Logics for causal inference under uncertainty

Personal webpage – Sara Magliacane

I’m a fourth-year PhD student in AI at the VU University in Amsterdam, where I’m part of the Knowledge Representation and Reasoning Group, led by Frank van Harmelen. I’m also collaborating with the Causality Amsterdam group at the UvA led by Joris Mooij and Paul Groth at Elsevier Labs. During my PhD I interned in Google Zurich and in Google Research New York. I previously studied Computer Engineering at the University of Trieste, at Politecnico di Milano and Alta Scuola Politecnica.

My thesis is on “Logics for causal inference under uncertainty”. In particular, I have been working on logic-based methods that formulate causal inference as a joint optimization problem, developing ACI (Ancestral Causal Inference), a method that provides comparable accuracy to the best state-of-the-art methods, but improves on their scalability.

Currently I’m working on joint causal inference, a powerful formulation of causal discovery over multiple datasets in which we jointly learn both the causal structure and targets of interventions from independence test results on all available observational and interventional datasets.

 

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