Dr Thi Nguyen
Data Scientist
Working groups
Background
Dr Thi Nguyen has been a data scientist at Burnet Institute since 2025, following his role as data manager from 2019. His research interests lie in healthcare data science, biostatistics, and data automation, with expertise in the application of advanced machine learning and natural language processing methods to public health data. Dr Nguyen has substantial experience with electronic data capture platforms, including REDCap, and is actively involved in integrating these systems into research workflows to support rigorous data collection, management, and analysis in public health studies.
Prior to joining Burnet, Dr Nguyen was a research fellow at the National University of Singapore, where he developed natural language processing algorithms to enhance infectious disease surveillance systems.
Qualifications
- 2023: Master of Biostatistics, University of Melbourne, Australia
- 2019: Machine Learning Engineer Nanodegree, UDACITY
- 2013: PhD (CompSci), La Trobe University, Australia
- 2008: Bachelor of Computer Science (Hons), La Trobe University, Melbourne
- 2007: Bachelor of Computer Science, La Trobe University, Melbourne
Positions
- 2025–present: Data Scientist, Burnet Institute, Melbourne
- 2019–2024: Data Manager, Burnet Institute, Melbourne
- 2019: Research Collaborator and Academic, La Trobe University, Melbourne
- 2013–2015: Research Fellow, National University of Singapore, Singapore
- 2009–2013: PhD Candidate, La Trobe University, Melbourne
Awards
- 2023: Artificial Intelligence in Public Health Competition 3rd Prize, University of Melbourne
- 2008: First Class Honours, La Trobe University
- 2006: Member of the Golden Key International Honour Society in recognition of academic excellence achievement, La Trobe University
- 2006: 2005 Dean's Honours List, La Trobe University
Reports and other work
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The Optimise Study: A rapid survey examining frequency, impacts of long COVID and associated concerns. (PUBLIC HEALTH REPORT)
Long COVID is estimated to be costing the Australian economy $3.6 billion annually.1 Partly because of the variation in the definition of long COVID
The Optimise Study: A rapid survey examining frequency, impacts of long COVID and associated concerns. (PUBLIC HEALTH REPORT) -
The Optimise Study: A rapid survey examining the influence of potential cessation of the Victorian pandemic declaration. (PUBLIC HEALTH REPORT)
The Optimise Study: A rapid survey examining the influence of potential cessation of the Victorian pandemic declaration. (PUBLIC HEALTH REPORT) -
COVID-19 testing in schools and attitudes and concerns about the current state of the pandemic. (PUBLIC HEALTH REPORT)
The Optimise Study has followed a cohort of over 700 Victorians since September 2020. A rapid survey was conducted between 28 October and 4 November 2021 to assess optimise participants' views about the best ways to implement COVID-19 testing in schools.
COVID-19 testing in schools and attitudes and concerns about the current state of the pandemic. (PUBLIC HEALTH REPORT)
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The Optimise Study: A rapid survey examining concerns about children returning to school in 2022. (PUBLIC HEALTH REPORT)
The Optimise Study has followed a cohort of around 700 Victorians since September 2020. A rapid survey was conducted between 4 and 14 March 2022 to assess Optimise participants' concerns about children returning to school, COVID-19 testing in schools, views about COVID-19 prevention measures taken in schools, and the acceptability of closing schools under certain circumstances.
The Optimise Study: A rapid survey examining concerns about children returning to school in 2022. (PUBLIC HEALTH REPORT) -
The Optimise Study: Summer 2021-2022 Snapshot. (PUBLIC HEALTH REPORT)
The Optimise Study: Summer 2021-2022 Snapshot. (PUBLIC HEALTH REPORT)
Burnet publications
View 3 moreA longitudinal study of alcohol consumption among adults in Victoria, Australia during the COVID-19 pandemic
PLoS ONE
Tianhui Ke et al
Phenotyping people with a history of injecting drug use within electronic medical records using an interactive machine learning approach
npj Digital Medicine
Carol El‐Hayek et al
Priority populations’ experiences of isolation, quarantine and distancing for COVID-19: protocol for a longitudinal cohort study (Optimise Study)
BMJ Open
Alisa Pedrana et al
Current projects
View 4 more
STRIVE: stronger surveillance for vector-borne pathogens
Infectious diseases are an increasing global health threat, especially in low- and middle-income countries.
Global collaboration to prevent pre-eclampsia with aspirin
PEARLS is the world’s largest study on aspirin use to prevent pre-eclampsia.
Eliminate Hepatitis C Australia (EC Australia)
Partnering to eliminate hepatitis C as a public health threat by 2030.
Past projects
ACCESS Myanmar: Assessing the feasibility of an integrated HIV cascade of care surveillance system in Myanmar
ACCESS Myanmar will implement and evaluate an electronic health records data linkage system that effectively monitors the progress of patients through HIV testing and treatment episodes of care across a network of partnering community and government services.
The Optimise Study: Optimising Isolation, Quarantine and Distancing for COVID-19
This project aims to find out how Victorians are experiencing COVID-19 and responding to the measures introduced to stop the spread of the virus.