Two new Associate Teams and three renewed teams with California Universities – Update: A third project joins Inria@SiliconValley!

MiMove  Inria team  ©Inria / Photo C. Morel

Inria is glad to announce the selection of 2 new Associate Teams with California partners (University of California, Irvine and the RAND Corporation ) as part of the 2018 Inria Associated Team call. 

In addition, three teams that were created in 2015 (Meta&Co , formerly MetaMRI, GeomStats (both with Stanford University) and REALMS (with UC Berkeley) have been renewed for 3 years.

Update April 16th, 2018: A third project joins Inria@SiliconValley in 2018! The Associate team DrIVE between Inria team DIANA at Sophia-Antipolis and University of Campinas & Ericsson Research in Brazil, is partnering with the Internet working research group (i-NRG) at UC Santa Cruz.

The Inria@SiliconValley program counts now 14 ongoing Associated Teams in 2018. See the Research Teams page for the full list.

3 Associate Teams selected in 2018:

MINES – “Adaptive Communication Middleware for Resilient Sensing & Actuation IN Emergency Response Scenarios” – MIMOVE Inria Team (Valerie Issarny) and UC Irvine (Nalini Venkatasubramanian)

Emerging smart-city and smart-community efforts will require a massive deployment of connected entities (Things) to create focused smartspaces. Related applications will enhance citizen quality of life and public safety (e.g., providing safe evacuation routes in fires). However, supporting IoT deployments are heterogeneous and can be volatile and failure-prone as they are often built upon low-powered, mobile and inexpensive devices – the presence of faulty components and intermittent network connectivity, especially in emergency scenarios, tend to deliver inaccurate/delayed information. The MINES associate team addresses the resulting challenge of enabling interoperability and resilience in large-scale IoT systems through the design and development of a dedicated middleware. More specifically, focusing on emergency situations, the MINES middleware will: (i) enable the dynamic composition of IoT systems from any and all available heterogeneous devices; (ii) support the timely and reliable exchange of critical data within and across IoT in the enabled large-scale and dynamic system over heterogeneous networks. Finally, the team will evaluate the proposed solution in the context of emergency response scenario use cases.

SWAGR – “Statistical Workforce for Advanced Genomics using RNAseq” – SISTM Inria Team (Boris Hejblum) and RAND Corporation (Denis Agniel)

The SWAGR Associate Team aims at bringing together a statistical workforce for advanced genomics using RNAseq. SWAGR combines the biostatistics experience of the SISTM team from Inria Bordeaux with the mathematical expertise of the statistics group at the RAND Corporation in an effort to improve RNAseq data analysis methods by developing a flexible, robust, and mathematically principled framework for detecting differential gene expression. Gene expression, measured through the RNAseq technology, has the potential of revealing deep and complex biological mechanisms underlying human health. However, a critical limitation of current state-of-the-art approaches for RNAseq data analysis is their failure to adequatly control the type-I error, leading to an inflation of false positives in analysis results. False positives are an important issue in all of science. In particular in biomedical research when costly studies are failing to reproduce earlier results, this is a pressing issue. SWAGR propose to develop a rigorous statistical framework modeling complex transcriptomic studies using RNAseq by leveraging the synergies between the works of B. Hejblum and D. Agniel. The new method will be implemented in open-source software as a Bioconductor R package, and a user friendly web-application will be made available to help dissemination. The new method will be applied to clinical studies to yield significant biological results, in particular in vaccine trials through existing SISTM partnerships. The developed method is anticipated to become a new standard for the analysis of RNAseq data, which are rapidly becoming common in biomedical studies, and has therefore the potential for a large impact.

Visit the SWAGR web site  at:

DrIVE – “Distributed Intelligent Vehicular Environment – Enabling ITS through programmable networks” – DIANA Inria Team (Thierry Turletti), FEEC/UNICAMP (Christian Esteve Rothenberg), Ericsson (Mateus Santos) and UC Santa Cruz (Katia Obraczka)

Transportation systems are part of our society’s critical infrastructure and are expected to experience transformative changes as the Internet revolution unfolds. The automotive industry is a notable example: it has been undergoing disruptive transformations as vehicles transition from traditional unassisted driving to fully automated driving, and eventually to the self-driving model. Communication technology advancements such as support for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication have been one of the key enablers of next generation transportation services, also known as Intelligent Transport Systems (ITS). However, ITS services and applications pose significant challenges to the underlying communication and network infrastructure due to their stringent low latency, reliability, scalability, and geographic decentralization requirements. The DrIVE associated team proposal aims at addressing such challenges by: (1) developing a programmable network control plane that will dynamically adjust to current environment conditions and network characteristics to support ITS’ scalability, quality of service (QoS), and decentralization requirements, and (2) applying the proposed distributed network control plane framework to ITS applications, such as road hazard warning, autonomous- and self-driving vehicles, and passenger-centric services (e.g., infotainment and video streaming).

Visit the DrIVE website:

All new associate teams are subject to final approval from the French authorities.