Nina Miolane

I am a postdoctoral researcher on Geometric Statistics for Medical Image Analysis, at Stanford (USA) and Inria (France) and a consultant for the start-up Bay Labs.

Contact information

  • Addresses:
Inria, Asclepios Project-Team, Office F224, Bâtiment Fermat, 2004 route des lucioles, 06902 Sophia-Antipolis, France

Stanford University, Department of Statistics, Sequoia Hall, 390 Serra Mall, CA 94305, United States
  • Email: nina.miolane at inria.fr


Publications


Journals

Conferences with peer-reviews

Ph.D Thesis

Others

Research interests

  • Applied Statistics and Machine learning,
  • Riemannian, pseudo-Riemannian and sub-Riemannian geometry,
  • (Organ) shape analysis,
  • (Medical) Image processing,
  • (Medical) Image Analysis.

Reviewer

  • NeuroImage (2014)
  • Journal of Mathematical Imaging and Vision (2015)
  • NIPS conference (2016)

Fellowships

Awards

Background

  • PhD in "Geometric Statistics for Computational Anatomy". Inria, in collaboration with Stanford.
  • MS. in Theoretical Physics "Quantum Fields and Fundamental Forces". Imperial College London, UK.
  • "Diplome d'Ingénieur" and MS. in Mathematics and Theoretical Physics. Ecole Polytechnique, France.

Medias


Newspapers

Radios

TVs

Vulgarisation

Communication on science and scientists

In highschools:

Useful links

  • Github: https://github.com/ninamiolane/
  • LinkedIn: www.linkedin.com/in/ninamiolane
  • Dblp: http://dblp.uni-trier.de/pers/hd/m/Miolane:Nina
  • Asclepios Team, INRIA: https://team.inria.fr/asclepios/
  • Department of Statistics, Stanford University: https://statistics.stanford.edu/
  • Susan Holmes Lab: http://statweb.stanford.edu/~susan/LabIndex.html