Beatrice (Bea) Franzolini

E-mail: beatrice.franzolini@unimib.it and beatrice.franzolini@unibocconi.it
I am an Assistant Professor of Statistical Sciences at the University of Milano-Bicocca.

Below you can find recent news, upcoming talks, publications, teaching material, and more about my background and research interests.

A full pdf version of my CV is available here.

Upcoming Talks and Conferences

NORDSTAT - June 2026, Helsinki, Finland. I will present the work on complexity bounds for Dirichlet process slice samplers  (joint with F. Gaffi).
IMPMS - June 2026, Palermo, Italy. I will present the work on dynamic network clustering via connectivity pattern persistence and node-level dependence (joint with F. Gaffi).
ISNPS - June 2026, in Thessaloniki, Greece. I will present the work on complexity bounds for Dirichlet process slice samplers  (joint with F. Gaffi).
BAYSM - June 2026, in Chiba, Japan. I will present the works on multivariate species sampling models and Partially exchangeable partitions à la de Finetti: finite and infinite characterizations (joint with A. Lijoi, I. Prünster, and G. Rebaudo).
ISBA - June 2026, in Nagoya, Japan. The 2026 ISBA World Meeting, talk title: TBD.
IFCS - July 2026, in Milan, Italy. I will present the work on learning pathways of life events: a sequential allocation Bayesian model with label tracking (joint with A. Cremaschi, R. Piccarreta).
COMPSTAT - August 2026, in Athens, Greece.. I will present the work on complexity bounds for Dirichlet process slice samplers  (joint with F. Gaffi).

News

I am honoured and happy to have received the 2025 Blackwell-Rosenbluth award for junior researchers in Bayesian statistics based on their overall contribution to the field and to the community.
Vladimir Badalyan was awarded the 2025 Prize for Best Master’s Thesis in Methodological Statistics in memory of Prof. Oliviero Lessi by the Italian Statistical Society for his thesis “Dependent Stick-Breaking Processes with Common Atoms: Properties, Representations, and Inference.”
I am thrilled and honored to have received the 2024 IMS New Researcher Travel Award from the Institute of Mathematical Statistics!
On 5 Feb 2025, I had the honor of giving an ISBA-BNP webinar on random partitions beyond exchangeability. If you miss it, you can watch the recording here: BNP webinar recording link .

Publications

Preprints and submitted articles

  • Franzolini, B. and Pozza, F. (2026). Laplace and skew-Laplace approximations for Dirichlet process mixture posterior density. arXiv:2604.25410 [pdf] [code]
  • Franzolini, B., Lijoi, A., Prünster, I., and Rebaudo, G. (2025). Multivariate species sampling models. arXiv:2503.24004 [pdf] [code]
  • De Iorio, M., Heinecke A., Franzolini, B., and Cabral, R. (2025). Singularity, tails, and hazard rates in Bayesian shrinkage priors.
  • Cremaschi, A., et al. (2025). A Bayesian semi-parametric model for longitudinal growth and appetite phenotypes in children. arXiv:2501.17040
  • Anceschi, N., Fasano, A., Franzolini, B., Rebaudo, G. (2024). Scalable expectation propagation for generalized linear models. arxiv:2407.02128

