Project-Team:PARIETAL


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Section: Dissemination

Philippe Ciuciu: IEEE ISBI (15 papers), IEEE ICASSP (10 papers), IEEE ICIP (5 papers), NIPS (4 papers), EUSIPCO (5 papers).
Bertrand Thirion: IPMI, MICCAI, NIPS, ISBI, PRNI, AISTATS
Gaël Varoquaux: IEEE ICASSP, MICCAI, NIPS, IPMI, ICML

Bertrand Thirion: Medical Image Analysis, Frontiers in brain imaging
Gaël Varoquaux: Frontiers in NeuroInformatics, Frontiers in brain imaging methods, NeuroImage

Philippe Ciuciu: Reviewer for Neuroimage, IEEE Signal Processing Letters, Signal Processing, IEEE Trans. Medical Imaging, Plos One, Plos Comput. Biology, Frontiers in Neuroscience.
Bertrand Thirion: Human Brain Mapping, IEEE TMI, MedIA, NeuroImage, PNAS
Gaël Varoquaux: NeuroImage, JSTSP, PNAS, HBM, PLOS Comp Bio, Gigascience
Olivier Grisel: Journal of Machine Learning Research (software track).

February: invited talk at the Imagerie du Vivant National congress, entitled Large-scale analyses in functional brain Imaging.
February: presentation at the Pasadena working group of the Digicosme Labex.
April: invited presentation at European Neuroscience institute, Paris, entitled Seeing it all: Convolutional network layers map the function of the human visual system.
April: presentation Functional connectomicts, at DTU Copenhagen, entitled from large-scale estimators to empirical validation.
May: Talk at Atlas workshop, Grenoble, entitled Learning representations from functional brain imaging.
June: organizer of a table ronde at the Futur en Seine event entitled Computational methods for neurosciences & medical imaging.
October: talk at MPI Psychiatry, Munich, entitled Machine learning for neuroimaging: current challenges and solutions.
June: Talk at Neurostic workshop, Grenoble, entitled Learning representations from functional brain imaging.
October: Invited talk by the ITMO Neuroscience, Bordeaux, entitled Working with large data samples: the case of human brain imaging.

12/16: IEEE Lecture at University of British Columbia (Vancouver, Canada): Sparkling: Novel non-Cartesian sampling schemes for accelerated 2D anatomical imaging at 7 Tesla.
12/16: Pacific Parkinson's research center (Vancouver, Canada): Impact of perceptual learning on resting-state brain dynamics in fMRI: A supervised classification study.
09/16: GdR d'Analyse Multifractale (Avignon, France): Convergence of neural activity to multifractal attractors in MEG predicts learning.
08/16: invitation to the Special session entitled “Unraveling brain networks from functional neuroimaging data” at EUSIPCO'16 (Budapest, Hungary): Impact of perceptual learning on resting-state fMRI connectivity: A supervised classification study.
06/16: Journées scientifiques d'Inria (Rennes, France): Compressive Sampling in MRI.
06/16: Inria Sophia-Antipolis, équipe Athena. New physically plausible compressive sampling schemes for MRI: First results at 7 Tesla
05/16: University of Geneva (Campus BioTech, Geneva, Switzlerand): Convergence to asymptotic Multifractal dynamics in the brain predicts learning.
02/16: Grenoble Institut of Neurosciences (Grenoble, France): Physically plausible trajectories for Compressed Sensing in MRI.
02/16: Workshop on 7 Tesla scanner at NeuroSpin (Gif-sur-Yvette, France) Compressed sensing for high resolution MRI at 7 Tesla.
01/16: Cosmostat lab, IRFU/CEA. On the generation of compressed sampling schemes in MRI.

EuroScipy 2016: scikit-learn tutorial
Budapest BI 2016 : scikit-learn tutorial and talk "Recent developments in scikit-learn and joblib"

PyData Berlin and PyData Paris 2016: "Predictive modeling with Python, trends and tools
invited talk on Some recent developments in Deep Learning researc at Strata London 2016.

Paris Open Source summit 2016: scikit-learn, the vision and the community
EuroScipy 2016 (Erlangen): keynote: "On writing code the science"
Open Data Science Conference 2017 (London): keynote: "The code of data science"
EuroPython 2016 (Bilbao): keynote "Scientists meet web dev: how Python became the language of data"
PiterPy 2016 (St Petersbourg): keynote: "Python for data"
Facebook AI Research: some statistical learning problems in brain imaging
GDR ISIS Imagerie medicale: prediction de pathologies psychiatriques à partir d'imagerie fonctionnelle de repos
Brain network analysis workshop, MICCAI 2016 (Athenes): keynote
Journée Graphes et neuroscience à Marseilles: Machine learning on brain graphes
Séminaire débat sur le Big data en Neuroscience, Lyon
Seminar Max Planck Institute Leipzig: data mining for neuroimaging
Seminar Telecom ParisTech: randomized methods for high-dimensional statistical learning
Séminaire d'équipe Asclepios: Quelques problèmes d'apprentissage sur des images cérébrales

Gaël Varoquaux: Chair of the steering committee, IEEE PRNI
Bertrand Thirion: member of the Committee on Best Practices in Data Analysis and Sharing for the OHBM community.

Philippe Ciuciu: ANR JC, NSERC au Canada, FWO
Bertrand Thirion: ANR, NWO, NSF
Gaël Varoquaux: Membre de la Commission Expertises Scientifiques, (CE23) ANR
Olivier Grisel did 3 days of consulting with the CTO of the Therapixel startup to share expertise on the use of Deep Learning for the predictive analysis of 3D imaging data.

03/16: Involvement in the CEA visiting committee on High Performance Computing.
05/16: Member of a Comité de sélection for hiring an Assistant Professor in Paris-Saclay University (Section 61 of CNU).
06/16: Member of the Inria scientific commission in charge of ranking PhD and post-doctoral applicants as well as delegations of Assistant Professors to Inria.

Leader of the Datasense axis of the Digicosme Labex
Member of the STIC department committee Paris-Saclay University and of the bureau thereof.
DSA Saclay.

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