My research interests are diverse. My methodological interests include spatial and spatio-temporal statistics, Bayesian hierarchical models, high-dimensional data and small area estimation. The methods research usually emerge from my collaborations with researchers in areas of air pollution, environmental health, forestry and climate modeling, epidemiology and international health. Currently, I'm working on statistical methods for hyper-local air pollution data, Bayesian transfer learning approaches for extremely small datasets, and methods and software development for massive spatio-temporal data. I have also recently got involved in applications of spatial statistics in neuroimaging and genetics.
If you're interested in any of the areas and would like to discuss research or collaboration opportunities, feel free to email me or drop by my office.