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Papers & Manuscripts

(15 first-authored, 5 corresponding authorship, 2 senior-authored)

Manuscripts in Review & Preprints

25. Bargagli Stoffi, F.J., Tortù, C., Forastiere, L. Network Causal Tree: Heterogeneous Treatment and Spillover Effects under Clustered Network Interference. arXiv preprint arXiv:2008.00707.

American Causal Inference Conference Tom Ten Have Award Honorable Mention.

[pdf[preprint] [cite

24. Bargagli Stoffi, F.J., Lee, K., Cadei, R., Dominici, F. Causal Rule Ensemble: An ensemble Learning Approach for Interpretable Discovery of Heterogeneous Subgroups. arXiv preprint arXiv:2009.09036.

Health Effect Institute Jane Warren Award.

[pdf[preprint]​​​​ [cite]

23.  Zorzetto*, D., Bargagli Stoffi*, F.J., Canale, A., Mealli, F., Dominici, F. Bayesian Nonparametrics for Principal Stratification: an Application on Environmental Policies Effects on Health. arXiv preprint arXiv:2302.11656. 



22. Bargagli Stoffi, F.J., De Beckker, K., Maldonado, J. E., & De Witte, K. Assessing Sensitivity of Machine learning Predictions. A Novel Toolbox with an Application to Financial Literacy. arXiv
preprint arXiv:2102.04382. 

[pdf] [preprint] [code] [cite]

21. Bargagli Stoffi, F.J.*, McFarlin, E.*, Castro, E., Schwartz, J., Dominici, F., Amini H. Air Quality Disparities Mapper: An Open-Source Web Application for Environmental Justice.

[preprint available upon request]

20. Bargagli Stoffi*, F.J., Qin*, M., Reidman, D., Fairbank, N., Bennett, L., Butler, K., Braun, D., Dominici, F. Distance Between Schools and Gun Retailers and Risk of School Gun Incidents in the United States. 

[preprint available upon request]

19. Biliotti, C.*, Bargagli Stoffi, F.J.*, Fraccaroli, N., Puliga,M., Riccaboni, M. Breaking Down the Lockdown: A Causal Analysis of Uncertainty and Public Reaction to the First Western COVID-19 Stay-at- Home Mandate. 


18. Chen, K.L., Bargagli Stoffi, F.J., Kim, R., Nethery, R. Estimating Heterogeneous Causal Effects under Bipartite Network Interference: An Application to Air Pollution Regulatory Policies. arXiv preprint arXiv:2304.12500. 


Statistical Methodology (refereed)

17. Bargagli Stoffi, F. J., De Witte, K., Gnecco. G. Heterogeneous Causal Effects with Imperfect Compliance: a Bayesian Machine Learning Approach. The Annals of Applied Statistics, 16 (3), 1986-2009, 2022. Atlantic Causal Inference Conference Tom Ten Have Award Runner Up.

[pdf] [arXiv] [code] [cite

Coverage: [R-bloggers post] [YoungStats post]​

16. Zorzetto, D., Bargagli Stoffi, F.J., Canale, A., Dominici, F. Confounder-Dependent Bayesian Mixture Model: Characterizing Heterogeneity of Causal Effects in Air Pollution Epidemiology. arXiv preprint arXiv:2009.09036. Conditionally accepted at Biometrics.

[pdf] [preprint] [code] [cite]

15. Dominici, F., Bargagli Stoffi, F.J., Mealli, F. From Controlled to Undisciplined Data: Estimating Causal Effects in the Era of Data Science using a Potential Outcome Framework.
Harvard Data Science Review, 3(3), 2021.

[paper] [preprint]

14. Bargagli Stoffi, F.J., Gnecco, G. Causal Tree with Instrumental Variable: An Extension of the Causal Tree Framework to Irregular Assignment Mechanisms. International Journal of Data Science and Analytics, 9, 315–337, 2020.

[paper] [cite]​

13. Bargagli Stoffi, F.J., Cevolani, G., & Gnecco, G. Simple Models in Complex Worlds: Occam’s Razor and Statistical Learning Theory. Minds and Machines, 32(1), 13-42, 2022.

[paper] [cite]

12. Bargagli Stoffi, F.J., Cevolani, G., & Gnecco, G. Should Simplicity Be Always Preferred to Complexity in Supervised Machine Learning? In International Conference on Machine Learning, Optimization, and Data Science (LOD) (pp. 55-59) 2021. Springer, Cham.

[paper] [cite]

11Zorzetto D., Bargagli-Stoffi F.J., Canale A., Dominici F.. Dependent Dirichlet Mixture Pro-
cesses for Causal Inference.
Proceedings of the 36th International Workshop on Statistical Modelling. pp. 618 - 623. 2022.

10Bargagli Stoffi, F.J., Gnecco, G. Estimating Heterogeneous Causal Effects in the Presence of Irregular Assignment Mechanisms. In IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-10), 2018. 

