Mathematical Sciences

Ilya Shpitser

Primary position:
Lecturer

Background

The University of Southampton
  • BA in Computer Science/Mathematics, UC Berkeley
  • MS in Computer Science, UCLA
  • PhD in Computer Science, UCLA
  • Research Fellow/Associate, Program in Causal Inference, Harvard School of Public Health
  • Lecturer, Southampton University
Dr Ilya Shpitser's photo

Publications

The University of Southampton's electronic library (e-prints)

Article

VanderWeele, Tyler J. and Shpitser, Ilya (2013) On the definition of a confounder. Annals of Statistics, 41, (1), 196-220. (doi:10.1214/12-AOS1058).
Tchetgen Tchetgen, Eric J. and Shpitser, Ilya (2012) Semiparametric theory for causal mediation analysis: efficiency bounds, multiple robustness, and sensitivity analysis. Annals of Statistics, 40, (3), 1816-1845. (doi:10.1214/12-AOS990).
VanderWeele, Tyler J. and Shpitser, Ilya (2011) A new criterion for confounder selection. Biometrics, 64, (4), 1406-1413. (doi:10.1111/j.1541-0420.2011.01619.x).
Shpitser, Ilya and VanderWeele, Tyler J. (2011) A complete graphical criterion for the adjustment formula in mediation analysis. International Journal of Biostatistics, 7, (1), 1-24. (doi:10.2202/1557-4679.1297).
Kang, Eun Yong, Ye, Chun, Shpitser, Ilya and Eskin, Eleazar (2010) Detecting the presence and absence of causal relationships between expression of yeast genes with very few samples. Journal of Computational Biology, 17, (3), 533-546. (doi:10.1089/cmb.2009.0176).
Shpitser, Ilya and Pearl, Judea (2008) Complete identification methods for the causal hierarchy. Journal of Machine Learning Research, 9, 1941-1979.

Book Section

Shpitser, Ilya, Evans, Robin, Richardson, Thomas and Robins, James (2013) Sparse nested Markov models with log-linear parameters. In, Proceedings of the Twenty Ninth Conference on Uncertainty in Artificial Intelligence (UAI-13). Corvallis, US, AUAI Press, 576-585.
Shpitser, Ilya (2012) Structural equations, graphs, and interventions. In, Berzuini, Carlo, Dawid, Philip and Bernardinelli, Luisa (eds.) Causality: Statistical Perspectives and Applications. Chichester, GB, Wiley, 15-24.
Richardson, Thomas S., Robins, James M. and Shpitser, Ilya (2012) Nested markov properties for acyclic directed mixed graphs. In, Proceedings of the Twenty Eighth Conference on Uncertainty in Artificial Intelligence. Corvallis, US, AUAI Press, 13.
Shpitser, Ilya, Richardson, Thomas S. and Robins, James M. (2011) An efficient algorithm for computing interventional distributions in latent variable causal models. In, Cozman, Fabio Gagliardi and Pfeffer, Avi (eds.) Proceedings of the Twenty Seventh Conference on Uncertainty in Artificial Intelligence (UAI-11). Corvallis, US, AUAI Press, 661-670.
Shpitser, Ilya (2011) Graph-based criteria of identifiability of causal questions. In, Berzuini, Carlo, Dawid, Philip and Bernardinelli, Luisa (eds.) Causal Inference: Statistical Perspectives and Applications. Chichester, GB, Wiley, 59-70.
Shpitser, Ilya and Tian, Jin (2010) On identifying causal effects. In, Dechter, Rina, Geffner, Hector and Halpern, Joseph Y. (eds.) Heuristics, Probability, and Causality: A Tribute to Judea Pearl. London, GB, College Publications.
Shpitser, Ilya (2010) Disease models, part I: graphical models. In, Bui, Alex A.T. and Taira, Ricky K. (eds.) Medical Imaging Informatics. New York, US, Springer, 335-370.
Shpitser, Ilya, VanderWeele, T. and Robins, J. (2010) On the validity of covariate adjustment for estimating causal effects. In, Proceedings of the Twenty Sixth Conference on Uncertainty in Artificial Intelligence (UAI-10). Corvallis, US, AUAI Press, 527-536.
Kang, E.Y., Shpitser, Ilya and Eskin, E. (2010) Respecting Markov equivalence in computing posterior probabilities of causal graphical features. In, Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence. Menlo Park, US, AAAI Press, 1175-1180.
Shpitser, Ilya, Richardson, T.S. and Robins, J.M. (2009) Testing edges by truncations. In, Proceedings of the Twenty First International Joint Conference on Artificial Intelligence (IJCAI-09). Menlo Park, US, AAAI Press, 1957-1963.
Shpitser, Ilya and Pearl, Judea (2009) Effects of treatment on the treated: identification and generalization. In, Proceedings of the Twenty Fifth Conference on Uncertainty in Artificial Intelligence (UAI-09). Corvallis, US, AUAI Press, 514-521.
Shpitser, Ilya and Pearl, Judea (2008) Dormant independence. In, Proceedings of the Twenty-third AAAI Conference on Artificial Intelligence. Menlo Park, US, AAAI Press, 1081-1087.
 

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).

Primary research group:  Statistics

Contact

Dr Ilya Shpitser
Building 54
Mathematical Sciences
University of Southampton
Highfield
Southampton SO17 1BJ

Room Number: 54/9001