| My Research: I am interested in both: (i) Theoretical and methodological research in Bayesian methods as well as (ii) in modeling complex real life processes using statistical methods.
Theoretical and methodological research: I am interested in developing computationally efficient methods for Bayesian inference. Along with and our Ph.D. student Paul Brown,
we have developed a computationally efficient algorithm based on low discrepancy sequences which can be used in grid-based Bayesian methods such as . I am also currently working on Approximate Bayesian Computation (ABC) methods.
Recently, I have also started working on problems in Bayesian robustness - specifically on prior robustness. I am interested in developing prior robustness methods for Bayesian models using the distorted band class of priors.
Statistical Modelling: I am part of the newly formed NZ Institute of Secutiry and Crime Science. I am working on modelling crime in collaboration with NZ Police. Recently, I have started working on the Adversarial Risk Analysis (ARA) in collaboration with (ICMAT) and others.
From time to time, I collaborate with scientists on interesting modelling problems. This includes some recent work with group
on incorporating uncertainty using Bayesian methods. Over the last few years, I also worked with (now at Univ. of Wyoming, U.S.) on problems related to modeling
species distribution. We developed a novel mathematical framework called 'Traitspace' which incorporates the various processes/factors which govern the assembly of ecological
communities via their functional traits and predicts the community assembly by using the observed trait values.
Previous statistical work/interests include: Efficient Bayesian inference on Stochastic Differential Equation (SDE) models, Epidemiology, Clinical trials, Demand estimation and Market research.
From 2003 until 2007, I worked as a statistician for a number of leading corporations in the pharmaceutical and market research area.