Dinh Phung


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Personal profile


Dinh Phung is a Professor of Machine Learning and Data Science in the Faculty of Information Technology, Monash University, Australia. He is a leading researcher at the forefront of theoretical and applied machine learning with a current focus on generative deep learning, Bayesian nonparametrics and graphical models, optimal transport and point process theory for machine learning. He publishes regularly in the areas of machine learning, AI and data science. He is also a technical consultant as Director of AI Research for Trusting Social - an AI Fintech company whose aim is to advance data science and AI to provide financial access for all.

Prof Dinh Phung is currently the Chief Examiner for the new FIT3181 Deep Learning unit, which will be offered in 2019. His personal website is at: dinhphung.ml and he's also known in Vietnamese as Phùng Quốc Định.


  • Machine Learning
  • artificial intelligence
  • deep learning
  • representation learning
  • Bayesian statistics
  • graphical models
  • learning from non-stationary distributions
  • deep generative models
  • data science
  • autism

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2018 2022

Research Output 2013 2019

GoGP: scalable geometric-based Gaussian process for online regression

Le, T., Nguyen, K., Nguyen, V., Nguyen, T. D. & Phung, D., 2019, (Accepted/In press) In : Knowledge and Information Systems. 30 p.

Research output: Contribution to journalArticleResearchpeer-review

Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices

Nguyen, T., Larsen, M., O'Dea, B., Nguyen, H., Nguyen, D. T., Yearwood, J., Phung, D., Venkatesh, S. & Christensen, H., 2019, (Accepted/In press) In : Future Generation Computer Systems. 9 p.

Research output: Contribution to journalArticleResearchpeer-review

Academia versus social media: a psycho-linguistic analysis

Nguyen, T., Venkatesh, S. & Phung, D., Mar 2018, In : Journal of Computational Science. 25, p. 228-237 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Bayesian Multi-Hyperplane Machine for pattern recognition

Nguyen, K., Le, T., Dinh, T. N. & Phung, D., 2018, 2018 24th International Conference on Pattern Recognition (ICPR): Aug. 20 2018 to Aug. 24 2018 Beijing, China. Liu, C-L., Chellappa, R. & Pietikäinen, M. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 609-614 6 p. 8545139

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Discovering topic structures of a temporally evolving document corpus

Beykikhoshk, A., Arandjelović, O., Phung, D. & Venkatesh, S., Jun 2018, In : Knowledge and Information Systems. 55, 3, p. 599-632 34 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access