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Umeå University
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Niloofar Moosavi

Contact

E-mail
niloofar.moosavi@umu.se
Phone

Works at

Affiliation
Affiliated as postdoctoral position at Umeå School of Business, Economics and Statistics (USBE) Section: Statistics
Location
Samhällsvetarhuset, Biblioteksgränd 6 Umeå universitet, 901 87 Umeå
Convolutional neural networks for valid and efficient causal inference
Journal of Computational And Graphical Statistics, Taylor & Francis 2024, Vol. 33, (2) : 714-723
Mohammad, Ghasempour; Moosavi, Niloofar; de Luna, Xavier
The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters
Statistical Science, Institute of Mathematical Statistics 2023, Vol. 38, (1) : 1-12
Moosavi, Niloofar; Häggström, Jenny; de Luna, Xavier
Valid causal inference in high-dimensional and complex settings
Statistical studies, 56
Moosavi, Niloofar
Valid causal inference: model selection and sensitivity to unobserved confounding in high-dimensional settings
Moosavi, Niloofar; Gorbach, Tetiana; de Luna, Xavier
A note on sensitivity analysis for post-machine learning causal inference
Moosavi, Niloofar; Gorbach, Tetiana; de Luna, Xavier
View publications in DiVA

Research groups

Group member
Stat4Reg

Research projects

1 June 2022 until 31 December 2026
Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions