Paul-Marie Grollemund

Home
Research
Curriculum Vitae
Teaching (fr)

Home

I am an Associate Professor (Maître de Conférences) in Statistics at LMBP (Laboratoire de Mathématiques Blaise Pascal) at UCA (University of Clermont Auvergne). The main axes of my research are Bayesian statistics initiating and developing tailored methodologies, and contributing to theoretical aspects and applied statistics in agronomy, medical science, and cyber security. I am currently Head of the Data Science BUT (Bachelor of Technology) on the Aurillac campus.

Prior to my current position, I was a Research Associate in Statistics and Pathogen Phylodynamics at the Department of Mathematics at Imperial College London under the supervision of Oliver Ratmann. I work on HIV transmission and in particular I am focusing on determining the importance of risk factors in transmission networks and the proportion of HIV introductions into a population by demographic characteristics.

During my first non-tenured position, I did my PhD in the IMAG lab at the University of Montpellier under the supervision of Christophe Abraham, Pierre Pudlo and Meïli Baragatti. The title of my PhD thesis Bayesian Functional Linear Regression, mainly deals with 1) how to sparsely estimate the coefficient function of the Functional Linear Regression model and in particular its support, 2) how to build an informative prior of this model from experts' knowledge and 3) establishing the consistency of this model.

Contact

Name Paul-Marie Grollemund
Position Associate Professor
Responsibility Head of department of Data Science BUT (UCA)
Lab LMBP (Laboratoire de Mathématiques Blaise Pascal),
Université Clermont Auvergne (UCA)
Address IUT Science des Données, 100 Rue de l'Égalité, 15000 Aurillac
Mail paul_marie.grollemund (at) uca.fr

Research

Journal articles & conference papers

Arezki O., Grollemund, P.M., Pinel S. (2026) On the Asymptotic Behavior of the Multi-step Prediction Error for a Nonlinear Random Fields Model with Estimated Coefficients, Methodology and Computing in Applied Probability.pdf
Kioye T.J.K., Grollemund P.M., et al. (2025) Sparse inference in Poisson log-normal model by approximating the L0-norm, Journal of Multivariate Analysis.pdf
Durécu F., Puys M., Chalhoub G., Grollemund P.M. (2025) Evaluation of Machine Learning Intrusion Detection Systems Resiliency to Network Traffic Evolution, SoftCOM 2025.pdf
Durbert A., Grollemund P.M., Atighehchi K. (2025) Biometric Untargeted Attacks: A Case Study on Near-collisions, Information Sciences.pdf
Durbert A., Grollemund P.M., Lafourcade P., Atighehchi K. (2025) Accuracy Limits as a Barrier to Biometric System Security, CODASPY.pdf
Chagnon D., Durbet A., Grollemund P.M., Atighehchi K. (2025) Exploit the Leak: Understanding Risks in Biometric Matchers, ICISSP.pdf
Grollemund P.M., Poupet C., Comte E., Bonnet M., Veisseire P., Bornes S. (2024) A clustering-based survival comparison procedure designed to study the Caenorhabditis elegans Model, Scientific Reports. pdf
Lepoivre M., Laurent C., Martin B., Grollemund P.M., …, Coppa M. (2024) Relationship between milk intrinsic quality scores and the environmental impact scores of dairy farms, Italian Journal of Animal Science.pdf
Grollemund P.M., Lenoir L., Benoit J., Chassard C., Bord C. (2022) Permanova testing and Poisson Log-Normal modelling unravel how two traditional cheeses are distinguished through sorting and verbalization tasks, Food Quality and Preference. pdf
Durbet A., Grollemund P.M., Lafourcade P., Thiry-Atighehchi A. (2022) Near-collisions and their Impact on Biometric Security, Secrypt 2022. pdf
Durbet A., Grollemund P.M., Lafourcade P., Migdal D., Thiry-Atighehchi A. (2022) Authentication Attacks on Projection-based Cancelable Biometric Schemes, Secrypt 2022. pdf
Grollemund P.M., Lafourcade P., Thiry-Atighehchi K., Ticht A. (2020) Proof of Behavior, 2nd Tokenomics Conference on Blockchain Economics, Security and Protocols. pdf
Abraham C., Grollemund P.M. (2020) Posterior Concentration for a Misspecified Bayesian Regression Model with Functional Covariates, Journal of Statistical Planning and Inference. pdf
Le Tacon F., Murat C., Gravier J., Montpied P., Dupouey J.L., Grollemund P.M., Baragatti M. (2019) Evolution of the Périgord black truffle production in the Vaucluse department (France) from 1903 to 1988, Mycorrhiza. pdf
Grollemund P.M., Abraham C., Pudlo P., Baragatti M. (2018) Bayesian Functional Linear Regression with Sparse Step Functions, Bayesian Analysis. pdf Supplementary Material software

