# Research

In my (short, I have to say) research activity I’ve mainly focused in developing tools and methodologies pertaining, broadly speaking, to the cluster analysis realm.

More specifically I am particularly interested in the density-based formulation of the clustering problem both from a model-based (parametric) and from a modal (nonparametric) standpoint.

During my PhD I’ve been lucky enough to work on theoretical as well as application-motivated issues. My recent works thus include nonparametric density estimation when considered as a tool for the final purpose of grouping the data at hand, ensamble clustering approaches and simultaneous clustering of subjects and variables when dealing with time-dependent observations.

Currently I’m working with Prof. Brendan Murphy on some high-dimensional problems arising in the framework of the VistaMilk project.

### Interests

- Clustering
- Density estimation
- Nonparametric tools
- Latent variable models
- Time-dependent data
- Dimensionality reduction

# Publications

## Working Papers

- Casa, A., Bouveyron, C., Erosheva, E. & Menardi, G. (2019+).

*Co-clustering of time-dependent data via Shape Invariant Model*.

## Under Review

- Casa, A., Scrucca, L. & Menardi, G. (2019).

*How bettering the best? Answers via model ensemble in density-based clustering*.

Pre-print available at https://arxiv.org/pdf/1911.06726.pdf - Casa, A. & Menardi, G. (2019).

*Nonparametric semi-supervised classification with application to signal detection in High Energy Physics*.

Pre-print available at https://arxiv.org/pdf/1809.02977.pdf

## Journal Articles

- Casa, A., Chacón, J.E. & Menardi, G. (2020).

*Modal clustering asymptotics with applications to bandwidth selection*.

Electronic Journal of Statistics (in press). Pre-print available at https://arxiv.org/pdf/1901.07300.pdf - Casa, A. (2018).

*On the choice of the weight function for the integrated likelihood*.

SM Journal of Biometrics & Biostatistics, 3(3), 1033.

## Book Chapters

- Cabassi A., Casa, A., Farcomeni, A., Fontana, M., Russo, M. (2018).

*Three testing perspectives on connectome data*.

Studies in Neural Data Science, Springer Volume ‘Proceedings in Mathematics & Statistics’, ISBN-9783030000394.

## Conferences and Workshops

- Casa, A., Chacon, J.E. & Menardi, G. (2019).

*Asymptotics for bandwidth selection in nonparametric clustering*.

CLADAG 2019 - Book of Short Papers. - Casa, A. & Menardi, G. (2019).

*Nonparametric Semisupervised Classification and Variable Selection for New Physics Searches*.

EMS 2019 - Program and Book of Abstracts. - Pascali, G., Casa, A. & Menardi, G. (2019).

*Co-clustering TripAdvisor data for personalized recommendations*.

Book of short papers SIS 2019. ISBN: 978889191510. - Casa, A., Scrucca, L. & Menardi, G. (2018).

*Averaging via stacking in model-based clustering*.

Book of Abstracts of the 4th International Workshop on Model-Based Clustering and Classification (MBC2). - Casa, A., Scrucca, L. & Menardi, G. (2018).

*On the selection uncertainty in parametric clustering.*

Book of Abstracts of the European Conference on Data Analysis (ECDA). - Casa, A., Chacon, J.E. & Menardi, G. (2018).

*On the choice of an appropriate bandwidth for modal clustering*.

Book of short papers SIS 2018. ISBN: 9788891910233. - Casa, A., Chacon, J.E. & Menardi, G. (2018).

*Clustering-oriented selection of the amount of smoothing in kernel density estimation*.

Book of Abstracts ISNPS 2018. ISBN:978-88-61970-00-7. - Casa, A. & Menardi, G. (2017).

*Signal detection in high energy physics via a semisupervised nonparametric approach*.

Proceedings of the Conference of the Italian Statistical Society “Statistics and Data Sciences: new challenges, new generations”. ISBN: 978-88-6453-521-0. - Casa, A. & Menardi, G. (2017).

*Nonparametric semi-supervised classification with application to signal detection in high energy physics*.

Book of Abstracts of the International Federation of Classification Societies (IFCS).