2D / 3D), the systems of equations used, the spatial scales / simulated temporal and / or numerical methods used to solve them. It is difficult to establish a hierarchy between these different tools, each having its own merits on different aspects, such as the numerical cost, their numerical precision, the exhaustivity of the represented processes, etc. In the best of cases, these models are coupled together, each being used in its (allegedly) preferred geographic area. The present IPL proposes to go beyond this approach by relying on the combined expertise of the Inria teams involved and to propose a more integrated approach, by mutually enriching the different models and notably by proposing a quantification and a representation of the uncertainty associated with the different choices and approximations made. These issues related to oceanography, ecology and geophysics raise major scientific challenges with strong socio-economic benefits. This IPL will help structure Inria's contributions to these major topics of ocean modelling, where it can have a strong impact.
Inria Project Teams: AIRSEA, FLUMINANCE, CARDAMON, ANGE, LEMON, DEFI, MINGUS.
- IPL SURF website
- Leader: Patrick Vidard - + 33 4 57 42 17 88
ZEP : Zero-Power computing systems
This proposal addresses the issue of designing tiny wireless, batteryless, computing objects, harvesting energy in the environment. The energy level harvested being very low, very frequent energy shortages are expected. In order for the new system to maintain a consistent state, it will base on a new architecture embedding non-volatile RAM (NVRAM). In order to benefit from the hardware innovations related to energy harvesting and NVRAM, software mechanisms will be designed. On one hand, a compilation pass will compute a worst-case energy consumption. On the other hand, dedicated runtime mechanisms will allow 1) to manage efficiently and correctly the NVRAM-based hardware architecture 2) to use energy intelligently, by using the worst-case energy consumption. The ZEP project will gather four INRIA teams that have a scientific background in architecture, compilation, operating systems together with the CEA Lialp and Lisan laboratories of CEA LETI & LIST. The main application target is Internet of Things (IoT).
Inria Project Teams: Cairn, Corse, Pacap, Socrate
ALGAE IN SILICO: Predicting and optimizing the productivity of microalgae
Microalgae potential has been re-discovered in the last decade. These microorganisms may be the source of innovations in the fields of energy, green chemistry, human nutrition, cosmetics and animal nutrition. Indeed, microalgae are recognized for the extraordinary diversity of molecules they can contain: proteins, lipids, vitamins, antioxidants, pigments. Major economic developments on the horizon of a decade are expected.
INRIA has developed in recent years many numerical models describing the complex behaviour of these organisms at different scales, especially for macroscopic modelling (BIOCORE), metabolic network reconstruction (DYLISS) or hydrodynamic modelling (ANGE). The expansion context of microalgae offers many opportunities to transfer the researches in the very demanding industrial world of microalgae.
The Algae in silico IPL will impulse a new dynamics and structure the developments carried out â€‹â€‹over the past five years in various Inria EPI, and will synchronise the future developments. It will provide an integrated numerical platform for simulation "from genes to industrial processes". Our objective is to provide an innovative tool to assess the performance of a given species in a specific process, under a defined climate.This innovative tool will save considerable time and limit investments (going from millions of euros to thousands of euro), while making algae production more efficient.
Project-teams: BIOCORE, ANGE, DYLISS, COFFEE, IBIS, ERABLE
Partners: UPMC (LOV), INRA (LBE), IFREMER (PBA)
- Leader: Olivier Bernard +33 4 92 38 77 85
BCI-LIFT: a new generation of Brain-computer interfaces
Brain-computer interfaces (BCI) are human-machine interaction systems that rely on the analysis of brain activity. They lead to new paradigms for interaction, communication, diagnosis and therapy. BCI-LIFT (Learning, Interaction, Feedback, Training) aims at a new generation of BCI that are simple to handle, efficient, and usable by a large number of people. Our consortium involves experts in signal processing, statistical learning, human-machine interaction, virtual and augmented reality, human motor control, electrophysiology, cognitive neurosciences and brain-computer interfaces. With usability as driving objective, BCI-LIFT will develop new user-centered approaches, notably for training and for proficiency evaluation.
Targeted applications include:
- in the clinical domain, a neurorehabilitation training platform for upper-limb motor control restoration,
- for the general public, an interactive brain-activity visualization tool
- in view of operating standard applications through BCI, a GUI-level interaction protocol.
Project-team s: ATHENA, DEMAR, HYBRID, NEUROSYS, MJOLNIR, POTIOC
C2S@Exa: Computer and Computation Sciences @ exascale
It is nowadays recognized that a multidisciplinary approach is required to overcome the challenges raised by the development of highly scalable numerical simulation software that can exploit computing platforms offering several hundreds of thousands of cores. To achieve this goal, the C2S@Exa initiative gathers
- computer scientists that study programming models, and develop environments and tools for harnessing massively parallel systems,
- algorithmicists that devise numerical kernels and core solvers, and develop generic libraries in order to take benefit from all the parallelism levels with the main goal of optimal scaling on very large numbers of computing entities
- numerical mathematicians that are studying numerical schemes and develop parallel solvers for systems of partial differential equations in view of the simulation of complex physical problems.
