University
Assistant Professor, Department of Economics, Management, and Quantitative Methods (2024/02-Ongoing)
University of Milan

Assistant Professor, Department of Mathematics (2021/04-2024/02)
Politecnico di Milano

Teaching Assistant, BSc courses in Statistics and Statistical Methods (2019/02-2021/07)
University of Milano-Bicocca

Postdoctoral research fellow, Department of Statistics and Quantitative Methods (2020/04-2021/03)
University of Milano-Bicocca

Teaching Assistant, BSc course in Statistics (2017/09-2018/02)
Bocconi University

Industry
Freelance data scientist (2020/01-2020/04)
DCG, Milan

Business analyst and planner (2015/09-2016/09)
HP Inc, Barcelona

Visiting periods
Visiting PhD Student (2018/03-2019/03)
Insight Centre for Data Analytics, University College Dublin

Exchange Semester (2014/01-2014/06)
School of Economics and Management, Tilburg University

Articles in refereed journals

1. Benetti, L., Boniardi, E., Chiani, L., Ghirri, J., Mastropietro, M., Cappozzo, A., & Denti, F. (2023)
   Variational Inference for Semiparametric Bayesian Novelty Detection in Large Datasets
   Advances in Data Analysis and Classification (online first)
   link | arXiv | code

2. Cappozzo, A., Ieva, F., Fiorito, G. (2023)
   A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation
   Annals of Applied Statistics 17(4), 3257-3282
   link | arXiv | code

3. Cappozzo, A., García Escudero, L.A., Greselin, F., Mayo-Iscar, A. (2023)
   Graphical and computational tools to guide parameter choice for the cluster weighted robust model
   Journal of Computational and Graphical Statistics 32(3),1195–1214
   link | code

4. Casa, A., Cappozzo, A., Fop, M. (2022)
   Group-wise shrinkage estimation in penalized model-based clustering
   Journal of Classification, 39(3), 648–674.
   link | arXiv | code

5. Cappozzo, A., McCrory, C., Robinson, O. et al. (2022)
   A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events
   Clinical Epigenetics 14, 121
   link | code

6. Cappozzo, A., García Escudero, L.A., Greselin, F., Mayo-Iscar, A. (2021)
   Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling
   Stats 2021, 4(3)
   link | code

7. Denti, F., Cappozzo, A., Greselin, F. (2021)
   A Two-Stage Bayesian Nonparametric Model for Novelty Detection with Robust Prior Information
   Statistics and Computing, 32, 18
   link | arXiv | code

8. Cappozzo, A., Duponchel, L., Greselin, F., Murphy, T.B. (2021)
   Robust variable selection in the framework of classification with label noise and outliers: applications to spectroscopic data in agri-food
   Analytica Chimica Acta, 1153, 338245
   link | arXiv | code | cover

9. Cappozzo, A., Greselin, F., Murphy, T.B. (2021)
   Robust variable selection for model-based learning in presence of adulteration
   Computational Statistics & Data Analysis, 158, 107186
   link | arXiv | code

10. Cappozzo, A., Greselin, F., Murphy, T.B. (2020)
    Anomaly and Novelty detection for robust semi-supervised learning.
    Statistics and Computing, 30, 1545–1571
    link| arXiv | code

11. Cappozzo, A., Greselin, F., Murphy, T.B. (2020)
    A robust approach to model-based classification based on trimming and constraints.
    Advances in Data Analysis and Classification, 14(2), 327-354
    link | arXiv | code

Submitted and working papers

1. Cappozzo, A., Casa, A. (2024+)
   Model-based clustering for covariance matrices via penalized Wishart mixture models
   Submitted
   arXiv | code

2. Caldera, L., Masci, C., Cappozzo, A., Forlani, M., Antonelli, B., Leoni, O., Ieva, F. (2024+)
   Uncover mortality patterns and hospital effects in COVID-19 heart failure patients: a novel Multilevel logistic cluster-weighted modeling approach
   Submitted
   arXiv | code

3. Cappozzo, A., Casa, A., Fop, M. (2024+)
   Sparse model-based clustering of three-way data via lasso-type penalties
   Revision submitted
   arXiv | code

Young Researcher Paper Award (2023/09)
CLADAG 2023 14-th Scientific Meeting Classification and Data Analysis Group
Salerno, Italy

Best poster presentation (2018/09)
MBC² Workshop on Models and Learning for Clustering and Classification
Catania, Italy

Member of the third best team in terms of algorithm predictive accuracy (2017/09)
Young CLADAG - Data science competition
Politecnico di Milano, Italy

Member of one of the four winning teams (2017/06)
Stats Under the Stars 3 - Data science competition
Università degli Studi di Firenze, Italy

Successful participant to HP Business Academy Assessment Week (2015/07)
Hewlett Packard Española and Fundación Universidad-Empresa
Barcelona, Spain

Member of the Italian Statistical Society, its young group y-SIS and the Institute of Mathematical Statistics

Leaf at the Mathematics Genealogy Project. Are you a scholar in math or a related field? You should consider adding your dissertation, and let the branches grow!