My main research topics are statistical learning methods, biostatistics and machine learning with a particular focus on decision-trees methods and random forests. Since 2020, I have also been studying spatio-temporal modeling and inference and Bayesian methodology, in particular Monte-Carlo methods.

• [2020-20XX] Samir Orujov, co-supervised with Francois Septier (UBS) and Victor Elvira (Univ. Edinburgh, UK), ``On the combination of statistical models and neural networks for time-series modeling''. (supervision rate: 33%)
• [2020-20XX] Yann Guguen, co-supervised with Francois Septier (UBS), ``Statistical Learning and Random Forests for spatio-temporal data''. (supervision rate: 50%)

• [02/2021-06/2021] Mael Le Gal, co-supervised with Charlotte Pelletier (UBS), ``Group variable identification based on the random forests for grouped variables algorithm''.

• [09/2021-08/2022] Ellen Wang, co-supervised with Pierre Lafaye de Micheaux (UNSW Sydney) and J. Jiang (CHeBA, UNSW Sydney), ``Random forests for lacune detection in MRI''.