Project teams : AVALON, BACCHUS, TONUS, ALPINES, HIEPACS, MOAIS, NACHOS, ROMA, RUNTIME, SAGE
- Leader : Stéphane Lanteri + 33 4 92 38 77 34
CAPPRIS: Protection of Privacy Rights in the Information Society
Cappris is an Inria Project Lab initiated in 2013. The general goal of Cappris is to foster the collaboration between research groups involved in privacy in France and the interaction between the computer science, law and social sciences communities in this area. In order to reach its goals, Cappris will carry out two kinds of actions :
- Joint Research Actions to investigate specific research topics following a collaborative and interdisciplinary approach. Three Joint Research Actions have been launched: the first one is dedicated to the notion of consent, the second one aims to devise a privacy reference architecture and the third one focuses on privacy assessment.
- Networking actions to favour the emergence of a research community on privacy and enhance the interest of researchers and the public in this fast evolving domain.
The outputs of the first line of actions are research results whereas the networking actions will take the form of joint events (meetings, visits, workshops, etc.) as well as wider audience publications and events.
Even if its goal is to provide general techniques with a potentially broad impact, Cappris will consider different contexts and concrete case studies to ensure the relevance and significance of its results. To reach this aim, three classes of case studies have been selected: Online Social Networks (OSN), Location Based Services (LBS) and Electronic Health Record Systems (EHR), which correspond to application domains with great impact on society.
Project teams : PRIVATICS
- Leader : Daniel le Metayer
CITYLAB@INRIA: Overcoming the Smart City Challenge - Toward Environmental and Social Sustainability
CityLab@Inria studies ICT solutions toward smart cities that promote both social and environmental sustainability. Toward that goal, the Lab undertakes a multi-disciplinary research program through the integration of relevant scientific and technology studies, from sensing up to analytics and advanced applications, so as to actually enact the foreseen smart city Systems of Systems while fostering citizen participation.
Obviously, running urban-scale experiments is a central concern of the Lab, so that we are able to confront proposed approaches to actual settings.
The Lab’s research leverages relevant effort within Inria project-teams that is further revisited as well as integrated to meet the challenges of smart cities. Research themes span: energy-efficient wireless communication protocols, urban-scale social and physical sensing, privacy by design, cloud-based urban data management, data assimilation, visual analysis, and urban system software engineering.
In addition, CityLab@Inria research builds upon collaborative effort at the international level, and especially collaboration in the context of the Inria@SiliconValley program.
Inria Project-teams: Clime, Dice, Fun, Mimove, Myriads, Smis, Urbanet, Willow
- Leader: Valérie Issarny +33 1 39 63 57 17
FRATRES : Fusion ReAcTors Research and Simulations
The current rate of fossil fuel usage and its serious adverse environmental impacts (pollution, greenhouse gas emissions, ...) leads to an energy crisis accompanied by potentially disastrous global climate changes. The research of alternative energy sources is thus of crucial importance. Controlled fusion is one of the most promising alternatives to the use of fossil resources, potentially with a unlimited source of fuel.
Controlled nuclear fusion can be considered as an example of grand challenge in many fields of computational sciences from physical modeling, mathematical and numerical analysis to algorithmic and software development and several Inria teams and their partners are developing mathematical and numerical tools in these areas.
The goal of FRATRES is to organize these developments on a collaborative basis in order to overcome the current limitations of today numerical methodologies. The ambition is to prepare the next generation of numerical modeling methodologies able to use in an optimal way the processing capabilities of modern massively parallel architectures.
This objective requires close collaboration between:
- applied mathematicians and physicists that develop and study mathematical models of PDE;
- numerical analysts developing approximation schemes;
- specialists of algorithmic proposing solvers and libraries using the many levels of parallelism offered by the modern architecture and computer scientists.
The project will contribute in close connection with National and European initiatives devoted to nuclear Fusion to the improvement and design of numerical simulation technologies applied to plasma physics and in particular to the ITER project for magnetic confinement fusion.