Conference resumes & poster

Kioye T.J.Y., Grollemund P.M., Chauvet J., Latouche P. (2026) Multivariate count data modeling using deep neural network, JdS 2026.
Bourlioux M., Grollemund P.M., Arous C., Geneste A., Grizon A. (2026) Méthodes statistiques et de deep learning pour l'analyse de données fonctionnelles issues du spectromètre de masse maldi-tof, JdS 2026.
Arezki O., Pinel S., Grollemund P.M. (2026) Spatial Prediction of Central Europe Humidity Fields: Uncertainty Quantification and AMSE Analysis, ICSTA 2026.
Bourlioux M., Grollemund P.M., Arous C., Geneste A., Grizon A. (2025) Microorganisms identification at strain level: statistical and deep learning methods for analysis of biotyper Maldi-Tof mass spectra, Microbiome Solution Symposium. poster
Michel E., Bourlioux M., Grollemund P.M., …, Chassard C., Delbès C. (2025) A database to predict safety risks of raw milk cheeses from farming practices in climate change context, JOBIM. poster
Kioye T.J.Y., Grollemund P.M., Chauvet J., Chassard C. (2025) Sparse inference in Poisson log-normal model by approximating the L0-norm, CASI (ou/IWSM) 2025.poster
Bonnet M., Poupet C., Diet A., Grollemund P.M., …, Delbès C. (2025) Caenorhabditis elegans, un modèle utilisé pour le criblage de microbiotes fromagers à effet santé, CNRIUT. poster
Lepoivre M., Martin B., Grollemund P.M., …, Chassard C. (2024) Relationship between milk intrinsic quality and the environmental impact of dairy farms, Mountain Livestock Farming Systems Meeting. poster
Bord C., …, Grollemund P.M., Mardon J. (2024) Relevance of a modelling approach to monitor the sensory attributes of blue cheeses during ripening, WDS 2024. poster
Kioye T.J.Y., Grollemund P.M., et al. (2023) Sélection de variables à l'aide d'un critère d'information lissé dans un modèle poisson log-normal, Journées Maths Bio Santé 2023. poster
Kioye T.J.Y., Grollemund P.M., et al. (2023) Sélection de variables à l'aide d'un critère d'information lissé dans un modèle poisson log-normal, JdS 2023.pdf
Bouhadjera F., Baragatti M., Grollemund P.M., et al. (2022) Bayesian functional linear regression estimation, Extension to scalar and categorical covariates, JdS 2022. pdf
Isman M.A., Yao A.F., Grollemund P.M., Ah Pine J. (2022) Modèle de régression et prévision de séries temporelles pour la demande en électricité à Djibouti, JdS 2022. pdf
Lepoivre M., Coppa M., Grollemund P.M., et al. (2022) Évaluation multicritère des fermes laitières selon la qualité physico-chimique de leur lait estimé par spectroscopie et leurs impacts environnementaux estimés par CAP2ER, J3R 2022. pdf
Grollemund P.M., Ratmann O., Herbeck J., et al. (2019) Preliminary report of high rates of external infection sources for newly HIV-1 diagnosed heterosexual men and women in Seattle and King County, USA, HIV D&E 2019. poster abstract
Grollemund P.M., Abraham C., Baragatti M. (2018) Bayesian Linear Regression on Function Data, ISBA 2018. poster
Grollemund P.M., Abraham C. (2018) Posterior Consistency for Bayesian Functional Linear Regression using Wald Approach, JdS 2018. pdf
Grollemund P.M., Abraham C., Baragatti M. (2017) Bayesian approach using expert's opinion, JdS 2017. pdf
Grollemund P.M., Abraham C., Pudlo P., Baragatti M. (2016) Bayesian linear functional regression with sparse step function.International Conference on Computational Statistics ,(COMPSTAT). pdf
Grollemund P.M., Abraham C., Baragatti M., Pudlo (2015) Interpretable Bayesian Functional Linear Regression, JdS 2015. pdf

Submitted papers & resumes

Durecu F., Puy M., Grollemund P.M., Chalhoub G. (2026) An Evaluation Methodology for Online Machine-Learning Intrusion Detection Models, DIVMA 2026.
Kioye T.J.K., Grollemund, P.M., Chauvet J., Chassard C. (2025) Sparse Poisson Log Normal Model for Zero-Inflated Multivariate Count Data.

