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 in providing Research Directorship for the AI and Machine Learning Research Lab 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
- 5 Active
Stay Well: Analysing Lifestyle Data from Smart Monitoring Devices (ARC DP)
Phung, Q. D., Venkatesh, S. & Kumar, M.
18/06/18 → 31/12/18
Project: Research
Nonparametric Machine Learning for Modern Data Analytics (ARC DP)
18/06/18 → 31/12/19
Project: Research
ARC Research Hub for Digital Enhanced Living
Mouzakis, K., Grundy, J. C., Venkatesh, S., Maeder, A. J., Hutchinson, A., Berk, M., Maddison, R., Kouzani, A. Z., Vasa, R., Calvo, R., Christensen, H. M., Williams, P., Phung, Q. D., Yearwood, J., Gordon, S., Powers, D. M. W., Wickramasinghe, N., Bidargaddi, N., Rana, S., Tran, T., Gupta, S., Luo, W., Abdelrazek, M., Tan, F. T. C., Langberg, H., Kayser, L., Kensing, F., Bodendorf, F., Hansen, J. P., Warren, J. R., Sinha, R., Smeaton, A., Aitken, I., Voukelatos, F., Fiebig, J., Serroni, D., Farquhar, C., Nagarajan, R., Tripodi, B., Biggin, J., Fouyaxis, J., Gerasimou, E., Varley, D. & Pitcher, M.
Monash University – Internal Faculty Contribution
15/03/18 → 14/03/22
Project: Research
Research Output 2013 2018
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
Discovering topic structures of a temporally evolving document corpus
Beykikhoshk, A., Arandjelović, O., Phung, D. & Venkatesh, S., 1 Jun 2018, In : Knowledge and Information Systems. 55, 3, p. 599-632 34 p.Research output: Contribution to journal › Article › Research › peer-review
Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding
Nguyen, D., Luo, W., Venkatesh, S. & Phung, D., 1 May 2018, In : Journal of Medical Systems. 42, 5, 94.Research output: Contribution to journal › Article › Research › peer-review
Geometric Enclosing Networks
Le, T., Vu, H., Nguyen, T. D. & Phung, D., 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18). Lang, J. (ed.). California USA: International Joint Conferences on Artificial Intelligence, p. 2355-2361 7 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access
File
GoGP: scalable geometric-based Gaussian process for online regression
Le, T., Nguyen, K., Nguyen, V., Nguyen, T. D. & Phung, D., 1 Jan 2018, (Accepted/In press) In : Knowledge and Information Systems. 30 p.Research output: Contribution to journal › Article › Research › peer-review