Dr Shalem Leemaqz is a postdoctoral researcher at the Pregnancy Health and Beyond (PHaB) Lab, College of Medicine and Public Health and a biostatistician. His current research aims to model risks for pregnancy complications through statistical and data mining techniques, with a focus on advanced mathematical and statistical modelling of high-dimensional data. He has a background in Mathematics/Statistics and Electronic Systems Engineering, with knowledge of computer architecture and machine learning techniques, and experience in programming using various languages with expertise in R statistical programming.

During his PhD (2010 – 2015) with the Placental Development Group in the Robinson Research Institute and Adelaide Medical School at the University of Adelaide, he established the theoretical basis of a novel tiered modelling approach which enables classification of low-prevalence outcomes into low, moderate and high risk levels. This modelling concept was applied to develop screening tools for preeclampsia, preterm birth, intrauterine growth restriction and gestational diabetes, which were the subject of a PCT application filed 23 March 2016.

He is committed to bringing quality statistics into medical research, with great interests in applied mathematics and statistics to model complex health-related Big-data. He collaborate with bioinformaticians to develop methods to analyse and integrate genomic data together with clinical data.