Professor Ricardo Silva

Biographical Details

Ricardo is a Professor at the Department of Statistical Science and Adjunct Faculty of the Gatsby Computational Neuroscience Unit. Prior to that, Ricardo got his PhD from the newly formed Machine Learning Department at Carnegie Mellon University in 2005. Ricardo also spent two years at the Gatsby Computational Neuroscience Unit as a Senior Research Fellow, and one year as a postdoctoral researcher at the Statistical Laboratory in Cambridge.

Research Interests

Machine learning, causality, graphical models, Bayesian inference, relational inference.

Selected publications

• Kusner M, Loftus J, Russell C and Silva R (2017). Counterfactual fairness. Advances in Neural Information Processing Systems (NIPS 2017) 30, 4066-4076.
• Silva R and Evans R (2016). Causal inference through a witness protection program. Journal of Machine Learning Research 17, 1949-2001.
• Silva R, Kang SM and Airoldi EM (2015). Predicting traffic volumes and estimating the effects of shocks in massive transportation systems. Proceedings of the National Academy of Sciences 112 (18), 5643-5648.
• Silva R and Ghahramani Z (2009). The hidden life of latent variables: Bayesian learning with mixed graph models. Journal of Machine Learning Research 10, 1187-1238.
• Silva R, Scheines R, Glymour C and Spirtes P (2006). Learning the structure of linear latent variable models. Journal of Machine Learning Research 7(Feb):191-246.