Return to Associate Teams (joint research projects)

Archive: Complete list of supported associate teams

Associate Team Research Focus Partners Principal Investigators Dates
AC/DC Soft robotics, mechanical modeling of deformations, robotic design Stanford University Christian Duriez, Inria  DEFROST

& Allison Okamura, Mechanical Engineering Dept.
Stanford University

AQUARIUS  Advanced methods for uncertainty quantification in compressible flows Stanford University Pietro M. Congedo, Inria CARDAMOM

& Gianluca Iaccarino, Dpt of Mechanical Engineer, Stanford University

A hybrid P2P/cloud for big data UC Santa Barbara Patrick.Valduriez, Inria ZENITH

& Divyakant Agrawal, University of California Santa Barbara

Analysis of structural MR and DTI in neonates  Univ. of Southern California

& Univ. of Pennsylvania

Pierre Fillard & B. Thirion, Inria PARIETAL,

Caroline Brun, University of Pennsylvania

& Natasha Lepore, USC and Children’s hospital of Los Angeles – University of Southern California

Mathematical modelling and Numerical Simulation for Cardiovascular Applications Stanford University Irène Vignon-Clémentel, Inria REO

& Alison Marsden, Mechanical and Aerospace Engineering Dpt – Stanford

Cloud computing over Internet volunteer resources UC Berkeley Derrick Kondo, Bruno Gaujal, Arnaud Legrand, Inria MESCAL

& David Anderson, Space Sciences Laboratory, U.C. Berkeley

CLOUDY Secure and Private Distributed Data Storage and Publication in the Future Internet UC Berkeley

& UC Irvine

Claude Castellucia, Inria PRIVATICS

& Dawn Song, EECS Dpt, U.C. Berkeley and Gene Tsudik, UC Irvine

COALA Communication optimal algorithms for linear algebra UC Berkeley Laura Grigori, Inria ALPINES

& Jim Demmel, EECS Dpt, U.C. Berkeley

CoHPC Correctness and Performance of HPC Applications LBNL Emmanuelle Saillard, Inria  STORM

& Costin Lancu, LBNL

Computation of causal structures University of California Davis Nicolas Brodu, Inria GEOSTAT

& James Crutchfield, University of California Davis

Since 2021


COMET Computational methods for the analysis of high-dimensional data  Stanford University Steve Oudot, Inria GEOMETRICA

& Leo Guibas, EECS Dpt, Stanford University

 COMFORT COntrol and FOrecasting in Transportation networks UC Berkeley Carlos Canudas De Wit, Inria NECS

& Roberto Horowitz,  Dpt of Mechanical Engineering, U.C. Berkeley

COMMUNITY Message delivery in heterogeneous networks  UC Santa Cruz Thierry Turletti, Inria DIANA

& Katia Obraczka, School of Engineering, U.C. Santa Cruz

COMPOSITE Compositional System Integration  UC San Diego Jean-pierre Talpin, Inria  TEA

& Rajesh Gupta, Microelectronic Embedded Systems Lab, U.C. San Diego

CRISP Human perception for graphics and Interaction  UC Berkeley Adrien Bousseau, Inria GraphDeco (previously REVES)

& Maneesh Agrawala, Marty Banks, EECS Dpt and Optometry and Vision Science, U.C. Berkeley

Data Analysis on Large Heterogeneous Infrastructures for Science LBNL Christine Morin, Inria MYRIADS

& Deb Agarwal, Lawrence Berkeley National Laboratory, U.C. Berkeley

DECibel  Discover, Express, Create – Interaction Technologies For Creative Collaboration UC Berkeley Wendy Mackay, Inria ExSitu 

& Bjoern Hartmann, CITRIS UC Berkeley

DEfining Surrogacy of early Transcriptomics foR vaccInE Response RAND Corporation Boris Hejblum, Inria SISTM

& Denis Agniel (RAND Corporation)

Since 2022
DIVERSITY Measuring and Exploiting Diversity in Low-Power Wireless Networks  Univ. of Southern California Thomas Watteyne, Inria EVA

& Bhaskar Krishnamachari, Univ. of Southern California, Autonomous Networks Research Group (ANRG



Distributed Intelligent Vehicular Environment – Enabling ITS through programmable networks UC Santa Cruzand

FEEC at UNICAMP (Brazil)

Thierry Turletti, Inria DIANA& Katia Obraczka, UC Santa Cruz

& Christian Esteve Rothenberg, INTRIG Team FEEC/UNICAMP

ELF Efficient deep learning frameworks Caltech Yulia Gusak, Inria HIEPACS

& Anima Anandkumar (Caltech)

Since 2023


 FASTLA  Fast and Scalable Hierarchical Algorithms for Computational Linear Algebra  Stanford University & LBNL  Olivier Coulaud,Inria  HIEPACS ,

Eric Darve, ICME, Stanford,

& Esmond Ng Lawrence Berkeley National Laboratory, U.C. Berkeley

GeomStats Geometric Statistics in Computational Anatomy: Non-linear Subspace Learning Beyond the Riemannian Structure Stanford University Xavier Pennec, Inria EPIONE (formerly ASCLEPIOS)

