Projects per year
Personal profile
Biography
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.
Keywords
- 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
Cardiorespiratory function as a non-invasive biomarker for detecting seizures with artificial intelligence: Utilising data from long-term patient recordings from an epilepsy monitoring unit
O'Brien, T., Kwan, P., Sivathamboo, S., Perucca, P., Ge, Z., Le, T., Phung, D., Bonnington, P. & Piccenna, L.
8/04/19 → 8/04/20
Project: Research
Nonparametric Machine Learning for Modern Data Analytics (ARC DP)
18/06/18 → 31/12/19
Project: Research
Deep Learning for Cyber (Data61 CRP 38)
Phung, D., Le, T., Xiang, Y., Zhang, J., Wen, S., Murray, T. & Nock, R.
15/06/18 → 30/06/20
Project: Research
Stay Well: Analysing Lifestyle Data from Smart Monitoring Devices (ARC DP)
Phung, D., Venkatesh, S. & Kumar, M.
7/06/18 → 31/12/19
Project: Research
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 journal › Article › Research › peer-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 journal › Article › Research › peer-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 journal › Article › Research › peer-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. 8545139Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research
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 journal › Article › Research › peer-review
Open Access
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