Berkeley CSUA MOTD:Entry 54698
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2025/05/29 [General] UID:1000 Activity:popular
5/29    

2013/6/27-8/23 [Computer/SW/Languages/JavaScript] UID:54698 Activity:nil
6/27    Now that ilyas is gone... tell us about the city, ausman
        \_ http://preview.tinyurl.com/9aatryf -a
        \_ Whither ilyas?
           \_ http://www.southampton.ac.uk/maths/about/staff/is1d12.page
2025/05/29 [General] UID:1000 Activity:popular
5/29    

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www.southampton.ac.uk/maths/about/staff/is1d12.page
Respecting Markov equivalence in computing posterior probabilities of causal graphical features. In, Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence. On the validity of covariate adjustment for estimating causal effects. In, Proceedings of the Twenty Sixth Conference on Uncertainty in Artificial Intelligence (UAI-10). Effects of treatment on the treated: identification and generalization. In, Proceedings of the Twenty Fifth Conference on Uncertainty in Artificial Intelligence (UAI-09). In, Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence. Research Research Interests Inferring cause effect relationships is the principal aim of the empirical sciences. I am interested in identification and estimation of quantities that correspond to causal relationships of interest in practical data analysis, such as (interventional) causal effects, direct and indirect effects, and effects of treatment on the treated. I am also interested in the limits of causal inference, that is in characterizing cases where causal inference is not possible. Finally, I am interested in using insights gained in causal analysis for inference and learning in hidden variable statistical models. Research Projects * Longitudinal mediation analysis (identification and inference) * Learning and inference in marginal models (nested Markov models) * Causal inference and graphical models (causal effects, mediation, effects of treatment on the treated, counterfactuals).