& Susan Holmes, Stanford University

GOAL Geometry and Optimization with ALgebraic methods  UC Berkeley  Jean-charles Faugere, Inria POLSYS

& Bernd Sturmfels, U.C. Berkeley

HERMES Distributed Systems & Big Data LNBL Shadi Ibrahim, Inria MYRIADS, Inria STACK

& Suren Byna, Scientific Data Management Group, LBNL



Large-scale statistical learning for visual recognition  UC Berkeley Zaïd Harchaoui, Inria LEAR,

Cordelia Schmid, Inria LEAR,

Nourredine El Karoui, Statistics Dpt, U.C. Berkeley

& Malik Jitendra, EECS Dpt, U.C. Berkeley

IT-SG-WN Wireless networks and information theory  UC Berkeley François Baccelli, Inria TREC

David TseVankat Anantharam, EECS Dpt and Wireless Foundations – UC Berkeley

ITSNAP Geometric and knowledge-based analysis for Nucleic

Acid and Protein dynamics and Interactions

 Stanford University Julie Bernauer, Inria AMIB

& Michael Levitt, CSB Lab, Stanford University

LargeBrainNets Characterizing Large-scale Brain Networks Using Novel Computational Methods for dMRI and fMRI-based Connectivity Stanford University Demian Wassermann, Inria ATHENA

& Vinod Menon,  Stanford Cognitive and Systems Neuroscience Laboratory

LEGO LEarning GOod representations for natural language processing Univ. of Southern California (formerly with  UCLA) Aurélien Bellet, Inria MAGNET

& Fei Sha, University of Southern California, Dpt of Computer Science (formerly with TEDS,UCLA)

MARE Reduced-order models, numerical modeling Stanford University Angelo Iollo, Inria MEMPHIS

& Charbel Farhat, Department of Aeronautics and Astronautics, Stanford University



Meta&Co (formerly MetaMRI)  Machine learning for meta-analysis of functional neuroimaging data  Stanford University Bertrand Thirion, Inria PARIETAL 

& Russ Poldrack, Stanford University

MINES Adaptive Communication Middleware for Resilient Sensing & Actuation IN Emergency Response Scenarios  UC Irvine  Valerie Issarny, Inria MIMOVE

& Nalini Venkatasubramanian, UC Irvine

Num4SEP Numerics for Spherical Electroporation   UC Santa Barbara Clair Poignard, Inria MONC

& Frederic Gibou, Dpt of Mechanical Eng., U.C. Santa Barbara

OAKSAD  Languages and techniques for efficient large-scale Web data management UC San Diego  Ioana Manolescu, Inria OAK

& Alin Deutsch, University of California San Diego

ORESTE  Optimal reroute strategies for traffic management   UC Berkeley  Paola Goatin, Inria OPALE

& Alexandre Bayen, EECS Dpt, U.C. Berkeley

Pushing the Limits of Audio Spatialization with eMerging Architectures Stanford University Romain Michon, Inria EMERAUDE

& Chris Chafe (Stanford University)

Since 2022
Protégé and SHACL extension to support ontology validation Stanford University Fabien Gandon, Inria WIMMICS

& Rafael Gonçalves (Stanford University)

Since 2020
REALMS Real-Time Real-World Monitoring Systems UC Berkeley

& Univ. of Michigan

Thomas Watteyne, Inria EVA (Initially HIPERCOM2),

Steven Glaser, U.C. Berkeley

& Branko Kerkez, Uni. Michigan

RIPPES Rigorous Programming of Predictable Embedded Systems   UC Berkeley  Alain Girault, Inria SPADES

& Lee Edward, UC Berkeley

ROHM Reduced Order Hybrid Models Stanford University Angelo Iollo, Inria MEMPHIS

& Charbel Farhat (Stanford University)

Since 2023


SIRIUS  Situated interaction  Stanford University Wendy Mackay & Michel Beaudoin-Lafon, Inria INSITU

& Scott Klemmer, Stanford HCI group

SNOWBALL (formerly SNOWFLAKE)  Discovering knowledge on drug response variablity by mining electronic health records (formerly Knowledge Discovery from Linked Data and Clinical Notes)  Stanford University Adrien Coulet, Inria ORPAILLEUR

& Nigam Shah, Stanford University

SPLENDID  Self-Paced Learning for Exploiting Noisy, Diverse or Incomplete Data  Stanford University Nikos Paragios, Inria GALEN

& Daphne Koller, DAGS

STATWEB  Fast statistical analysis of text databases via sparse learning  UC Berkeley Francis Bach, Inria SIERRA

& Laurent El Ghaoui, EECS Dpt and IEOR – UC Berkeley

SWAGR  Statistical Workforce for Advanced Genomics using RNAseq  RAND Corporation  Boris Hejblum, Inria SISTM

& Denis Agniel, RAND Corporation, Statistics group

Robust Communication and Localization for Swarms of Mobile Miniaturized Wireless Motes University of California Berkeley Thomas Watteyne

Inria EVA

& Kris Pister (UC Berkeley)

Since 2021