Email : giulia.marchello@inria.fr
I am a PhD student at the Côte d’Azur University in the MAASAI (Models and Algorithms for Artificial Intelligence) research team of Inria and the J. A. Dieudonné laboratory. I work under the supervision of Prof. Charles Bouveyron and Dr. Marco Corneli on the statistical analysis of dynamic bipartite networks with applications to pharmacovigilance.
I obtained a Master Degree in Statistics for Finance and Economics from the University of Perugia in 2020 and a Bachelor Degree in Business Administration from University of Salento in 2017.
My research interests include:
- Network analysis: stochastic block models (SBM), latent block model (LBM), dynamic bipartite networks
- Heterogeneous data
- Time series analysis
- Applications in medicine
Publications
Journals:
Marchello, G., Fresse, A., Corneli, M., C. Bouveyron. Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance. Stat Comput 32, 41 (2022). https://doi.org/10.1007/s11222-022-10098-y
G. Marchello, M. Corneli, and C. Bouveyron (2023). A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices. In revision at Journal of Computational and Graphical Statistics. [pdf]
Conferences:
G. Marchello, M. Corneli, C. Bouveyron. Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM. European Symposium on Artificial Neural Networks (ESANN), October 2023, Bruges (Belgium).
G. Marchello, M. Corneli, C. Bouveyron. A Deep Dynamic Latent Block Model for the Co-clustering of Zero-Inflated Data Matrices. ECML PKDD, September 2023, Turin (Italy).
G. Marchello, M. Corneli, C. Bouveyron. A deep dynamic co-clustering model for Zero-inflated streams of count data. Working group on Model-Based clustering, July 2023, Pittsburgh (Pennsylvania).
G. Marchello, M. Corneli, C. Bouveyron. A deep dynamic co-clustering model for Zero-inflated streams of count data. 54émes Journées de Statistique (JdS), July 2023, Brussels (Belgium).
G. Marchello, M. Corneli, C. Bouveyron. A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Count Data Matrices. 24th International Conference on Computational Statistics, August 2022, Bologna (Italy).
G. Marchello, M. Corneli, C. Bouveyron. Co-clustering of evolving count matrices in pharmacovigilance with the dynamic latent block model. 53émes Journées de Statistique (JdS), June 2022, Lyon (France).
G. Marchello, M. Corneli, C. Bouveyron. A Dynamic Latent Block Model for Co-clustering of Count Data Streams. Working group on Model-Based clustering, October 2021, Athens (Greece).
G. Marchello, A. Fresse, M. Corneli, C. Bouveyron. Co-clustering of evolving count matrices in pharmacovigilance with the dynamic latent block model. ICLR 2021 – Workshop AI for Public Health, May 2021, Virtual Conference (formerly Vienna), Austria. [pdf]
G. Marchello, M. Corneli, C. Bouveyron. The dynamic latent block model for sparse and evolving count matrices. ICML Workskshop Artemiss (2020). [pdf]
G. Marchello, M. Corneli, C. Bouveyron. The dynamic latent block model for the co-clustering of evolving binary matrices. 52èmes Journées de Statistique (JdS) (2020).