Refereed research papers

  1. Franzolini, B. and Gaffi, F. (2026).
    Complexity bounds for Dirichlet process slice samplers.
    International Conference on Machine Learning, 2026, accepted.
    [pdf pre print] [code]
  2. Franzolini, B., De Iorio, M., and Eriksson, J. (2026).
    Conditional partial exchangeability: a probabilistic framework for multi-view clustering.
    The Journal of the American Statistical Association, Theory and Methods, in press. DOI: 10.1080/01621459.2025.2609381
    [pdf] [supplement pdf] [code]
  3. Lazarus, M., Franzolini, B., Eriksson, J., Chong, M., Ying, T. J., De Iorio, M., Michael, M., Yap, F., Chong, Y. S., Kee, M., and Fogel, A. (2026).
    Feeding practices and concerns as mediators between maternal mental health and eating behaviours in early childhood.
    Appetite, 217: 108340. DOI:10.1016/j.appet.2025.108340
    [link]
  4. Cremaschi, A., van den Boom, W., Ng, N.B.H., Franzolini, B., Tan, K.B., Yen, J.C.K., Tan, K.H., Chong, Y.-S., Eriksson, J.G., De Iorio, M. (2025).
    Post-partum screening for type 2 diabetes in women with a history of gestational diabetes mellitus: A cost-effectiveness analysis in Singapore.
    Value in Health Regional Issues, 45: 101048. DOI:10.1016/j.vhri.2024.101048
    [link]
  5. Ascolani, F., Franzolini, B., Lijoi, A., and Prünster, I. (2024).
    Nonparametric priors with full-range borrowing of information.
    Biometrika, 111(3): 945–969. DOI:10.1093/biomet/asad063
    [pdf] [code]
  6. Franzolini, B. and Rebaudo, G. (2024).
    Entropy regularization in probabilistic clustering.
    Statistical Methods & Applications, 33(1): 37–60. DOI:10.1007/s10260-023-00716-y
    [pdf] [code]
  7. Franzolini, B., Beskos, A., De Iorio, M., Poklewski Koziell, W., and Grzeszkiewicz, K. (2024).
    Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market.
    The Annals of Applied Statistics, 18(1): 555-584. DOI:10.1214/23-AOAS1801
    [pdf] [code]
  8. Franzolini, B., Cremaschi, A., van den Boom, W., and De Iorio, M. (2023).
    Bayesian clustering of multiple zero-inflated outcomes.
    Philosophical Transactions of the Royal Society A , 381(2247): 20220145. DOI:10.1098/rsta.2022.0145
    [pdf] [code]
  9. Franzolini, B., Lijoi, A., and Prünster, I. (2023).
    Model selection for maternal hypertensive disorders with symmetric hierarchical Dirichlet processes.
    The Annals of Applied Statistics, 17(1): 313-332. DOI:10.1214/22-AOAS1628
    [pdf] [code]

Discussions, short papers, and book chapters
  1. Franzolini, B., Rebaudo, G. (2025). Invited discussion on: “A tree perspective on stick-breaking models in covariate-dependent mixtures” by Horiguchi, A., Chan, C., and Li, M. Bayesian Analysis, 20(3): 1139-1230. DOI: 10.1214/24-BA1462
  2. Catalano, M., Franzolini, B., Giordano, M., Rebaudo, G. (2024). A discussion on: “Sparse Bayesian factor analysis when the number of factors is unknown” by Frühwirth-Schnatter, S., Hosszejni, D., Freitas Lopes, H. Bayesian Analysis, 18(1): 287-366. DOI: 10.1214/24-BA1423 [pdf]
  3. Franzolini, B. (2024). How to leverage Bayesian mixtures for dynamic clustering and classification. In Methodological and Applied Statistics and Demography II: SIS 2024, 73-78. [link] [pdf] [code]
  4. Bondi, L., Franzolini, B., Palma, M. (2024). A longitudinal study of the gender gap in school grades via flexible Bayesian Beta regression. In Methodological and Applied Statistics and Demography III: SIS 2024, 233-238. [link] [pdf]
  5. Franzolini, B., Bondi, L., Fasano, A., and Rebaudo, G. (2023). Bayesian forecasting of multivariate longitudinal zero-inflated counts: an application to civil conflict. In Book of Short Papers CLADAG 2023, 465-468. (Editors: Corretto, P., Giordano G., La Rocca, M., Parrella, M. L., Rampichini, C.) ISBN 9788891935632 [book] [pdf]
  6. Fasano, A., Anceschi, N., Franzolini, B., and Rebaudo, G. (2023). Efficient computation of predictive probabilities in probit models via expectation propagation. In Book of Short Papers CLADAG 2023, 449-452. (Editors: Corretto, P., Giordano G., La Rocca, M., Parrella, M. L., Rampichini, C.) ISBN 9788891935632 [book] [pdf] [code]
  7. Fasano, A., Anceschi, N., Franzolini, B., and Rebaudo, G. (2023). Efficient expectation propagation for posterior approximation in high-dimensional probit models. In Book of Short Papers SIS 2023, 1133-1138. (Editors: Chelli, F. M., Ciommi, M., Mariani, F., Recchioni, M. C.) ISBN 9788891935618 [book] [pdf] [code]
  8. Rebaudo G., Fasano, A., Franzolini, B., and Müller, P. (2023). A discussion on: “Evaluating sensitivity to the stick-breaking prior in Bayesian nonparametrics” by Giordano, R., Liu, R., Jordan M. I. and Broderick T. Bayesian Analysis, 18(1): 287-366. DOI: 10.1214/22-BA1309 [pdf]
  9. Franzolini, B. and Rebaudo, G. (2022). A regularized-entropy estimator to enhance cluster interpretability in Bayesian nonparametrics. In Book of Short Papers SIS 2022, 387-397. (Editors: Balzanella, A., Bini, M., Cavicchia, C. and Verde, R.) ISBN 9788891932310 [book] [pdf]
  10. Ascolani, F., Franzolini, B., Lijoi, A., and Prünster, I. (2021). On the dependence structure in Bayesian nonparametric priors. In Book of Short Papers SIS 2021, 1219-1225. (Editors: Perna, C., Salvati, N. and Schirripa Spagnolo, F.) ISBN 9788891927361 [book-part1] [book-part2] [pdf]
PhD Thesis
  • Franzolini, B. (Advisors: Lijoi, A., and Prünster, I.), Feb 2022. On Dependent Processes in Bayesian Nonparametrics: Theory, Methods, and Applications. Bocconi University [pdf - high quality] [pdf - compressed]

