Short Bio

I’m Associate Professor of Statistics in the Department of Statistical Sciences of the Università Cattolica del Sacro Cuore, Milan (Italy).

Prior to joining Cattolica University as Assistant Professor in 2016, I was a Post–Doctoral Fellow in the Department of Statistical Sciences at the University of Bologna, where I obtained my Ph.D. in Statistics (2014). I’ve been a Visiting Scholar in the Department of Statistical Sciences of Duke University (2012, USA), in the Statistical and Applied Mathematical Sciences Institute (2014, USA) and in the Faculty of Economics of the University of Zaragoza (2016, Spain).

I’m Associate Editor of Statistical methods & applications. I’m currently member of the Board of Directors of ISBA. Previously, I was treasurer of EnviBayes and Program Chair of j-ISBA. In 2016, I also chaired ySIS, the young section of the Italian Statistical Society.

Research

My research interests focuses on Bayesian inference of spatial and spatio-temporal modeling, graphical modeling and mixture modeling. Real data applications range from ecological and environmental processes to social and life sciences.

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Selected publications

(Full list here)

Argiento R., Filippi-Mazzola E., Paci L. (2024), Model-based clustering of categorical data based on the Hamming distance, Journal of the American Statistical Association, DOI:10.1080/01621459.2024.2402568.

Colombi A., Argiento R., Paci L., Pini A. (2024) Learning block structured graphs in Gaussian graphical models, Journal of Computational and Graphical Statistics, 33, 152-165.

Gasperoni F., Luati A., Paci L., D’Innocenzo E. (2023) Score Driven Modeling of Spatio-temporal Data, Journal of the American Statistical Association, 118, 1066-1077.

Codazzi L., Colombi A., Gianella M., Argiento R., Paci L., Pini A. (2022) Gaussian graphical modeling for spectrometric data analysis, Computational Statistics & Data Analysis, 174, 107416.

Paci L., Consonni G. (2020) Structure discovery of contemporaneous dependencies in graphical VAR models, Computational Statistics & Data Analysis, 144, 106880.

Paci L., Beamonte M. A., Gelfand A. E., Gargallo P., Salvador M. (2020) Spatial hedonic modeling adjusted for preferential sampling, Journal of the Royal Statistical Society: Series A, 183, 169-192.

Finazzi F., Paci L. (2020) Kernel-based estimation of individual location densities from smartphone data, Statistical Modelling, 6, 617-633.

Finazzi F., Paci L. (2019) Quantifying personal exposure to air pollution from smartphone-based location data, Biometrics, 75, 1356-1366.

Canale A., Durante D., Paci L., Scarpa B. (2018) Connecting statistical brains, Significance, 15, 38-40.

Canale, A., Durante, D., Paci, L., Scarpa, B. (Eds.) (2018), Studies in Neural Data Science, Springer Proceedings in Mathematics and Statistics.

Paci L., Finazzi F. (2018) Dynamic model-based clustering for spatio-temporal data, Statistics and Computing, 28, 359-374.

Paci L., Beamonte M. A., Gelfand A. E., Gargallo P., Salvador M. (2017) Analysis of residential property sales using space-time point patterns, Spatial Statistics, 21, 149-165.

Paci L., Gelfand A. E., Beamonte M. A., Rodrigues M., Peréz-Cabello F. (2017) Space-time model for post-fire vegetation recovery, Stochastic Environmental Research and Risk Assessment, 31 (1), 171-183.

Paci L., Gelfand A. E., Cocchi D. (2015) Quantifying uncertainty for temperature maps derived from computer models, Spatial Statistics, 12, 96-108.

Paci L., Gelfand A. E., Holland D. M. (2013) Spatio-temporal modeling for real-time ozone forecasting, Spatial Statistics, 4, 79-93.

Bruno, F., Cocchi, D., Paci L. (2013) A practical approach for assessing the effect of grouping in hierarchical spatio-temporal models, AStA Advances in Statistical Analysis, 97 (2), 93-108.

Preprints

Papers on arXiv

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Teaching

I’m vice program coordinator of the Master of Science in Data analytics for business at the Università Cattolica del Sacro Cuore. In 2024/25, I teach “Statistics” for the BSc in Economics and “Applied linear models” for the MSc in Data analytics for business.

For more info about my courses, see my web-page @Unicatt.