Shalem Leemaqz

Dr Shalem Leemaqz

Postdoctoral Fellow

Adelaide Medical School

Faculty of Health and Medical Sciences

Dr Shalem Leemaqz is an adjunct staff at the Adelaide Medical School. He is currently a postdoctoral researcher at the Pregnancy Health and Beyond (PHaB) Lab at the College of Medicine and Public Health, Flinders University, and a statistician at South Australian Health and Medical Research Institute. His 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 and collaborate with bioinformaticians to develop methods to analyse and integrate genomic data together with clinical data.

Statistical modelling for early screening tools to predict pregnancy complications

Preeclampsia, intrauterine growth restriction, preterm birth and Gestational Diabetes affect 1 in 4 Australian pregnancies, with mothers and babies at risk of morbidity and mortality. Hence, methods to identify women at risk of pregnancy complications before symptoms occur would be highly valued by the obstetricians, as modifiable risk factors can be addressed and early interventions implemented to reduce the risk or severity of complications. However, due to complex gene-environment interactions and multiple confounding factors, risk prediction remains a major challenge. More sophisticated statistical techniques are required to model risk. Dr Leemaqz's current research focuses on mathematical and statistical approaches to address analytical and practical challenges in the development and application of flexible algorithms for low-prevalence disease prediction. These methods will be applied to develop a novel screening tool to predict risk for pregnancy complications using models which will permit classification of patients into 3 levels of risk, for whom interventions that could benefit both mother and child may be provided.

  • Appointments

    Date Position Institution name
    2020 Research Associate in Biostatistics Flinders University
    2015 - 2020 Postdoctoral Fellow University of Adelaide
    2015 - 2020 REDCap Database System Administrator University of Adelaide
    2014 - 2014 Statistical Analyst (part-time) Central Queensland University
    2013 - 2014 Biostatistician (casual) ODesk
    2012 - 2012 Statistical Analyst (part-time) with Prof. Irene Hudson on project from Appleton Institute, Central Queensland University
    2010 - 2010 Statistical Analyst (part-time) University of Adelaide
    2010 - 2010 Statistical Analyst (part-time) University of Adelaide
    2009 - 2010 Statistical Analyst (part-time) University of South Australia
    2008 - 2008 Robotics Mentor (part-time) University of South Australia
  • Awards and Achievements

    Date Type Title Institution Name Country Amount
    2014 Award HDA Travel Grant Healthy Development Adelaide
    2014 Award RI & SPRH Travel Grant 2014 University of Adelaide Australia
    2010 Scholarship PhD Scholarship University of Adelaide Australia
  • Education

    Date Institution name Country Title
    2015 University of Adelaide Australia PhD
    2009 Macquarie University Australia Masters
    2008 University of South Australia Australia Bachelor
  • Certifications

    Date Title Institution name Country
    2007 Cisco Certified Networking Associate Cisco
    2007 Microsoft Certified System Administrator Microsoft
  • Research Interests

  • Memberships

    Date Role Membership Country
    2013 - ongoing Member Australian Society for Medical Research (ASMR) Australia
    2012 - ongoing Member Statistical Society of Australia (SSAI) Australia
  • Position: Postdoctoral Fellow
  • Phone: 83136077
  • Email:
  • Campus: North Terrace
  • Building: Adelaide Health and Medical Sciences, floor 6
  • Room: WS6062.45
  • Org Unit: Adelaide Medical School

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