• In case you are interested in a PhD/Post doctoral position in high-dimensional statistics, federeated learning, graphs and networks.... please reach out to me!

    I am a Lecturer (Chargé de cours) at UCLouvain working at the Institute of Statistics, Biostatistics and Actuarial Sciences within LIDAM at the Faculty of Science.

    Prior to moving at UCLouvain, I held a Visiting professor position at Ghent University affiliated with the Department of Applied Mathematics, Computer Science and Statistics within the Faculty of Sciences and a Postdoctoral position at KU Leuven affiliated with the ORSTAT department within the Faculty of Economics and Business.

    My research focuses on: Models for high-dimensional data, Probabilistic graphical models, Social network models, Copula models and Information criteria.

List of publications

Technical reports

Pircalabelu, E.

WB-graphs: a within versus between group similarity interplay. (Under review)


Nezakati, E. & Pircalabelu, E. (2023)

Estimation and inference in sparse multivariate regression and conditional Gaussian graphical models under an unbalanced distributed setting. Electronic Journal of Statistics. Accepted.


Book chapters

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Research team

Mengxue Li

Mengxue is a Ph.D. student at the Institute of Statistics, Biostatistics and Actuarial Sciences of UCLouvain since 2022. She obtained her Master's degree in Statistics from Shandong University, China. Her main research interests lie in modeling of spatio-temporal data, probabilistic graphical models and network analysis. Currently, she is working on modeling and analysis of time-varying brain functional networks. Jointly supervised with Rainer von Sachs (main supervisor).

Lise Léonard

Lise is a PhD student and teaching assistant in statistics at the Institute of Statistics, Biostatistics and Actuarial Sciences at UCLouvain. She received her Bachelor's degree in mathematical sciences from the Université libre de Bruxelles, and her Master's degree in Statistics from UCLouvain. In her research, Lise develops inference tools for high-dimensional models. She is currently working on inference for model-averaging estimators based on the desparsified LASSO estimator. Jointly supervised with Rainer von Sachs.

Lara Wautier

Lara is a Ph.D. student and a teaching assistant at the Institute of Statistics, Biostatistics, and Actuarial Sciences at UCLouvain. She holds a bachelor's degree in economics and a master's degree in data science with a focus on statistics from UCLouvain. Her Ph.D. thesis focuses on conditional independence modeling, specifically on extending the estimation of probabilistic graphical models when data from multiple financial series are present in the analysis. Jointly supervised with Christian Hafner.

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Past PhD theses

Ensiyeh Nezakati (2023). Distributed estimation and inferential tools for graphical models.

Alexandre Jacquemain (2023). Lorenz regressions.

Jointly supervised with Cédric Heuchenne (main supervisor)

Thesis in 180 sec: https://www.youtube.com/watch?v=TWXcuK3QVSE&ab_channel=LIDAMResearchInstitute

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R packages

Some R packages accompanying the papers are available for free download.

This software comes as it is. No guarantee whatsoever is given. The author(s) cannot be held responable for any misunderstanding, incorrect use, false scientific conclusions or other problems using these programs. In case bugs are discovered, please feel free to contact me.

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Service to the profession


We are in full preparations for the 30th Annual Meeting of the Royal Statistical Society of Belgium .. The website of the conference is here. Looking forward to seing you in Louvain-la-Neuve!.

I am currently in charge of organizing the regular Statistical/Econometrics seminars at ISBA . A list of the upcoming seminars can be found here .

As part of the open-science paradigme that UCLouvain strongly believes in, I am currently together with other colleagues at UCLouvain, developing the RShiny@UCLouvain platform that will host didactical apps created in Shiny for classroom usage.

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One-week-ahead predictions

COVID - 19

To contribute to the understanding of the effect of the spread of the COVID-19 virus on the health care system in Belgium, I have developed a SHINY app that predicts one day ahead the amount of hospitalized and ICU patients, as well as the total number of deaths as a result of the virus.
https://eugenpircalabelu.shinyapps.io/covid19-forecasting .

More on the subject here: https://uclouvain.be/fr/instituts-recherche/lidam/actualites/how-can-we-predict-the-evolution-of-covid-19-in-belgium.html .

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Get in Touch


Room d.125, 1st floor; Voie du Roman Pays 20, 1348 Louvain-la-Neuve, Belgium