Rate My Professor Jonathan Keith

Associate Professor Jonathan Keith serves in the School of Mathematics within the Faculty of Science at Monash University. He is a researcher specializing in Bayesian methods, bioinformatics, and genetic epidemiology. His primary research interest lies in developing statistical methods for the detection of novel non-protein-coding functional elements in genomes. Keith has pursued projects in phylogenetics, whole genome association studies, and the identification of quantitative trait loci. He also explores Bayesian modelling and computational methods, with applications in invasive species modelling and epidemiology. As a chief investigator, he contributes to two Australian Research Council Discovery grants: "Statistical methods for detection of non-coding RNAs in Eukaryote Genomes" and "Statistical methods for discovering RNAs contributing to human diseases and phenotypes." Keith teaches units such as MTH4260 Statistics of Stochastic Processes.

Keith's academic career spans several institutions. He earned his PhD from the University of Queensland and held a Research Officer position at the University of Queensland's School of Mathematics and Physics from 2000 to 2006. Subsequently, he was a postdoctoral researcher at Queensland University of Technology's School of Mathematical Sciences from 2007 to 2009. Since 2010, he has been affiliated with Monash University, where he progressed to Associate Professor in the School of Mathematics. His scholarly output includes over 60 research items, comprising 44 articles, 9 conference papers, 8 chapters, and 2 edited books. Notable publications feature "Detection and identification of cis-regulatory elements using change-point and classification algorithms" (BMC Genomics, 2022), "Optimal designs for some bivariate cokriging models" (Journal of Statistical Planning and Inference, 2022), "A Comparison of Bayesian Inference Strategies for Parameterisation of Large Amplitude AC Voltammetry Derived from Total Current and Fourier Transformed Versions" (ChemElectroChem, 2021), "Identification of community structure-based brain states and transitions using functional MRI" (NeuroImage, 2021), "Recent advances and future perspectives for automated parameterisation, Bayesian inference and machine learning in voltammetry" (Chemical Communications, 2021), and contributions to Methods in Molecular Biology (2008). Keith maintains an active presence in statistical and computational biology research.