Josh Jacobson

Josh Jacobson

Ph.D. Candidate

Centre for Environmental Informatics

University of Wollongong

Welcome!

I am a final-year Ph.D. candidate in the School of Mathematics and Applied Statistics at the University of Wollongong in Australia. My dissertation is in multivariate spatial and spatio-temporal statistical modeling with applications to large remote sensing datasets for environmental processes, supervised by Noel Cressie, Andrew Zammit Mangion, and Michael Bertolacci. A primary focus has been the estimation of natural carbon sources and sinks in a hierarchical Bayesian inversion framework.

More broadly, my research interests span spatio-temporal statistics and Bayesian inference, including methods for big data, data fusion, multivariate processes, and uncertainty quantification, especially as applied to the environmental and climate sciences. I am also interested in neural inference and statistics of extremes.

Previously, I have also been involved as a data science consultant at Jupiter Intelligence, where I developed statistical extreme-value models for climate risk analysis. I hold B.S. and M.S. degrees in applied mathematics from the University of Colorado Boulder.

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