I am a maître de conférences (~associate professor) at Université Paris-Saclay in Orsay (south of Paris) in the field of statistics. My main research interests are multiple testing and its applications to biological problems. I am also interested by conformal prediction and mathematical statistics at large.

Previously, I worked as a data scientist on patient and asset flow at Intelligent Locations. Before that, I prepared my PhD in applied mathematics at the Laboratoire de Probabilité, Statistique et Modélisation (LPSM) of Sorbonne Université, under the supervision of Etienne Roquain and Pierre Neuvial.

You can find more information in my Curriculum Vitae (in French).

Research interests

• Multiple testing, FDR and FDP control
• p-value weighting and power optimality
• Discrete multiple testing
• Selective inference, post hoc inference
• Conformal inference
• Applications to omics data

Publications

Published papers

Post hoc false positive control for structured hypotheses, G. Durand, G. Blanchard, P. Neuvial, E. Roquain, Scandinavian Journal of Statistics 47.4 (2020), pp. 1114–1148. Accepted version is on arXiv: arXiv:1807.01470.

Adaptive p-value weighting with power optimality, G. Durand, Electronic Journal of Statistics 13.2 (2019), pp. 3336–3385.

New FDR bounds for discrete and heterogeneous tests, S. Döhler, E. Roquain, G. Durand, Electronic Journal of Statistics 12.1 (2018), pp. 1867–1900.

Performance of epistasis detection methods in semi-simulated GWAS, C. Chatelain, G. Durand, V. Thuillier, F. Augé, BMC Bioinformatics 19.231 (2018).

Fixation probability in a two-locus intersexual selection model, G. Durand, S. Lessard, Theoretical population biology 109 (2016), pp. 75–87.

Preprints

A fast algorithm to compute a curve of confidence upper bounds for the False Discovery Proportion using a reference family with a forest structure, G. Durand, arXiv:2502.03849.

FDR control and FDP bounds for conformal link prediction, G. Blanchard, G. Durand, A. Marandon-Carlhian, R. Périer, arXiv:2404.02542.

DiscreteFDR: An R package for controlling the false discovery rate for discrete test statistics, G. Durand, F. Junge, S. Döhler, E. Roquain, arXiv:1904.02054.

Software

R package sansSouci on GitHub. Post hoc bounds on the number of false positives of any selected set of hypotheses.

R package DiscreteFDR on CRAN. Multiple testing procedures controlling the FDR for p-values with discrete support.

Selected Talks

Contrôle post hoc des faux positifs pour des hypothèses structurées, Séminaire de Statistique du MAP5, November 2024, Paris. Slides.

Contrôle post hoc des faux positifs pour des hypothèses structurées, Séminaire de Probabilités et Statistique de l’IMAG, November 2023, Montpellier. Slides.

Contrôle post hoc des faux positifs pour des hypothèses structurées, Séminaire de probabilités et statistiques du LAMA, March 2021, Champs-sur-Marne. Slides.

Improved post hoc bounds for localized signal, Young Researchers’ Meeting in Mathematical Statistics, September 2018, Paris. Slides.

Optimal data-driven weighting procedure with grouped hypotheses and pi_0-adaptation, Workshop: Post-selection Inference and Multiple Testing, February 2018, Toulouse. Poster.

Tests multiples : généralités, problème du weighting optimal, Journée des thésards ESP, October 2017, Toulouse. Slides.

Adaptive data-driven optimal weighting, Statistique Mathématique et Applications, September 2017, Fréjus. Slides.

Step-up procedure with data-driven optimal weights for grouped hypotheses, Multiple Comparison Procedures, June 2017, Riverside. Slides.

BH procedure using data-driven optimal weights for grouped hypotheses, CMStatistics, December 2016, Sevilla. Slides.

An extension of the Benjamini and Hochberg procedure using data-driven optimal weights with grouped hypothesis, Journées MAS, August 2016, Grenoble. Slides.

Teaching

The details of my teachings are in my Curriculum Vitae (in French). Here you can find some of my course material.

For all my teachings of mathematical statistics:

Essentiels de théorie de la mesure, notes in French.

For the Master 2 Mathématiques & IA:

Introduction to multiple testing, slides in English.

For my Mathematical Statistics teaching at ENSAE:

The textbook, in French.

Work experience

Maître de conférences, Université Paris-Saclay, Laboratoire de Mathématiques d’Orsay, since 2021.

Data Scientist, Intelligent Locations, 2018-2021. Study and simulation of patient and asset flow inside multiple hospital services, software development using Pyton and SQL.

PhD student, Sorbonne Université, 2015-2018. See Education.

Research internship in bioinformatics, Sanofi, under the supervision of Franck Augé, 2015 (6 months).

Research internship in population genetics, Université de Montréal, under the supervision of Sabin Lessard, 2014 (4 months).

Engineer internship, Lipigas, under the supervision of Camilo Muñoz, 2013 (6 weeks).

Teaching internship in elementary schools, Académie de Créteil, under the supervision of Axel Jean, 2011-2012 (7 months).

Education

PhD, LPSM, Sorbonne Université, 2015-2018, Paris. Here is my manuscript (with minor corrections with respect to the TEL repository version) and here are my defense slides.

Master 2 Mathématiques pour les sciences du vivant, Université Paris-Sud (now Université Paris-Saclay), 2014-2015, Orsay.

Diplôme de l’X, École polytechnique, 2011-2015, Palaiseau.