Linda Mhalla
EPFL SB MATH
MA A1 417 (Bâtiment MA)
Station 8
1015 Lausanne
+41 21 693 74 43
Office:
MA A1 417
EPFL › SB › MATH › MATH-GE
Website: https://math.epfl.ch/
EPFL SB MATH
MA A1 417 (Bâtiment MA)
Station 8
1015 Lausanne
+41 21 693 74 43
Office:
MA A1 417
EPFL › SB › SB-SMA › SMA-ENS
Website: https://sma.epfl.ch/
EPFL SB MATH
MA A1 417 (Bâtiment MA)
Station 8
1015 Lausanne
+41 21 693 74 43
Office:
CM 1 618
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDMA-ENS
EPFL SB MATH
MA A1 417 (Bâtiment MA)
Station 8
1015 Lausanne
+41 21 693 74 43
Office:
CM 1 618
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDMS-ENS
Website: https://go.epfl.ch/edms
Expertise
Statistical consulting.
Mission
Selected publications
Causality and extremes
Linda Mhalla, Valérie Chavez-Demoulin
Published in Handbook on Statistics of Extremes in 2026
A Review of Applications of Extreme Value Theory to Environmental Risk Assessment
Linda Mhalla
Published in Environmental Modelling with Contemporary Statistics: Learning, Directionality, and Space-Time Dynamics in 2026
Causal Discovery in Multivariate Extremes: A Study of Swiss Hydrological Catchments
Linda Mhalla, Valérie Chavez-Demoulin, Philippe Naveau
Published in Environmetrics in 2025
Bayesian space-time gap filling for inference on extreme hot-spots: an application to Red Sea surface temperatures
Linda Mhalla
Published in Extremes in 2021
Causal mechanism of extreme river discharges in the upper Danube basin network
Linda Mhalla
Published in Journal of the Royal Statistical Society: Series C (Applied Statistics) in 2020
Extremal connectedness and systemic risk of hedge funds
Linda Mhalla
Published in Journal of Applied Econometrics in 2020
Teaching & PhD
Courses
Applied statistics
MATH-516
The course will provide an overview of everyday challenges in applied statistics through case studies. Students will learn how to use core statistical methods and their extensions, and will use computational and problem-solving tools to provide reproducible solutions for the problems presented.
Bioinformatic Analysis of RNA-sequencing (Spring)
BIO-693(b)
This course will take place at EPFL in June 2026, from 8th to 12th, in room AAC 137. It introduces the workflows and techniques that are used for the analysis of bulk and single-cell RNA-seq data. It empowers students to understand and analyze their own data.
Probability and statistics
MATH-131
The course introduces the basic notions of probability and statistical inference, with an emphasis on the main concepts and the most commonly used methods.
Risk and environmental sustainability
MATH-383
This course gives an introduction to the assessment of risk with a particular focus on modelling of rare events, which can have huge environmental impacts.
Statistical computation and visualisation
MATH-517
The course will provide the opportunity to tackle real world problems requiring advanced computational skills and visualisation techniques to complement statistical thinking. Students will practice proposing efficient solutions, and effectively communicating the results with stakeholders.
Statistical consulting and collaborations
MATH-663
Analyzing data for a collaborator or client is very different from working on your own research project ; not only do you need competences in statistics, you must also ensure good communication (both ways) in a multi-disciplinary environment, coordination of the work, and the management of everyone.