Project-teams : CASTOR, KALIFFE, IPSO, TONUS
Partners : IRFM-CEA, Max Planck Institute-IPP Garching, LJLL-Jussieu, IMT-Toulouse
- Leader : Hervé Guillard, +33 4 92 38 77 96
HEMERA: developing large scale parallel and distributed experiments
Grid'5000, launched in 2004 by Inria, has become an indispensible tool in software experimentation. Grid'5000 represents nearly 3,000 processors in more than 1,000 nodes, located on 9 French sites, with extensions in the Netherlands, Japan, Luxembourg and Brazil. It is the largest shared computer network in Europe, reserved for research in computing. The aim of this initiative is to experiment with large-scale research problems, such as grid optimisation algorithms, studying the robustness of peer-to-peer networks or simulations in the fields of hydrogeology or energy. This means leading and extending the scientific community around Grid'5000.
Project teams: ALGORILLE, ASAP, ASCOLA, ASTRE, CEPAGE, DOLPHIN, GRAAL, GRAND-LARGE, KERDATA, MESCAL, MYRIADS, OASIS, REGAL, RESO, RUNTIME, SAGE, in partnership with the LSIIT (Strasbourg), the LAAS and IRIT (Toulouse).
- Head of the initiative: Christian Perez - Tel.:+ 33 4 72 72 84 34
MORPHOGENETICS: Deciphering morphogenesis at multiple scales
Morphogenetics is aimed at understanding how shape and architecture in plants are controlled by genes during development. To do so, we will study the spatio-temporal relationship between genetic regulation and plant shape utilizing recently developed imaging techniques together with molecular genetics and computational modeling. Rather than concentrating on the molecular networks, the project will study plant development across scales. In this context we will focus on the Arabidopsis flower, currently one of the best-characterised plant systems.
Project teams : VIRTUAL PLANTS, IMAGINE, MORPHENE
Partners : UMR RDP (ENS-Lyon, Inra, CNRS - Lyon) and RFD (UMR Physiologie Cellulaire Végétale CEA-INRA-CNRS - Grenoble)
- Leader : Christophe Godin - Tél. : 04 67 61 65 77
MULTICORE: a novel approach based on virtualization and dynamicity
Multicore processors are becoming the norm in most computing systems. However supporting them in an efficient way is still a scientific challenge. This large-scale initiative introduces a novel approach based on virtualization and dynamicity, in order to mask hardware heterogeneity, and to let performance scale with the number and nature of cores. It aims to build collaborative virtualization mechanisms that achieve essential tasks related to parallel execution and data management. We want to unify the analysis and transformation processes of programs and accompanying data into one unique virtual machine. We hope delivering a solution for compute-intensive applications running on general-purpose standard computers.
- Leader: Gilles Muller - Tel.: + 33 1 44 27 88 52
PAL: An initiative dedicated to assisting people
This goal is to create an infrastructure that can enable numerous Inria teams to work on technologies for assisting people, to experiment them with users and learn from their experience. The goal is to offer the elderly or disabled more autonomy and a better quality of life. Four research topics will be studied: estimating the degree of frailty of elderly people using non-invasive sensors in order to prevent falls or detect signs of malnutrition; developing mobility equipment such as walkers, wheelchairs; assisting people in getting up, for example from a bed; studying the best means of communication for preserving social links.
Project teams: AROBAS, COPRIN, DEMAR, E-MOTION, PULSAR, PRIMA, MAIA, TRIO, LAGADIC with partners in the medical and hospital sectors.
REGATE: modelling the reproductive function (IPL completed)
Reproduction and its biological mechanisms, in humans and animals, are of increasing interest for researchers. This major physiological function is complex and tightly controlled. It involves the hypothalamus (in the central nervous system), the pituitary gland (an endocrine gland) and the gonads (testicles and ovaries). Researchers are studying the modelling, simulation and control of these different organic levels (from cells to tissue) and their interactions. Multiple temporal scales are concerned: from hormonal communications lasting a few minutes to the 28-day menstrual cycle, from puberty to menopause. Applied mathematics, IT, control theory, but also physiology, cellular and molecular biology are all fields involved in the project.
Project teams: SISYPHE, CONTRAINTES and the following partners: Jacques-Louis Lions laboratory (University Pierre & Marie Curie), BIOS (Biology and Bioinformatics of Signalisation systems) and BINGO (Biology INtéGrative de l'Ovaries/Integrative Biology of the Ovary) teams from the INRA research centre in Tours and the Unit of Theoretical Chronobiology of the ULB (Université Libre de Bruxelles).
- Head of the large-scale initiative: Frédérique Clément - Tel.: +33 1 39 63 53 83
SOFA-INTERMEDS: simulating surgical procedures (IPL completed)
Surgical simulators are being increasingly used to practice complex procedures or learn new techniques in highly realistic conditions. Researchers are developing algorithms dedicated to medical simulation and prototyping of medical simulators. These algorithms are integrated in the SOFA software platform, which can also be used to compare and validate results. A series of medical simulators should be developed, for example, to simulate minimally invasive surgery in ophthalmology, interventional radiology or cardiology.
