Research

The statistical sciences interact with virtually every discipline in science, social science, and engineering. Research interests in the Department are similarly widespread. Consequently, the following summary covers just some of the main current themes of faculty members and their research teams (graduate student, postdocs, collaborators, etc.). For more detailed information, please see the  individual home pages of faculty members.

Biostatistics

Many faculty members (Rollin Brant, Jenny Bryan,Paul Gustafson, Kevin Murphy, John Petkau, Will Welch, Lang Wu) work on applying statistical methods to biomedical problems, ranging from analysing gene expression data to public health issues. Much of this work is done in conjunction with local hospitals (such as St Paul's) and research institutes (such as the BC Cancer Agency and the BC Genome Sciences Center).  As of Fall 2009, we are introducing a new MSc program in biostatistics, together with the School of Population and Public Health.  Some more details on some of this research can be found on the page for the  Biostatistical research group (BRG).

Environmental statistics

Jim Zidek has been active in this area for many years, and has consulted for the US EPA, and various Canadian agencies. Ongoing research ranges from analysis of pollution data collected over a geographical area and time to studies involving global climate models. Some of this work is summarized in his recent book Statistical Analysis of Environmental Space-Time Processes with Nhu Le (Springer, 2006). Click here for more information. John Petkau works on the public health issues related to air pollution. In 2012, we will move into a new building with the department of Earth and Ocean Sciences, which we expect will result in further collaborative work in this growing area.

Bayesian statistics

Many faculty members (including  Arnaud Doucet, Paul Gustafson, Kevin Murphy, and Jim Zidek) are involved in the methodology and applications of Bayesian statistics. A particular theme has been efficient computation. In particular, Arnaud Doucet has been developing novel Sequential Monte Carlo (SMC) methods, which are an alternative to the widely used Monte Carlo Markov Chain (MCMC) method.

Robust STATISTICS

Ruben Zamar and  Matias Salibian-Barrera focus on making statistical methods less sensitive to unusual, exteme values and to incorrect modelling assumptions.

OTHER AREAS

Other faculty work on a diverse range of topics, besides those mentioned above. Nancy Heckman works on functional data analysis and smoothing methods. Will Welch works on the design and analysis of computer experiments, as well as data mining. Harry Joe works on multivariate non-normal statistics. Jiahua Chen works on classical statistical theory, especially asymptotic analysis and analysis of mixture models. Lang Wu works on mixed effects models and longitudinal data analysis. Kevin Murphy works on graphical models. Paul Gustafson works on measurement error and nonidentifiable models.

Our two new hires are Natalia Nolde and Alex Bouchard-Cote.  Natalia works probabilistic and statistical aspects of multivariate extreme value theory, with applications to risk management.  Alex works in statistical machine learning, specializing in high-resolution computational models for evolutionary processes, with applications in statistical Natural Language Processing and computational biology.

These are just a few highlights of the diverse research activities in the Department. For more detailed information, please see the  individual home pages of faculty members.