Summary
Hien Nguyen is an Associate Professor and applied statistician with a decade of experience at the intersection of machine learning, pattern recognition, statistics and AI. He has held research and teaching roles across La Trobe University, The University of Queensland and Kyushu University, driving scalable inference methods for Big Data as an ARC DECRA fellow. His work spans mixture modelling, robust regression and false discovery rate control, with a practical focus on producing open, well-documented software for large-scale analysis. A Senior Lecturer and technical editor for the Australian and New Zealand Journal of Statistics, he combines deep theoretical training (PhD in Statistics and Image Processing) with hands-on statistical computing. Based in Melbourne, he brings uncommon domain breadth—from bioinformatics and medical imaging to econometrics—into modern ML-driven inference. Colleagues describe him as a methodologist who systematically bridges computational bottlenecks to make classical inferential tools practical at scale.
9 years of coding experience
Study Abroad (Scholarship), Study Abroad (Scholarship) at University of California, Berkeley
Doctor of Philosophy (PhD), Statistics and Image Processing, Doctor of Philosophy (PhD), Statistics and Image Processing at The University of Queensland
English, Vietnamese