Project teams: ALCOVE, ASCLEPIOS, EVASION, BUNRAKU, MAGRIT, MOAIS and VISAGES and the following clinical partners: CHR de Lille and CHR de Nancy hospitals, IRCAD and the Massachusetts General Hospital in Boston.
More realistic medical simulators
Sofa InterMeds is a large-scale initiative that aims to develop algorithms dedicated to medical simulation and prototyping of simulators. " This means adding new functions to the SOFA simulation platform, in order to improve its performance . " underlines Stéphane Cotin, Head of Sofa InterMeds and the S.H.A.M.A.N. project team, Inria Lille - Nord Europe " In a nutshell, we want to upgrade the software through our research. Recently we have developed a highly realistic prototype simulator for learning techniques in ophthalmology with the CHR de Lille hospital. We modelled tissue behaviour in order to calculate its deformation in real time and provide a very precise image for the manipulator ".
With the participation of six project teams, Inria's contribution to this research project is considerable " emphasises Stéphane Cotin. Another project goes beyond learning and is being conducted in partnership with clinicians of the CHU de Nancy hospital who are specialised in interventional radiology. This involves developing a tool to ensure better planning of treatments for strokes. To do this, researchers have designed a system that integrates all the patient's imaging data (MRI, scans). Furthermore, in partnership with the IRCAD (Research Institute against Digestive Cancer) in Strasbourg, the team is attempting to develop an augmented reality system that can be used to visualise the internal structures of the liver (vascular network, tumours...) during an operation (hepatectomy)."
SYNCHRONICS: improving the programming of embedded systems (IPL completed)
Initiated in January 2008, Synchronics aims to design a new programming language in order to develop critical embedded systems. These electronic and computer systems are used in avionics, nuclear power, automobiles, etc. This language will be synchronous, as is generally the case in programming embedded systems, and will use specific semantics, like the languages usually used to model them. The aim is also to define a compilation method for modern architectures, mainly multicore implementations.
Project teams: LIENS, PROVAL, ALCHEMY, POP ART, S4, Vérimag laboratory (Synchrone team)
CardioSense3D: a digital heart adapted to each patient (IPL completed)
Cardiosense3D, the first large-scale initiative launched by Inria, ended in 2009. This original interdisciplinary research project will be prolonged via a European project on the digital heart called EuHeart. The goal: to simulate the workings of the human heart in order to understand certain heart diseases and improve prevention, diagnosis and patient therapies. The academic partners, clinicians and medical industries involved have designed a heart simulator. It is based on physiological principles at the cellular, tissue and organ levels. The parameters of each model are set for an individual patient, a necessary approach for clinical use. The simulator is being tested with animal data and on patients who suffer from arrhythmia.
Project teams: ASCLEPIOS, MACS, SISYPHE, REO and international partners, notably the clinical teams at Guy's Hospital (London) and NIH (Washington).
- Head of the large-scale initiative: Hervé Delingette - Tel.: +33 4 92 38 77 64
COLAGE: controlling the growth of bacteria (IPL completed)
This large-scale initiative combines approaches in systems biology and synthetic biology. It involves studying and controlling the growth of bacteria. Innovative IT tools and quantitative experimental studies are used to explore the variability of bacterial growth in different environments. It is hoped that understanding and controlling the growth and aging of bacteria will lead to applications in biotechnologies and the creation of new drugs.
Project teams: ALCHEMY, COMORE, CONTRAINTES, IBIS and the following partners: experimental cellular biology teams from the INSERM (Université Paris Descartes) and the CNRS (LAPM, Université J. Fourier Grenoble).
- Head of the large-scale initiative: Hugues Berry - Tel.: + 33 4 72 43 72 84
FUSION: simulating nuclear fusion (IPL completed)
Thermonuclear fusion is a promising field for electricity production in the long term. Construction of an experimental reactor in Cadarache (France) is currently being studied, in the context of the international ITER project. Fusion requires temperatures of one million degrees Celsius and magnetic confinement of plasma (ionised gas). In 2006 and 2007, several Inria teams developed tools to analyse the behaviour of plasma within the framework of the collaborative research project Fusion. This large-scale initiative builds on these results in order to achieve two objectives: continuing the development of nuclear fusion simulation tools in general, and of ITER in particular, and building a community of mathematicians and computer scientists around this specific area of physics.
Project teams: CALVI, METALAU, BACCHUS, HIEPACS, SIMPAF, SMASH, PUMAS, GAMMA, APICS, TROPICS, university teams and CNRS centres at Nice, Toulouse and Paris 6, and the CEA of Cadarache.
- Head of the large-scale initiative: Eric Sonnendrücker
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Websites of Inria Project Labs
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