Yoav Zemel

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yoav.zemel@epfl.ch +41 21 693 73 38 https://yoavzemel.github.io

+41 21 693 73 38
EPFL > SB > SB-SMA > SMA-ENS

Web site: Web site: https://sma.epfl.ch/

EPFL SB-GE
CM 1 618 (Centre Midi)
Station 10
1015 Lausanne

+41 21 693 73 38
Office: CM 1 618
EPFL > SB > MATH > MATH-GE

Web site: Web site: https://math.epfl.ch/

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Administrative data

Research interests

Geometrical statistics, point processes and shape theory Functional data analysis Optimal transportation

Awards and honours

Second best master poster, 2012 Swiss government scholarship, 2010-2012 EPFL excellence scholarship, 2010-2011 Summa cum laude for the Bachelor, 2010 Participant in workshops for honour students in mathematics and economics, 2009-2010 Hebrew University "Amirim" scholarship, 2008-2010 Hebrew University Deans prize, 2008-2009 Hebrew University Rector prize, 2007-2008

Education

Doctorate

Mathematical statistics

EPFL

2012-2017

Master

Applied mathematics. Thesis title: Optimal Transportation: Continuous and Discrete

EPFL

2010-2012

Bachelor

Mathematics and economics

The Hebrew University of Jerusalem

2007-2010

Publications

Other publications

Journal articles

Panaretos, V. M. and Zemel, Y. (2016) Amplitude and Phase Variation of Point Processes. Annals of Statistics, 44 (2): 771-812. Henshaw, J. M. and Zemel, Y. (2017) A unified measure of linear and nonlinear selection on quantitative traits. Methods in Ecology and Evolution 8 (5): 604–614. Zemel, Y. and Panaretos, V. M. (2016) Fréchet Means and Procrustes Analysis in Wasserstein Space. To appear in Bernoulli. Masarotto, M., Panaretos, V.M., and Zemel, Y. (2018) Procrustes metrics on covariance operators and optimal transportation of Gaussian processes. arXiv:1801.01990

Teaching & PhD

Courses

Analysis IV (for SV, MT)

The course studies the fundamental concepts of complex analysis with a view to their use in solving multidisciplinary problems of scientific engineering.

Probability and statistics

This course teaches the basic concepts of probability theory and statistics, such as inference, testing and regression.

Statistical machine learning

A course on statistical machine learning for supervised and unsupervised learning

Statistical theory

-This course gives a mostly rigourous treatment of some statistical methods outside the context of standard likelihood theory.