David Broadhurst

Biography

David is the Professor of Data Science & Biostatistics in the School of Science, and director of the Centre for Integrative Metabolomics & Computational Biology (CiMCB). David holds a first class honours degree in Electronic Engineering, an MSc in Medical Informatics, and a PhD in the ‘‘Application of Artificial Neural Networks and Evolutionary Algorithms to Metabolic Profiling’’. He has been an active member of the Systems Biology community for over 20 years, where he has recognised expertise in design of experiments, signal processing, biostatistics, and machine learning. He started his professional career at University of Wales, Aberystwyth, witnessing the birth of Metabolomics (the quantitative study of low-molecular weight chemicals in a biological system related to genetic or environmental perturbations) as an independent post-genomic science, under the mentorship of Professor Douglas Kell C.B.E. After leaving Wales, David worked for an extended period as a post-doctoral research fellow at the University of Manchester developing large-scale clinical metabolomics protocols in collaboration with GSK and AstraZeneca. In 2009 he moved to Cork University Maternity Hospital, Ireland, to work as part of a team investigating pre-symptomatic metabolite biomarkers predictive of major pregnancy disorders. In 2011 David was appointed Associate Professor of Biostatistics at the University of Alberta, Canada, where he was scientific lead for a range of basic/clinical metabolomics projects, and continued his pregnancy related research. More recently he has expanded his research portfolio to a diverse range of post-genomic translational/precision medicine projects. In March 2016 he was appointed to his current position as Professor at Edith Cowan University. David’s current research focuses on integrative metabolomics and computational biology. With particular emphasis on multi-system/multi-omic data integration, population stratification via personalised trajectories, model optimization by evolutionary computation, artificial neural networks, and data visualisation.

Research Interest

Integrative Metabolomics & Computational Biology, Data Science & Biostatistics.