My educational background and experience allow me to work at the interface of spatial ecology, geographic information science, and environmental statistics.  My research is generally focused on the development of transdisciplinary approaches and tools used to account for the spatial location, configuration, and connectivity of features at multiple scales in statistical models.  This research is exciting because it is almost always motivated by real-world challenges in the area of regional monitoring program design, assessment, and reporting.

I am also committed to software tool development, which ensures that the methodologies I develop are made accessible to other scientists and natural resource managers. I lead and collaborate on a wide variety of projects  where we use big data analytics, statistical modelling and machine learning in the environmental and agricultural domains.  These projects are increasingly focused on the development of methods for near real-time data collected using in-situ sensors; accounting for data quality and uncertainty when combining different data sources, including citizen-science data; expert elicitation using information technologies such as virtual reality; IntelliSensing software for real-time workflows; and spatio-temporal analytics and/or visualisation.

I enjoy working with postgraduate and undergraduate students on a wide range of projects  and I am always looking for good students.  Please contact me to learn about research opportunities for students.