Unpublished works

Isman M.A., Yao A.F., Grollemund P.M., Ah Pine J. (2023) Time series forecasting for Djibouti electricity demand.
Bord C., Theil S., Grollemund P.M., …, Chassard C., Delbès C. (2022) Raw milk farm-specific traits outweigh the levelling effects of commercial lactic starter on the microbiological and sensory characteristics of uncooked pressed cheeses.
Grollemund P.M., Tordoff D., Hall M., Kerani R., Herbeck J., Ratmann O. (2019) A Bayesian non-parametric approach to estimate the proportion of external introductions of HIV in local populations with viral sequence data.
Grollemund P.M., Abraham C., Baragatti M. (2019) Bayesian Approach using Expert's Opinion: Impact of Rainfall on Production of Périgord Black Truffles. pdf

Fundings

Bourse de stage de M2, IUT Clermont Auvergne, 2024, 2025 and 2026, 3k–4k€/year, principal investigator.
CAP 20-25 Programme DATA, 2024, PhD grant, MSc internship + PhD student, participant with Chalhoub G. and Puys M.
Impulsion VetAgroSup, Santé Globale 2023, 8k€, participant with Mardon J. (PI) and Bord C.
Plan de relance, ANR (2021–2022), 160k€, participant with Lafourcade P., David C. (PI), 4.71 Company.
CAP 20-25 DATA Program & CIRAA (2022–2025), two half-grants for a PhD student, principal investigator with Chassard C., Chauvet J. and Theil S.
DECLIC, INSMI (2021–2022), 15k€, principal investigator with Lafourcade P., Tichit A., Atighechi K. and Bu G.
ANR JCJC PRIVABIO (2020–2024), 160k€, participant with Atighehchi K. (PI) and Lafourcade P.
Emergence Program, CAP 20-25, I-Site Clermont Auvergne (2020–2021), 22k€, principal investigator with Bornes S., Druilhet P., Yao A.-F., Veisseire P. and Bonnet M.

Research supervisions

PhD students

Bourlioux Marie [Statistics] (2025–…) Étudier les évolutions paramétriques d'un écosystème microbien, grâce au développement d'un modèle de Poisson Log Normal incluant des covariables fonctionnelles (supervised with Yao A.-F. and Bornes S.).Site Internet
Durécu Florent [Computer Science] (2024–…) Détection d'intrusions informatiques avec des outils d'IA (supervised with Chalhoub G. and Puys M.).
Kioye Togo Jean Yves [Statistics] (2022–2025) Sélection de variables pour le modèle Poisson Log Normal (supervised with Chassard C. and Chauvet J.).Site Internet
Aden Farah Hawa [Statistics] (2022–…) Régression logistique bayésienne avec INLA (supervised with Druilhet P.).
Isman Mohamed Abdillahi [Statistics] (2021–2024) Evolution de la demande en électricité à Djibouti (supervised with Yao A.F. and Ah Pine J.).
Durbet Axel [Crypto-Biometric] (2021–2024) Biometric scheme analysis (supervised with Lafourcade P. and Thiry-Atighehchi K.).Site Internet

Engineers

Mole Kamga Eloise Yollande with 4.71 (2022–2024): Automatisation du calcul du bilan carbone.
Vannaire Alexis with Monkey Factory (2022–2024): Analyse de réseaux de transports en commun.

