In a snapshot

I am professor of Mathematical Statistics (full professor since 2010) at the Université Libre de Bruxelles, where I am affiliated at ECARES and at the Department of Mathematics. I am also an Associate Member of the Toulouse School of Economics. I have been visiting professor at the Université Pierre-et-Marie Curie (2009-2014), in KULeuven (2015), and in Toulouse School of Economics (2015-2016, 2019-). My main research fields are asymptotic statistics, nonparametric inference, and high-dimensional statistics. At the end of 2021, I left the editorial boards of the Annals of Statistics and of the Journal of the American Statistical Association to focus on my new role as the Editor-in-Chief of Bernoulli (2022-2024). I am a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, and an elected member of the International Statistical Institute. I obtained several awards, the most prestigious of them being the Gottfried E. Noether Young Scholar Award (from the American Statistical Association).

Research topics

  • Asymptotic statistics

    Le Cam’s theory of asymptotic experiments plays a key role in many of my papers. Contiguity, local asymptotic normality, convergence of sequences of experiments and their impact, on the construction of optimal statistical procedures are my main interests there.

  • High dimensions

    I recently began working on problems where the number p of variables is large compared to the sample size n. In a hypothesis context, I do not restrict to null (n,p)-asymptotic results, but I also consider asymptotic non-null and optimality issues.

  • Directional statistics

    This topic addresses inference problems involving observations on the p-dimensional unit sphere. This arises in applications where only directions of the observations from a given centre are relevant (so that their distances from this centre may be discarded).

  • Nonparametric statistics

    I have always been interested in nonparametric inference, with special emphasis on hypothesis testing. In this framework, many of my papers developed rank tests for problems belonging to multivariate analysis. Under ellipticity assumptions, we showed that robustness and Le Cam optimality can be combined.

  • Depth-based methods

    Statistical depth measures centrality of a point in the sample space with respect to a probability distribution. In this context, my research focuses on defining new depth concepts and on developing inference methods based on depth.

  • Multivariate quantiles

    Part of my research has been dedicated to the possible extensions of the concept of quantile to the multivariate setup. On the agenda has been the companion problem to define concepts of multiple-output regression quantiles. In both cases, we are after concepts that maintain the strong links between quantiles and statistical depth.

Selected recent publications

(A full list, with download links, is available in my cv)

Konen, D., and P., D. (2023). Spatial quantiles on the hypersphere. Ann. Statist. 51, 2221-2245.

Dürre, A., and P., D. (2022). Affine-equivariant inference for multivariate location under Lp loss functions. Ann. Statist. 50, 2616–2640.

Rasoafaraniaina, J., P., D., and Verdebout, Th. (2022). Preliminary multiple-test estimation, with applications to k-sample covariance estimation. J. Amer. Statist. Assoc. 117, 1904-1915.

Konen, D., and P., D. (2022). Multivariate rho-quantiles: a spatial approach. Bernoulli 28, 1912-1934.

P., D. (2022). On the measure of anchored Gaussian simplices, with applications to multivariate medians. Bernoulli 28, 965-996.

Cutting, Chr., P., D., and Verdebout, Th. (2022). Testing uniformity on high-dimensional spheres: the non-null behaviour of the Bingham test. Ann. Inst. Henri Poincaré Probab. Stat. 58, 567–602.

Garcia-Portugues, E., P., D., and Verdebout, Th. (2020). On optimal tests for rotational symmetry against new classes of hyperspherical distributions. J. Amer. Statist. Assoc. 115, 1873-1887.

P., D., and Verdebout, Th. (2020). Inference for spherical location under high concentration. Ann. Statist. 48, 2982-2998.

P., D., and Verdebout, Th. (2020). Testing for principal component directions under weak identifiability. Ann. Statist. 48, 324-345.

P., D., and Verdebout, Th. (2020). Detecting the direction of a signal on high-dimensional spheres: non-null and Le Cam optimality results. Probab. Theory Related Fields 176, 1165-1216.

Selected awards

  • 2019 ASA Fellowship

    The designation of ASA Fellow has been a significant honor for nearly 100 years. To be selected, nominees must have an established reputation and have made outstanding reputation to statistical science

  • 2018 IMS Fellowship

    TFellows of the Institute of Mathematical Statistics are selected for having proved distinction in research in statistics or probability, by publication of independent work of merit.

  • 2012 Gumbel lecture

    This lecture, that was created in 2006, is a special plenary lecture annually awarded to a young statistician by the German Statistical Association. It is named after the German statistician Emil Julius Gumbel

  • 2007 Junior Noether Award

    Since 2001, the Noether Young Scholar is awarded by the American Statistical Association to a young researcher having “significant accomplishment in nonparametric statistics”

  • 2007 Prix Adolphe Wetrems

    Created in 1926, this price is awarded every year by the Classe des Sciences de l’Académie Royale de Belgique to a researcher “at the origin of a significant and recent scientific progress”

  • 2003 Prix MJLD

    This prize is awarded every three years by the Société Française de Statistique to the best Ph.D. in Statistics defended in a French-speaking university in the previous three years”