Nina Miolane

I am a Ph.D candidate on Geometric Statistics for Medical Image Analysis, at Inria Asclepios Team and Stanford University, under the supervision of Xavier Pennec and Susan Holmes.

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
  • Emails: nina.miolane at nmiolane at
  • Phones: + 33 6 33 55 62 02/ +1 650 656 6678



  • Miolane, N., Holmes, S., Pennec, X.: Topologically constrained template estimation via Morse-Smale complices allows to control its statistical consistency. (Submitted, 2016).
  • Miolane, N., Holmes, S., Pennec, X.: Template organ shape estimation in Computational Anatomy: Correcting an asymptotic bias (Submitted, 2016).
  • Miolane, N., Pennec, X.: Computing bi-invariant pseudo-metrics on Lie groups for consistent statistics. Entropy, 17(4), 1850–1881 (Apr. 2015).
  • Darmante, H., Bugnas, B., Dompsure, R.B.D., Barresi, L., Miolane, N., Pennec, X., de Peretti, F., Bronsard, N.: Analyse biometrique de l'anneau pelvien en 3 dimensions – a propos de 100 scanners. Revue de Chirurgie Orthopedique et Traumatologique 100 (7, Supplement), S241 – (Nov. 2014).
  • Miolane, N., Pennec, X., Holmes, S.: Miolane, N., Pennec, X., Holmes, S.: Quantifying and correcting the inconsistency of the mean shape estimation (Submitted, 2016).
  • Miolane, N., Pennec, X., Holmes, S.: Toward a unified geometric Bayesian framework for template estimation in Computational Anatomy. World Meeting of the International Society for Bayesian Analysis (June 2016). (Young Researcher Travel Award).
  • Miolane, N., Pennec, X.: Biased estimators on Quotient spaces. 2nd International Conference on Geometric Sciences of Information (Oct. 2015). (Oral presentation).
  • Miolane, N., Pennec, X.: A survey of mathematical structures for extending 2D neurogeometry to 3D image processing. Medical Computer Vision Workshop, 18th International Conference on Medical Image Computing and Computer Assisted Intervention (Oct. 2015).
  • Miolane, N., Pennec, X.: Statistics on Lie groups : A need to go beyond the pseudo-Riemannian framework. 34th International Workshop on Bayesian Inference and Maximum Entropy Methods (Sept. 2014). (Oral presentation)


  • Miolane, N.: Statistics on Lie groups: can we obtain a consistent framework with pseudo-Riemannian metrics? Workshop on Geometrical Models in Vision, Institut Poincare, Paris (Oct. 2014) (Poster).
  • Miolane, N., Khanal, B.: Statistics on Lie groups for Computational Anatomy. Video for the Educational Challenge of the 17th International Conference on Medical Image Computing and Computer Assisted Intervention, MIT Boston (Sept. 2014) (1st Popular Prize).
  • Miolane, N.: Defining a mean on Lie groups. Master Thesis. Imperial College London and INRIA Asclepios Team (Nov. 2013)

Research interests

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


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


  • Young Researcher Travel Award, International Society for Bayesian Analysis (2016).
  • Ranked 1st/7, Inria@SiliconValley Postdoctoral Fellowship (2016)
  • First Prize at MICCAI Educational Challenge, MIT, Boston (2014).
  • Applied Sciences Visiting Researcher Fellowship, France-Stanford Center for Interdisciplinary Studies (2014).
  • Ranked 1st/50, PhD Scholarship, INRIA S-Cordi (2013)


  • 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.

Useful links

  • Github:
  • LinkedIn:
  • Dblp:
  • Asclepios Team, INRIA:
  • Department of Statistics, Stanford University:
  • Susan Holmes Lab: