I am a postdoctoral researcher at the IT University of Copenhagen, where I mainly work with Jes Frellsen.

I received in 2017 my Ph.D. in applied mathematics from Université Paris Descartes. I worked at the MAP5 lab, where I had the chance to be advised by Charles Bouveyron and Pierre Latouche.

My field of research is statistical machine learning, with a particular emphasis on model uncertainty and sparsity. During my Ph.D., I mainly developed new Bayesian model selection methods for high-dimensional data. I also currently work on Bayesian deep learning for bioinformatics.

## Publications and preprints

## 2017

Exact Dimensionality Selection for Bayesian PCA

Preprint HAL-01484099, Université Paris Descartes (2017)

[pdf]

Multiplying a Gaussian Matrix by a Gaussian Vector

Statistics & Probability Letters, vol. 128, pp. 67–70 (2017)

Discussion on the Paper "A Bayesian Information Criterion for Singular Models" by Drton and Plummer

Journal of the Royal Statistical Society: Series B, vol. 79, pp. 370–371 (2017)

## 2016

Globally Sparse Probabilistic PCA

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics

Proceedings of Machine Learning Research, vol. 51, pp. 976–984 (2016)

Proceedings of Machine Learning Research, vol. 51, pp. 976–984 (2016)

Combining a Relaxed EM Algorithm with Occam's Razor for Bayesian Variable Selection in High-Dimensional Regression

Journal of Multivariate Analysis, vol. 146, pp. 177–190 (2016)