Dr Thin NguyenResearch interests
My research advances causal artificial intelligence — machine learning that goes beyond correlation to reason about causes, mechanisms, interventions and explanations. I develop methods across four connected themes:
- Causal discovery — acyclicity-free and Bayesian causal discovery; learning causal structure from observational data.
- Causal inference — conditional-independence testing with neural density models; robust causal direction and noise-model estimation.
- Trustworthy & explainable AI — root-cause explanation and causal domain generalisation; models that are robust under distribution shift.
- Causal reasoning in foundation models — causal alignment and steering of large language models.
These methods are driven by scientific and public-interest challenges where causal reasoning provides actionable insight, robust decision support and scientific understanding:
Grants
Total awarded research funding: approximately A$13.16 million.
Project PHONOTYPE: Validation of smartphone-based digital phenotyping markers for detecting amotivation symptoms in young people with depression$10.06M
2024–2029
CIs: Alexis Whitton, Sunil Gupta, Jill Newby, Aliza Werner-Seidler, Helen Christensen, Svetha Venkatesh, Bridianne O'Dea, Artur Shvetcov, Emma Elder, Leonard Hoon, Rajesh Vasa, Kon Mouzakis, Thin Nguyen.
Funding source: Wellcome Trust.
PRECIS: PRecision Evidence for Childhood obesity prevention InterventionS$1.28M
2021–2024
CIs: Melanie Nichols, Kathryn Backholer, Boyd Swinburn, Victoria Brown, Thin Nguyen, Christina Economos.
Funding source: NHMRC (Ideas Grants GA143439).
Identification of Blood RNA Biomarkers to Measure Disease Progression in Parkinson's Disease$85,000
2020–2021
CIs: Sunil Gupta, Svetha Venkatesh, Thin Nguyen.
Funding source: Garvan Institute of Medical Research.
A large-scale and fine-grained dataset for detection and recognition of animals in the wild$17,000
2019
CIs: Duc Thanh Nguyen, Thin Nguyen.
Funding source: Deakin University Central Research Grants Scheme (CRGS).
Social Media as Sensors for Mental Health$20,000
2017
CIs: Thin Nguyen.
Funding source: Deakin University's CRGS.
Large-scale Neural Embedding$9,235
2017
CIs: Dinh Phung, Thin Nguyen.
Funding source: Trusting Social.
Investigating the Australian far-right with online data$10,000
2017
CIs: Matteo Vergani, Thin Nguyen.
Funding source: Deakin University's CRGS.
mHealth for Automatic Dietary Assessment and Health Analysis$5,000
2017
CIs: Duc Thanh Nguyen, Thin Nguyen.
Funding source: Deakin University's CRGS.
Centre of Excellence in Big Data and Machine Learning$1.6M
2016–2020
CIs: Svetha Venkatesh, Dinh Phung, Alistair Shilton, Budhaditya Saha, Wei Luo, Truyen Tran, Sunil Gupta, Santu Rana, Thin Nguyen, Trung Le, Tu Nguyen, Vu Nguyen, Cheng Li.
Funding source: Telstra.
Improving Mental Health through Social Media$40,000
2016–2017
CIs: Thin Nguyen, Svetha Venkatesh, Dinh Phung.
Funding source: Black Dog Institute, UNSW.
Watson Data Analytics$33,000
2016
CIs: Wei Luo, Thin Nguyen, Dinh Phung.
Funding source: Deakin University.