Tomas Masák

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tomas.masak@epfl.ch +41 21 693 88 43 https://tmasak.github.io/

Citizenship: Czech

+41 21 693 88 43
EPFL > SB > SB-SMA > SMA-ENS

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

EPFL SB SMA-GE
CM 1 617 (Centre Midi)
Station 10
1015 Lausanne

+41 21 693 88 43
Office: CM 1 617
EPFL > SB > MATH > MATH-GE

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

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Administrative data

Research Interests

Functional Data Analysis - non-parametric estimation of covariance operators for space-time processes Computational Statistics - high-dimensional data, sparsity, iteratively reweighted least squares Compressed Sensing - low-rankness, matrix completion, robust principal component analysis

Education

PhD

Mathematical Statistics

EPFL

2018-

Master of Science

Probability, Mathematical Statistics and Econometrics

Charles University

2014-2017

Bachelor of Science

General Mathematics

Charles University

2011-2014

Teaching & PhD

Teaching

Mathematics

Courses

Linear models

Regression modelling is a fundamental tool of statistics, because it describes how the law of a random variable of interest may depend on other variables. This course aims to familiarize students with linear models and some of their extensions, which lie at the basis of more general regression model

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