Causal AI for Personalized Interventions

• Bargagli Stoffi, F.J., Tortù, C., Forastiere, L. Heterogeneous Treatment and Spillover Effects under Clustered Network Interference. Annals of Applied Statistics, 19(1), 28-55, 2025.

  [paper]

• Zorzetto, D., Bargagli Stoffi, F.J., Canale, A., Dominici, F. Confounder-Dependent Bayesian Mixture Model: Characterizing Heterogeneity of Causal Effects in Air Pollution Epidemiology. Biometrics, 80(2), 2024.

  [pdf] [preprint]

  
  

• Bargagli Stoffi, F. J., De Witte, K., Gnecco. G. Heterogeneous Causal Effects with Imperfect Compliance: a Bayesian Machine Learning Approach. Annals of Applied Statistics, 16 (3), 1986-2009, 2022. 

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

• Zorzetto, D., Canale, A., Mealli, F., Dominici, F., Bargagli Stoffi, F.J., Bayesian Nonparametrics for Principal Statification with Continuous Post-Treatment Variables arXiv preprint arXiv:2302.11656. 

  [preprint]

  
  

• 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]

  
  

Image: “Children of the Sea", Jozef Israels, 1872. Rijksmuseum, Amsterdam, The Netherlands.