Teaching

TEACHING MATERIALS
You are free to use this material as you wish; citation to the original files is highly appreciated.
Any typos or inaccuracies can be reported to me by email and would be greatly appreciated.
  • Introduction to Network Data Analysis
    These materials include an introductory lecture on network data analysis, lasting approximately 120 minutes (definitions, descriptive statistics, and stochastic block models) provided as PDF slides (with TeX sources), and a 60-minute R exercise.
    [Slides] [TeX sources] [Exercise in R]


    • COURSES
    @ UniMiB
    Statistics I (BSc) - Course Director - a.y. 2025-26
    Inference Principles (MSc) - Course Director - a.y. 2025-26
    @ Bocconi University
    Bayesian Statistical Methods (MSc) - Course Director - a.y. 2023-24, 2024-25, 2025-26
    Statistics (BSc) - Lecturer - a.y. 2019-20, 2020-21
    Financial Econometrics and Empirical Finance (MSc) - Lecturer - a.y. 2020-21
    Statistics (BSc) - Teaching Assistant - a.y. 2018-19
    Financial Econometrics and Empirical Finance (MSc) - Teaching Assistant - a.y. 2018-19, 2019-20
    @ Universita' Cattolica Del Sacro Cuore
    Statistics (BSc) - Teaching Assistant - a.y. 2019-2020

    About me

    A full pdf version of my CV is available here.

    I am an Assistant Professor of Statistical Sciences (Italian RTT) at the Department of Economics, Management and Statistics (DEMS), at the University of Milano-Bicocca (UniMiB).


    My research lies in Bayesian statistics and probabilistic models, with a primary focus on nonparametric methods for complex and structured data.

    In particular, I am interested in:

    • dependent random probability measures
    • random partitions and generalized exchangeability
    • dynamic and high-dimensional models
    • computational methods for scalable Bayesian inference


    I completed my PhD in Statistics in 2022 at Bocconi University (Italy), under the supervision of Antonio Lijoi and Igor Prünster.
    After my PhD, I was a Research Fellow at A*STAR and a member of the Division of Biomedical Data Science (BiDS), led by Maria De Iorio, at the National University of Singapore (NUS).
    In mid 2023, I returned to Italy, where I was until recently a Junior Assistant Professor (RTDA) at the Bocconi Institute for Data Science and Analytics, Bocconi University.
    I served on the board of the Junior Section of ISBA (j-ISBA) in 2023 and 2024 (Chair in 2024), and I am currently a member of the Board of Directors of the International Society for Bayesian Analysis (ISBA).