Short bio

I’m a postdoctoral researcher at the Data Science Institute of Hasselt University since December 2020. I did a PhD in Statistics at the University of Louvain under the supervision of Prof. Philippe Lambert. My area of research focuses on Bayesian statistics, computational methods in statistics, and infectious disease modeling. I am particularly interested in the development of new methodologies for fast and flexible inference in statistical models by using Markov chain Monte Carlo algorithms and sampling-free inference schemes with Laplace approximations. I love coding in general and developed several R packages. My latest projects are the EpiLPS package and the EpiDelays package, providing tools to estimate key epidemiological quantities. Selected recent research projects are listed below (full list in my CV).

Selected research projects

[1] Gressani, O. and Hens, N. (2025). Nonparametric serial interval estimation with uniform mixtures.
PLoS Computational Biology, 21(8):e1013338. doi.org/10.1371/journal.pcbi.1013338

[2] Ward, J., Lambert, J.W., Russell, T.W., Azam, J.M., Kucharski, A.J., Funk, S., Quilty, B.J., Gressani, O., Hens, N. and Edmunds, W.J. (2025). Estimates of epidemiological parameters for H5N1 influenza in humans: a rapid review.
BMC Infectious Diseases, 25(1755). https://doi.org/10.1186/s12879-025-11933-z

[3] Gressani, O., Torneri, A., Hens, N. and Faes, C. (2025). Flexible Bayesian estimation of incubation times.
American Journal of Epidemiology, 194(2):490-501. doi.org/10.1093/aje/kwae192

[4] Ward, J., Gressani, O., Kim, S., Hens, N. and Edmunds, W.J. (2025). The epidemiology of pathogens with pandemic potential: A review of key parameters and clustering analysis. Epidemics, 54:100882.
https://doi.org/10.1016/j.epidem.2025.100882

[5] Gressani, O. and Eilers, P.H.C. (2025). Gibbs sampling for Bayesian P-splines. ArXiv preprint.
https://doi.org/10.48550/arXiv.2406.03336