S. Sandun Malpriya

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S. Sandun Malpriya

S. Sandun Malpriya


First Name

S. Sandun Malpriya

Last Name



Macquarie University

Primary Affiliation





Dr. S. Sandun Malpriya Silva is a statistician specialized in biostatistics and data science in digital health scope.

He is currently working as a research fellow at Australian Institute of Health Innovation (AIHI). He has worked as a biostatistician at National Health Medical Research Council (NHMRC) Clinical Trial Center, University of Sydney, prior joining to AIHI.

He has completed his bachelor’s in Statistics at University of Colombo, Sri Lanka. After a year of working as a data analyst/scientist in Sri Lanka, he was offered a full scholarship from Department of Health Science and Biostatistics at Swinburne University of Technology Australia to follow a PhD in Statistics (STA90001) in the scope of Health Science (DR-HTHSCI).

His PhD project was named as “Innovative Statistical Methods to Model and Evaluate Physical Activity Programs Engagement”, which comprises statistical and machine learning models to model mHealth physical activity programs. This PhD project was done in collaboration with a US based world leading wellbeing program which is known as “Virgin Pulse Global Challenge”. The findings of the PhD were well published in leading academic journals and international conferences.

During his PhD, he has also consulted over 1000 students in advanced statistical modelling, time series analysis, machine learning, business forecasting and predictive analytics at three ranking universities namely Monash University, Melbourne University (MBS) and Swinburne University of Technology, with an overall rating of 4.7 out of 5.

He has also worked with Department of Transport, Victoria and Peter MacCallum Cancer Research Centre, Melbourne on various studies to solve real world problems. The findings of these studies have been published in leading academic journals.

He enjoys working on real world health problems using data and statistics.


Clinical Analytics, Digital Health, Informatics, Mobile Health


Community, Medicine, University

Other Discipline(s)

Statistical Analysis, Predictive analytics


Apps & Mobile Health, Data Science, Genomics / Biomedical Data & Bioinformatics

Domains of Interest

Promoting Informed Healthcare Delivery, Safely Managing & Sharing Information, Towards Personalised Health

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