About me

Starting from September 2022, I am Junior Professor in AI for Archaeology and History at Université Côte d'Azur. In collaboration with the researchers of the CEPAM laboratory, my job consists into developping new AI models and algorithms to answer research questions related with the historical/archaeological data. Indeed, this data is very scarse, fragmented and sparse. This is why standard machine and deep learning tools are either not adapted or at least not working out of the box. I am also part of the INRIA research team MAASAI in Sophia-Antipolis as well as member of the LJAD in Nice. I previously worked as researcher at the Center of Modeling, Simulation and Interactions of Université Côte d'Azur (Nice, France). I obtained my PhD in November 2017 at the Université Paris 1 Panthéon-Sorbonne, where I was part of the SAMM laboratory.

My research interests include:

New (!!)

- Our paper Template based Graph Neural Network with Optimal Transport Distances (Vincent-Cuaz et al. 2022) was accepted at NeurIPS 2022
- Our paper A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures (Corneli and Erosheva, 2020) was accepted at the 2022 ISBA world meeting
- Our paper Semi-relaxed Gromov-Wasserstein divergence with applications on graphs (Vincent-Cuaz et al. 2022) was accepted at ICLR 2022
- Our paper DeepLTRS: A deep latent recommender system based on user ratings and reviews (Liang et al.2021) published in Pattern Recognition Letters
- Our paper Online Graph Dictionary Learning (Vincent-Cuaz et al. 2021) was accepted at ICML 2021
- Our paper Co-clustering of evolving count matrices in pharmacovigilance with the dynamic latent block model (Marchello et al. 2021) was accepted at ICLR 2021 – Workshop AI for Public Health

Publications

Preprints

- R. Rastelli and M. Corneli. Continuous Latent Position Models for Instantaneous Interactions (2021): [ArXiv]
- A. Zugarini, E. Meloni, A. Betti, A. Panizza, M. Corneli, M. Gori. An optimal control approach to learning in SIDARTHE epidemic model (2020): [ArXiv]
- L. Vanni, M. Corneli, D. Mayaffre, F. Precioso. From text saliency to linguistic objects: learning linguistic interpretable markers with a multichannel convolutional architecture (2020): [HAL]

Book Chapters

- L. Vanni, M. Corneli, D. Longree, D. Mayaffre and F. Precioso. Key passages : from statistics to deep learning , in D.F. Iezzi, D. Mayaffre, M. Misuraca, Text Analytics - Advances and Challenges, Springer, Ch.4, (2020): [Web]

Journal papers

- D. Liang, M. Corneli, C. Bouveyron, P. Latouche. DeepLTRS: A deep latent recommender system based on user ratings and reviews , Pattern Recognition Letters, Vol. 152, pp. 267-274, Elsevier (2021): [Journal link]
- M. Corneli, C. Bouveyron, P. Latouche. Co-Clustering of ordinal data via latent continuous random variables and a classification EM algorithm , Journal of Computational and Graphical Statistics, Taylor & Francis (2020): [HAL, Journal link]
- L. Bergé, C. Bouveyron, M. Corneli, P. Latouche. The Latent topic block model for the co-clustering of textual interaction data, Computational Statistics and Data Analysis, vol. 137, pp.247-270, Elsevier (2019): [HAL, Journal link ].
- M. Corneli, C. Bouveyron, P. Latouche, F. Rossi. The dynamic stochastic topic block model for dynamic networks with textual edges , Statistics and Computing , pp.1-19, Springer (2018): [HAL , Journal link].
- M. Corneli, P. Latouche, F. Rossi. Multiple change points detection and clustering in dynamic networks. Statistics and Computing, vol. 28, Issue 5, pp 989–1007, Springer (2018): [HAL , Journal link ].
- M. Corneli, P. Latouche, F. Rossi. Exact ICL maximization in a non-stationary temporal extension of the stochastic block model for dynamic graphs. Neurocomputing , vol. 192, pp.81-91, Elsevier (2016): [HAL , Journal link ].
- M. Corneli, P. Latouche, F. Rossi. Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL. Social Network Analysis and Mining , pp. 6:55, Springer (2016): [HAL , Journal link ].

Conference papers

- C. Vincent-Cuaz, T. Vayer, R. Flamary, M.Corneli, N. Courty. Template based Graph Neural Network with Optimal Transport Distances , NeurIPS 2022 : [ArXiv]
- M. Corneli, E. Erosheva. A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures, ISBA world meeting 2022 : [HAL]
- C. Vincent-Cuaz, T. Vayer, R. Flamary, M.Corneli, N. Courty. Semi-relaxed Gromov-Wasserstein divergence with applications on graphs, ICLR 2022 : [ArXiv]
- C. Vincent-Cuaz, T. Vayer, R. Flamary, M.Corneli, N. Courty. Online Graph Dictionary Learning , ICML 2021 : [HAL]
-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. [HAL]
- D. Liang, M. Corneli, P. Latouche, C. Bouveyron. Missing rating imputation based on product reviews via deep latent variable models, ICML Workshop Artemiss (2020) [pdf]
- G. Marchello, M. Corneli, C. Bouveyron. The dynamic latent block model for sparse and evolving count matrices, ICML Workshop Artemiss (2020) [pdf]
- L. Vanni, M. Corneli, D. Longree, D. Mayaffre and F. Precioso. Hyperdeep : deep learning descriptif pour l’analyse de données textuelles,, 15èmes Journées Internationales d’Analyse statistique des Données Textuelles, online proceedings, JADT (2020)

Talks/Posters

Workshop Laboratory LJK, Grenoble, France, Apr 2018.
13th International Conference on Operation Research, Havana, Cuba, March 2018.
Journées YSP (Young Statisticians and Probabilists), Paris, France, Jan 2018.
The 6th International Conference on Complex Networks and Their Applications, Lyon, France, Nov/Dec 2017.
49èmes Journées de Statistique (JdS), Avignon, France, Mai/Juin 2017.
Statlearn, Vannes, France, Apr 2016 (poster).
International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Paris, France Aug 2015 (poster).
47èmes Journées de Statistique (JdS), Lille, France, Juin 2015.
49èmes Journées de Statistique (JdS), Avignon, France, Mai/Juin 2017.
European Symposium on Artificial Neural Networks, Computational Intelligence and ML (ESANN), Bruges, Belgium, Apr 2015.

Teaching

MSc Data Science UCA (since 2018)

  • Basic algebra for data analysis [Lecture notes].
  • Statistical inference.

Licence MIASHS Université Paris 1 (2014-2017)

  • Linear algebra.
  • Statistics and probability.

Ongoing projects

Topix

A new copyrighted technology for co-clustering of interaction data involving text and images

CpDyna

An R/C++ package for change point detection in dynamic graphs (joint work with Margot Selosse)

Software

ordinalLBM: an R package to perform co-clustering of ordinal data (CRAN)
CpDyna: an R/C++ package for change point detection in dynamic graphs (github)

Get In Touch

How to reach me: