Mohamed NDAOUD

Grade : Doctorant contractuel Ecole Polytechnique

Mail : ndaoudm[arrowbase]gmail.com

ResearchEducationJobsPublicationsTeachingWork in progressOther

Research Interests

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Variable selection, nonparametric estimation, high-dimensional statistics and sparsity, stochastic processes, harmonic analysis, random matrix theory, spiked models.


Biography

Education

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  • 2016 -      : Ecole polytechnique/CREST - PhD in Mathematical Statistics, High-dimensional variable selection, under the supervision of Alexandre Tsybakov

  • 2015 - 2016 : Université Pierre et Marie Curie, Paris 6 - Master 2 « Probabilités et Finance ». Received with highest honors (mention très bien)

  • 2012 - 2015 : Ecole polytechnique (Paris). [Applied Mathematics, Physics]

  • 2010 - 2012 : Lycée Moulay Youssef (RABAT). Classes Préparatoires aux Grandes Ecoles ( MP*)


Jobs

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  •  June 2018 - September 2018 : Twitter HQ San Francisco - Data Science intern, under the supervision of Eugene Quan and Elliott Star.

  • April 2015 - September 2016 : J.P.Morgan London - LINEAR QR intern, under the supervision of David Fellah and Danila Deliya. 

  • April 2014 - September 2015 :  Bloomberg New-York - QR intern, under the supervision of Bruno Dupire.



Publications

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  • Ndaoud, M. Interplay of minimax estimation and minimax support recovery under sparsity. (2018) Accepted at ALT 2019

  • Ndaoud, M., Tsybakov, A. B. Optimal variable selection and adaptive noisy Compressed Sensing. (2018) Submitted

  • Butucea, C., Ndaoud, M., Stepanova, N. A., & Tsybakov, A. B. (2018). Variable selection with Hamming loss. The Annals of Statistics, 46(5), 1837-1875.

  • Ndaoud, M. A New Rate-Optimal Series Expansion of Fractional Brownian Motion. 2015. Submitted

     


Teaching

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  ?

  • High-dimensional Statistics, ENSAE ParisTech, 3rd year (M2), 2016-2017
            TP1: Énoncé Corrigé
            TP2: Énoncé Corrigé
            TP3: Énoncé Corrigé
            TP4: Énoncé Corrigé
            TP5: Énoncé Corrigé
  • Valuation and hedging derivatives, ENSAE ParisTech, 3rd year (M2), 2016-2017
  • Parametric Statistics 2, ENSAE ParisTech, 2nd year (M1), 2016-2017
  • Introduction to financial Mathematics, ENSAE ParisTech, 2nd year (M1), 2016-2017
  • Algebra, ENSAE ParisTech, 1st year (L3), 2016-2017
  • Measure Theory, ENSAE ParisTech, 1st year (L3), 2016-2017

Work in progress

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  • Ndaoud, M., Sharp optimal recovery in the high-dimensional Gaussian mixture model.

  • Ndaoud, M., Minimax optimal adaptive norm estimation.

 

 

 

Other

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Grants:

  • 2016 - 2019 : AMX (Allocation-Moniteur Polytechnique) grant
  • 2012 - 2016 : French Government's Major-Excellence Scholarship

Upcoming events:

  • Meeting in Mathematical Statistics 2018, Frejus, France, December 16th-21th, 2018
  • ALT 2019, Chicago, March 22-24th, 2019

Seminar talks and conferences:


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