Projects per year
Personal profile
Biography
Dr Lan Du is a Teaching and Research Academic in the Faculty of IT, Monash Clayton Campus. He is particularly interested in statistical modeling and learning for text analysis, which broadly covers statistical machine learning, natural language processing, data mining, and social network analysis. My up-to-date information can be found here
Some specific research topics that he is interested in and currently working on:
- Probabilistic topic modeling: He is extremely interested in developing various topic models that can explore different discourse structures and other meta information associated with natural language text.
- Nonparametric Bayesian methods, e.g., Dirichlet process, Pitman-Yor process, and Indian Buffet process. He has been working on developing different sampling methods for Pitman-Yor process since his Ph.D. study.
- Inference/ optimization algorithms, e.g., MCMC methods, Variational Bayesian (VB), and various numerical optimization algorithms
- Relational learning techniques, e.g., probabilistic matrix factorization, tensor factorization, etc. He is interested in combining matrix factorization techniques with topic models to improve, for example, recommendation systems.
- Natural Language Processing. He has worked in the NLP group at Macquarie University for about four years. He is interested in how to utilize different linguistic features in topic modeling.
Monash teaching commitment
Dr Lan Du has experience as the Chief Examiner for the following units in the Faculty of IT:
- FIT5149 Applied data analysis
- FIT5196 Data wrangling
Lan Du has experience as the Lecturer for the following units in the Faculty of IT:
- FIT5149 Applied data analysis
- FIT5196 Data wrangling
Education/Academic qualification
Computer Science, Doctor of Philosophy, Australian National University
Award Date: 13 Dec 2012
Information Technology, Bachelor of Information Technology (Honours), Australian National University
Award Date: 21 Dec 2007
Information Technology, Bachelor of Communication and Information Technology, Flinders University
Award Date: 15 Dec 2006
Research area keywords
- machine learning
- text analysis
- topic modeling
- discrete data analysis
- Non Parametric Methods
- Ranking method
Network
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Innovative methodologies in AI-powered risk prediction and risk communication in pregnancy
Lim, S., McIntosh, J., Enticott, J., Cooray, S., Moran, L., Teede, H., Harrison, C., Thong, E., Ranakombu, K. K. D. S. & Du, L.
1/01/22 → 30/06/23
Project: Research
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Towards a National Data Management Platform and Learning Health System
Teede, H., Kannan, A., Andrew, N., Pearce, C., Johnson, A., Enticott, J., Bonnington, P., Dobson, R., Curcin, V., McKimm, A., Wale, R., Bingham, G., Tong, E., Mason, C. W., MacBean, L., Pearce, C., Ferrigi, J., Andrew, N., Beare, R., Srikanth, V., Phung, D., Du, L., Collyer, T., Shaw, T., Snelling, T. L., Keech, W., Geelhood, G. & Wilson, A.
1/02/21 → 30/06/22
Project: Research
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Towards an Efficient Medical Surveillance System
Nguyen, D., Du, L., Buntine, W., Srikanth, V., Buttery, J., Bain, C. & Skouteris, H.
1/02/21 → 31/01/24
Project: Research
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PRAISE: Predicting fracture outcomes from clinical Registry data using Artificial Intelligence Supplemented models for Evidence-informed treatment (PRAISE) study
Gabbe, B., Dipnall, J., Page, R. S., Du, L., Costa, M. L. & Lyons, R. A.
National Health and Medical Research Council (NHMRC) (Australia)
1/01/21 → 31/12/24
Project: Research
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Machine learning to support the civil construction industry to create a safer future for employees - Platformers - Human-in-the-Loop Analytics GRIP
Alfredo, R., Du, L., Zhou, P., Van Enk, M. & Pearson, R.
5/12/19 → 5/12/22
Project: Research
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Class mean-weighted discriminative collaborative representation for classification
Gou, J., Song, J., Du, L., Zeng, S., Zhan, Y. & Yi, Z., Jul 2021, In: International Journal of Intelligent Systems. 36, 7, p. 3144-3173 30 p.Research output: Contribution to journal › Article › Research › peer-review
4 Citations (Scopus) -
Multilingual Neural Machine Translation: can linguistic hierarchies help?
Saleh, F., Buntine, W., Haffari, G. & Du, L., 2021, Findings of the Association for Computational Linguistics: EMNLP 2021. Moens, M-F., Huang, X., Specia, L. & Wen-tau Yin, S. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 1313-1330 18 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open AccessFile -
Predicting fracture outcomes from clinical registry data using artificial intelligence supplemented models for evidence-informed treatment (PRAISE) study protocol
Dipnall, J. F., Page, R., Du, L., Costa, M., Lyons, R. A., Cameron, P., de Steiger, R., Hau, R., Bucknill, A., Oppy, A., Edwards, E., Varma, D., Jung, M. C. & Gabbe, B. J., Sep 2021, In: PLoS ONE. 16, 9, 12 p., e0257361.Research output: Contribution to journal › Article › Other › peer-review
Open Access -
Stratified sampling for extreme multi-label data
Merrillees, M. & Du, L., 2021, 25th Pacific-Asia Conference, PAKDD 2021 Virtual Event, May 11–14, 2021 Proceedings, Part II. Karlapalem, K., Cheng, H., Ramakrishnan, N., Agrawal, R. K., Reddy, P. K., Srivastava, J. & Chakraborty, T. (eds.). Cham Switzerland: Springer, p. 334-345 12 p. (Lecture Notes in Computer Science; vol. 12713).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data
Jin, Y., Liu, M., Li, Y., Xu, R., Du, L., Gao, L. & Xiang, Y., 2021, In: Data Mining and Knowledge Discovery. 35, p. 505-532 28 p.Research output: Contribution to journal › Article › Research › peer-review