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.
I am currently the Chief Examiner for the new FIT3181 Deep Learning unit, which will be offered in 2019. My personal website is at: dinhphung.ml and I'm 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
Nonparametric Machine Learning for Modern Data Analytics (ARC DP)
18/06/18 → 31/12/19
Project: Research
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
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., 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
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, 94Research output: Contribution to journal › Article › Research › peer-review
Learning graph representation via frequent subgraphs
Nguyen, D., Luo, W., Nguyen, T. D., Venkatesh, S. & Phung, D. 1 Jan 2018 p. 306-314 9 p.Research output: Contribution to conference › Paper › Other › peer-review
Model-based learning for point pattern data
Vo, B. N., Dam, N., Phung, D., Tran, Q. N. & Vo, B. T. 1 Dec 2018 In : Pattern Recognition. 84, p. 136-151 16 p.Research output: Contribution to journal › Article › Research › peer-review
PC chairs’ preface
Phung, D. & Tseng, V. S. 1 Jan 2018 In : Lecture Notes in Computer Science. 10937 LNAIResearch output: Contribution to journal › Editorial › Other › peer-review