Dr Luke Lloyd-Jones

I’m a passionate research scientist that focuses on the development and implementation of novel statistical and machine learning methods with applications in quantitative genetics and ecology. I have an internationally competitive research portfolio. I have initiated multiple active collaborations and have been awarded an international travel award (total $25,000) by the Swiss National Science Foundation and a Churchill Fellowship ($25,000).

I’m currently a Research Scientist at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) working with the Data61 business unit on statistical methods and application to ecological projects. I worked for five years as a Postdoctoral Research Fellow at the University of Queensland, in the Program in Complex Trait Genomics under the supervision of Professor Peter Visscher (FRS). My postdoctoral work was at the forefront of merging advanced statistical and machine learning methodology with software engineering, algorithm design, and quantitative genetics to make discoveries from big human genomics data sets. I have recently co-developed state-of-the-art Bayesian machine learning algorithms for improved prediction of an individual’s genetic risk http://cnsgenomics.com/software/gctb/#Overview. I have analysed and published on the largest individual-level data set ever compiled on human gene expression and disseminated them to an international audience via an R Shiny application. I have recently developed new statistical algorithms and theory for the lasso-penalized mixture of linear regression models problem. I have supervisory and management experience and have recently graduated as primary supervisor a master’s student to the completion of her degree with a high distinction. I have mentored many postgraduate and undergraduate research students over the past four years within my current laboratory.

I'm highly skilled in C++, FORTRAN, Python, R, and Bash scripting and computer programming. I have very strong graphical and presentation skills using LaTeX, R Markdown, and R Shiny, an in-depth understanding of a broad range of mathematical and statistical areas.