IEEE DSAA Travel Award Paper.

[paper] [preprint] [cite]

Applications (refereed)

9. Li, L., Dominici F., Blomberg, A., Bargagli Stoffi, F.J., Schwartz, J., Coull, B., Spengler, J., Wei, Y., Lawrence, J., Koutrakis, P. Exposure to Unconventional Oil and Gas Development and All-cause Mortality in Medicare Beneficiaries. Nature Energy, 7, 177–185, 2022.

[pdf] [paper] [code] [cite

Coverage: [The Guardian] [Science Daily] [The Hill] [Phys

8. Wasfy, J. H., Bargagli Stoffi, F.J. Assessing the Value of Echocardiography in the Absence of Randomized Trials: How Analytic Techniques from Causal Inference Can Fill the Gap. Journal of the American Society of Echocardiography, 34(6), 582-584, 2021.

[paper] [cite]

7. Bargagli Stoffi, F.J., Riccaboni, M., Rungi, A. Machine Learning for Zombie Hunting. Predicting Distress from Firms’ Accounts and Missing Values. Industrial and Corporate Change, forthcoming.

Credit Scoring and Credit Rating Conference Best Paper Award.

[pdf] [preprint] [cite]

6. Byrne, S., Reynolds, A.P.F., Biliotti, C., Bargagli Stoffi, F.J., Polonio, L., Riccaboni, R. Predicting Choice Behaviour in Economic Games using Gaze Data Encoded as Scanpath Images. Scientific Reports


5. Incerti, F., Bargagli Stoffi, F.J., Riccaboni, M. A Two-Country Study of Default Risk Prediction using Bayesian Machine-Learning. In International Conference on Machine Learning, Optimization, and Data Science (LOD), pp 188–192, 2023.


Statistical Software (refereed)


4. Khoshnevis, N., Cadei, R., Garcia, D., Lee, K., Bargagli Stoffi, F.J. CRE: an R package for
Interpretable Discovery and Estimation of Heterogeneous Treatment Effect. 
Journal of

Open Source Software, 8 (92), 5587, 2023.


Book Chapters (refereed)

3. Bargagli Stoffi, F.J., Niederreiter, J., & Riccaboni, M. Supervised Learning for the Prediction of Firm Dynamics. In Data Science for Economics and Finance (pp. 19-41) Consoli, S., Reforgiato Recupero, D., & Saisana, M. (Eds.), 2021. Springer, Cham.
Most downloaded book from July 2021 to July 2022 among all Springer books in STM (Science and Technology) and in HSS (Human and Social Sciences) of the same period.

[paper] [preprint] [code] [cite]

2. Smet, M., D’Inverno, G., Tierens, H., De Witte, K., & Bargagli Stoffi, F.J. The Effectiveness of the Equal Educational Opportunity Policy (In Dutch, original title: De Effectiviteit van Het GOK-Beleid). In Differences in Education – Striving for Excellence and Equal Educational Opportunities. (pp. 255-276) G. Devos, M. Tuytens (Eds.), 2021. Politeia.


Dissertation (referred)

1. Bargagli Stoffi, F.J. Essays in Applied Machine Learning. Ph.D. Thesis, KU Leuven and IMT School for Advanced Studies, 2020.

Manuscripts in Preparation

6. Bargagli Stoffi, F.J., Dominici, F., Imbens, G., Viviano, D. Spatial Confounding and Bipartite
Graphs. Assessing the Effects of Proximity Between Schools and Gun Retailers on School Gun


5. Bargagli Stoffi, F.J., Garcia, D., Delaney, S., Deziel, N., Bell, M., Dominici, F. Who is most vulnerable? Causal Machine Learning to Assess the Heterogeneous Health Impacts of Extreme Heat Exposure among Elderly Populations in North Carolina and Michigan.

4. Bargagli Stoffi, F.J., Katz-Christy, N., Gu, K., Nethery, R. Data-driven Heterogeneity Detection Among Subgroup-Specific Exposure-Response Functions.

3. Castro, E., Amini, H., Bargagli Stoffi, F.J., Dominici, F., Schwartz, J. Fine-scale Disparities in Exposure to Particulate Matter Components in U.S. Urban Areas.

2. Delaney, S., Mock, L., Mork, D., Cadei, R., Benmarhnia, T., Gill, T., Bell, M., Dominici,
Braun, D., Bargagli Stoffi, F.J., Zanobetti, A.
Data-driven identification of risk factors for hospitalization with ADRD from long-term exposure to fine particulate matter among Medicare


1. Ladant, F.X., Hedou, J., Sestito, P., Bargagli Stoffi, F.J. What is essential is visible to the eye. Saliency in primary school ranking and its effect on academic achievements.

Indicates co-first authorship.

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