Télécom ParisTech

Alexandre Gramfort

Maître de conférences

Alexandre Gramfort

Formation

  • Diplômes d’ingénieur de l’École Polytechnique (X 2001) et de Télécom ParisTech (2006),
  • Doctorat en traitement du signal et des images à l’INRIA Sophia-Antipolis (2009).

Enseignement

  • Traitement du signal,
  • Apprentissage statistique,
  • Optimisation,
  • Applications biomédicales du traitement du signal et des images.

Thématiques de recherche

  • Apprentissage statistique et traitement du signal pour l’analyse des données de neuroimagerie.

Animation scientifique et responsabilités collectives

  • Éditeur associé du journal Frontiers in brain imaging methods,
  • Contributeur aux projets logiciel open-source Scikit-Learn & MNE.

Distinctions

  • Prix de thèse de la “Fondation EADS” (2010),
  • Prix du jeune chercheur à la conférence internationale Biomag (2010).

Principaux Résultats scientifiques

  • A. Gramfort, D. Strohmeier, J. Haueisen, M. Hämäläinen, M. Kowalski, Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations, NeuroImage, 2013.
  • R. Jenatton, A. Gramfort, V. Michel, G. Obozinski, E. Eger, F. Bach, B. Thirion , Multiscale Mining of fMRI data with Hierarchical Structured Sparsity, SIAM Journal on Imaging Sciences, 2012.
  • S. Khan, A. Gramfort, N. Shetty, M. Kitzbichler, S. Ganesan, J. Moran, S. Lee, J. Gabrieli, H. Tager-Flusberg, R. Joseph, M. Herbert, M. Hämäläinen, T. Kenet, Local and long-range functional connectivity is reduced in concert in autism spectrum disorders, Proceedings of the National Academy of Sciences (PNAS) 2013.
  • G. Varoquaux, A. Gramfort, J. Poline, B. Thirion , Brain covariance selection: better individual functional connectivity models using population prior, In proc. Neural Information Processing Systems (NIPS) Conf., 2011.

Education

  • Masters degree in engineering from l’Ecole Polytechnique (x2001) and Telecom ParisTech (2006),
  • PhD in Signal and Image Processing at INRIA Sophia-Antipolis (2009)

Teaching

  • Signal Processing,
  • Machine Learning,
  • Optimization,
  • Biomedical applications of signal and image processing.

Major Research Interest or Current Research Topics

  • Machine learning and signal processing for neuroimaging data analysis.

Visibility, Membership, Committee

  • Associate Editor journal Frontiers in brain imaging methods.
  • Core contributor the Scikit-Learn and MNE open-source software.

Distinction

  • PhD award from the “Fondation EADS” (2010).
  • Young investigator award at Biomag international conference (2010).

Main Scientific Results

  • A. Gramfort, D. Strohmeier, J. Haueisen, M. Hämäläinen, M. Kowalski, Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations, NeuroImage, 2013.
  • R. Jenatton, A. Gramfort, V. Michel, G. Obozinski, E. Eger, F. Bach, B. Thirion , Multiscale Mining of fMRI data with Hierarchical Structured Sparsity, SIAM Journal on Imaging Sciences, 2012.
  • S. Khan, A. Gramfort, N. Shetty, M. Kitzbichler, S. Ganesan, J. Moran, S. Lee, J. Gabrieli, H. Tager-Flusberg, R. Joseph, M. Herbert, M. Hämäläinen, T. Kenet, Local and long-range functional connectivity is reduced in concert in autism spectrum disorders, Proceedings of the National Academy of Sciences (PNAS) 2013.
  • G. Varoquaux, A. Gramfort, J. Poline, B. Thirion , Brain covariance selection: better individual functional connectivity models using population prior, In proc. Neural Information Processing Systems (NIPS) Conf., 2011.