Internships

Ficat Maxime [BUT2 SD] (2026) Assistant technique à la recherche et la gestion du département
Agbessi Stowe [M1 Statistics] (2026) Implémentation d'une méthode de discrimination de spectres Maldi-Tof.
Bourlioux Marie [M2 Statistics] (2025) Méthodes d'analyse de spectre pour l'identification de micro-organismes.
Remesha Guy Darcy [M2 Statistics] (2024) Etude du microbiote des jeunes ruminants : données de comptage multivariées et sélection de variables.
Yahiaoui Yacine [M2 Statistics] (2022) Détection de la comobilité.
Sarr Assane [M1 Statistics] (2022) Classification via Deep Learning et ajustement du niveau d'anonymisation.
Elissée Corentin [M1 Economics] (2021–2022) Blockchain, cryptomonnaie et monnaies locales (supervised with Lafourcade P. and Tichit A.).
Comte Elise [M2 Statistics] (2021) Modelization and identification impacts of cheese microorganisms on the nematode C. elegans. → now at Montpellier CHU
Vannaire Alexis [M2 Statistics] (2020–2021) GPS tracks analysis to detect eco-friendly behaviors (supervised with Lafourcade P. and Thiry-Atighehchi K.). → now at Monkey Factory
Durbet Axel [M2 Crypto-Biometric] (2021) Biometric scheme analysis (supervised with Lafourcade P., Migdal D. and Thiry-Atighehchi K.).
Doumbia Adama [M1 Statistics] (2021) Sorting analysis via a RShiny App (supervised with Bord C.). → internship at Sanofi Paris
Delavet Tiphaine [DUT2 STID] (2021) Facilitated data acquisition via a RShiny App.
Pousa Staklin Victor [DUT2 STID] (2021) Data augmentation for pose estimation.
Brayat Amaury & Guibert Nathan [DUT2 STID] (2021) Data collection and GPS noise analysis.
Le Hoang Cédric [M1 Computer Science] (2020) GPS tracks and HPC computation (supervised with Lafourcade P. and Thiry-Atighehchi K.).
Raynal Louis [M1 Statistics] (2015) The Bayesian Lasso. → statistician at CHD Vendée

Oral presentations

IUT Symposium, June 21–22, 2023, Aurillac (France)
Holoflux seminar, January 24–25, 2023, Paris (France)
IUT Symposium, July 5–6, 2022, Montluçon (France)
Scientific day of DATA program, June 27, 2022, AgroParisTech, Aubière. poster
Statistics at the summit, March 24, 2022, Rochebrune (France)
AppliBUGS, June 13, 2019, Paris (France)
7th Annual Disease Modeling Symposium, April 24, 2019, Bellevue (Washington, US)
HIV Dynamics & Evolution, March 24, 2019, Cascais (Portugal). poster
Team Seminar (IRHS), March 21, 2019, Angers
Team Seminar (LJAD), March 19, 2019, Nice
Bayesian Statistics in the Big Data Era, November 27, 2018, CIRM, Marseille. poster
Team Seminar (Imperial College London), October 12, 2018, London
2018 ISBA World Meeting, June 24, 2018, Edinburgh. poster
Workshop Miat-Mistea, June 5, 2018, Montpellier
50th Days of Statistics (SFdS), May 31, 2018, Saclay
Seminar of PhD students (IMAG), May 16, 2018, Montpellier
Team Seminar (IRMAR), April 6, 2018, Rennes
RIS Network, March 27, 2018, Paris
Team Seminar (LAREMA), March 26, 2018, Angers
Team Seminar (IMAG), March 22, 2018, Grenoble
Team Seminar (AgroParisTech), March 12, 2018, Paris
Team Seminar (I2M), March 5, 2018, Marseille
Mexico Network (CIRAD), November 17, 2017, Montpellier
Seminar of PhD students (IMAG), October 11, 2017, Montpellier
49th Days of Statistics (SFdS), June 2, 2017, Avignon
Seminar of PhD students (IMAG), April 19 & 26, 2017, Montpellier
Team Seminar (MISTEA), March 27, 2017, Montpellier
Team Seminar AgroParisTech, October 17, 2016, Paris
"Journées Mathinfo", October 3–7, 2016, Mallemort
Satellite CRoNoS Workshop on Functional Data Analysis, August 26–28, 2016, Oviedo (Spain)
"Big data and Agriculture" Workshops, July 7, 2016, Montpellier
Team Seminar (MIAT), January 22, 2016, Toulouse
47th Days of Statistics (SFdS), June 1–5, 2015, Lille
Seminar of PhD students (I3M), May 6, 2015, Montpellier
Team Seminar (MISTEA), May 4, 2015, Montpellier

