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Higher degree by research students

Vu Viet Hoang Pham


About me

I am a PhD Candidate at the School of Information Technology and Mathematical Sciences, University of South Australia (UniSA). I have bachelor and master degrees in Information Technology. I am a member of Data Analytics Group. My research interests are causal inference and its applications in Bioinformatics, an interdisciplinary research area which requires the knowledge of Information Technology, Mathematics, and Statistics to solve biological problems.

Scholarships and awards I have won:
- Travel scholarship of Australian Genome Research Facility (AGRF) and Bioplatforms Australia to participate in the Winter School 2019 in The University of Queensland
- The Vice Chancellor and President's Scholarship for the top two PhD scholarship recipients in each Division at the University of South Australia
- Australian Government Research Training Program (RTP) scholarship for PhD program
- Deakin University International Scholarship for master program
- The First Laureate in the Candidates recruitment entrance examination to University of Natural Sciences for bachelor program
- Best Performers in Sub-Challenges 1 & 2 in DREAM Single Cell Transcriptomics Challenge (Team WhatATeam)

- Present a poster in Intelligent Systems for Molecular Biology (ISMB)/European Conference on Computational Biology(ECCB) 2019 in Switzerland
- Review papers for KDD 2019 Workshop on Causal Discovery
- Web Master for The 17th Australasian Data Mining Conference (AusDM'19)
- Tutor of the course Advanced Analytic Techniques 2
- Research Assistant at the School of Information Technology and Mathematical Sciences, University of South Australia


Developing Causal Inference Methods for Personalised Medicine in Cancer Research

As there is evidence that cancer is caused by genomic mutations, to design effective cancer treatment methods, scientists need to know causes of cancer at the genomic level. The biological factors which cause cancer at the genomic level are called cancer drivers. With the significant development of computer science and gene analysis techniques, there are a wide range of computational methods which are developed to infer cancer drivers. However, most of the current methods detect coding cancer drivers with mutations while there are still other cancer drivers such as non-mutated drivers, i.e. genes do not contain mutations but regulate driver mutations to develop cancer, or non-coding drivers, i.e. non-coding RNAs regulate gene expression and drive cancer. In this research, my aim is developing causal inference methods for identifying cancer drivers without the current limitations. The results of the research potentially contribute significantly to personalise medicine for cancer patients to increase their survival chance.

Research publications

Software: miRLAB

Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data

The winning methods for the DREAM single cell transcriptomics challenge

Pillman, Katherine ; Scheer, Kaitlin; Hackett-Jones, Emily; Saunders, Klay; Bert, Andrew; Toubia, John,; Whitfield, Holly; Sapkota, Sunil; Sourdin, Laura; Pham, Hoang; Le, Thuc Duy; Cursons, Joseph; Davis, Melissa; Gregory, Philip A; Goodall, Greg; Bracken, Cameron 2019. 'Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA)'. (Submitted to Nucleic Acids Research)

Pham, VVH, Liu, L, Bracken, CP, Goodall, GJ, Long, Q, Li, J & Le, TD 2019, 'CBNA: A control theory based method for identifying coding and non-coding cancer drivers'. (Submitted to PLOS Computational Biology)

Zhang, J+, Pham, VVH+, Liu, L, Xu, T, Truong, B, Li, J & Le, TD 2019, 'Identifying miRNA synergism using multiple-intervention causal inference'. (Submitted to Intelligent Systems for Molecular Biology (ISMB)/European Conference on Computational Biology(ECCB) 2019)

Pham, VVH, Liu, L, Bracken, CP, Li, J & Le, TD, 'Computational Methods for Identifying Cancer Drivers from Genomic Data'. (Submitted to Briefings in Bioinformatics)

Pham, VVH+, Zhang, J+, Liu, L, Truong, BMT, Xu, T, Nguyen, TT, Li, J & Le, TD 2019, 'Identifying miRNA-mRNA regulatory relationships in breast cancer with invariant causal prediction', BMC Bioinformatics, vol. 20, no. 1, pp. 143.

Pham, VVH, Yu, S, Sood, K & Cui, L 2018, 'Privacy issues in social networks and analysis: a comprehensive survey', IET Networks, vol. 7, no. 2, pp. 74-84.

Nosouhi, MR, Pham, VVH, Yu, S, Xiang, Y & Warren, M 2017, 'A Hybrid Location Privacy Protection Scheme in Big Data Environment', in GLOBECOM 2017 - 2017 IEEE Global Communications Conference, pp. 1-6.

Pham, VVH, Liu, X, Zheng, X, Fu, M, Deshpande, SV, Xia, W, Zhou, R & Abdelrazek, M 2017, 'PaaS - Black or White: An Investigation into Software Development Model for Building Retail Industry SaaS', in 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), pp. 285-7.


International Society for Computational Biology (ISCB)

Australian Bioinformatics And Computational Biology Society (ABACBS)

Australian Computer Society (ACS)

Golden Key International Honour Society

Online resources

Data Analytics Group

School of Information Technology and Mathematical Sciences

University of South Australia