Workshops & conferences attended

56th Days of Statistics (SFdS), June 2, 2025, Marseille
55th Days of Statistics (SFdS), May 27, 2024, Bordeaux
GT IA UCA, 2023, Clermont-Ferrand
StatLearn, 2023, Montpellier
Bayesian workshop (LMBP), 2022–2023, Clermont-Ferrand
[Remote] Statistiques aux sommets, March 22–24, 2021, Rochebrune
[Remote] AppliBugs, December 17–18, 2020, Paris
SMPGD, January 11–12, 2018, Montpellier
O-Bayes 2017, December 10–13, 2017, Austin Texas
48th Days of Statistics, May 30 – June 3, 2016, Montpellier
8èmes Journées Statistiques du Sud Montpellier, May 28–29, 2016, Montpellier
Workshop: Hypothesis testing and mixtures, April 5, 2016, Toulouse
Thematic month – week 5, February 29 – March 4, 2016, Marseille: Bayesian Statistics and Algorithms
"Bayesian Nonparametric Models" Workshops, January & February 2016, Montpellier
"High dimensional" Workshops, March & April 2015, Montpellier
Study Days in Statistics (SFdS), October 6–10, 2014, Fréjus

Education

[PhD Thesis] Bayesian Linear Regression on Functional Data (2017). pdf abstract

In spring 2014, I finished my Master's Degree in Biostatistics at the University of Montpellier. I then joined the MISTEA laboratory under Christophe Abraham and Meïli Baragatti to develop a Bayesian version of the FLiRTI method — giving sparse estimates of the coefficient of the functional linear regression model. The coefficient is considered sparse when it is null on some intervals and has a simple shape (constant or piecewise linear).
[Master Thesis] A Bayesian alternative to the FLiRTI model (2014).

In spring 2013, during the second half of my Master's Degree in Biostatistics, I completed a training course supervised by Jean-Marc Lemaitre and Jean-Michel Marin, in collaboration with Romain Desprat and Vincent Coulon. The goal was to investigate a statistical link between the G-quadruplex DNA sequence pattern and DNA replication initiation sites.
[MSc Report] The influence of the G-quadruplex pattern in DNA replication (2013).

Community

Reviewer for the following journals/conferences: Algotel, Biology Letters, Anals of Applied Statistics, International Journal of Technologies in Higher Education, Bioinformatics (Oxford University Press)
Member of organising committee of the 57th Days of Statistics, June 2026
Member of organising committee of the 25th Lactic Acid Bacteria Club Symposium, May 2026
Elected member of the board of the "Bayesian Statistics" Specialized Group, Société Française de Statistique, June 2024
Meet & Greet with high school students, Montpellier, October 23, 2017
Speaker at the "Science Festival", Montpellier, October 9, 2017
Co-organizer of the 5th meeting "Young Statisticians – Guest Lecturers", 48th Days of Statistics, Montpellier, 2016
Organizer of the workshop "Bayesian Nonparametric Models", 2016
Co-organizer of the seminars of PhD students (IMAG), 2016

Curriculum Vitae

CV (FR)
CV (ENG) [deprecated]

Teaching (fr)

Article

Grollemund P.M., Jacq C., Thiry-Atighehchi K. (2022) Enseignement de la sécurité des données individuelles en STID, RESSI 2022. pdf

Programme du BUT STID

Ci-dessous, le programme du BUT STID avec les principales ressources pédagogiques développées. Sera mis à jour au fur et à mesure des prochaines années.

Semestre 1
Statistique descriptive 1 poly
Statistique descriptive 1 – bivarié
Probabilités 1
Semestre 2
Statistique inférentielle
Statistique descriptive 2 poly
Probabilités 2
Semestre 3
Séries chronologiques poly
Test d'hypothèses
Semestre 4
Méthodes factorielles
Classification automatique
Modèle linéaire
Semestre 5
Data mining
Modélisation statistique avancée
Semestre 6
Méthodes statistiques pour le Big Data
Apprentissage statistique pour l'IA

Package R : STID

Il s'agit d'un package ayant vocation à être utilisé par les étudiants du BUT STID lors de leur formation, ainsi que de les suivre dans leur utilisation future de R.

Pour installer et utiliser ce package :

Cloner le git depuis l'URL https://forge.uca.fr/projects/stid_rpackage
Installer le package via le source

Ce package est en cours de construction. Il se peut donc que 1) le source en .tar.gz ne soit pas disponible (il faut alors construire le package) et 2) que les fonctions du package n'en soient pas à leur état final.

Merci aux contributeurs, dont la plupart sont des étudiants du DUT/BUT STID d'Aurillac :

Maeva Paradis, enseignante au DUT/BUT STID
Arthur Alvarez, stage de 2ème année (DUT STID)
Axel Bellon, Adin Bartoli, Nizar Chehaibou, Théo Court et Curtis-William Isandambo, projet tutoré de 1ère année (DUT STID)