Professor Lin Liu

Professor UniSA STEM

Mawson Lakes Campus (D3-10)
tel +61 8 830 23311

email Lin.Liu@unisa.edu.au

Research Degree Supervisor

About me

Machine Learning
Causal Discovery & Inference
Data Mining
Bioinformatics

Professor Lin Liu's research interest is in the fields of machine learning and data mining, with the focus on developing robust machine learning/data mining algorithms by utilising causal relationships discovered from big data. Her resesarch is supported by the Australian Research Council (ARC) and the Cooperative Research Centre (CRC) program, as well as industry research funding. Lin also works closely with experts in other areas (e.g. cancer biology, marketing and eduction) to develop and apply data mining/machine learning and causal inference methods to solve real world problems.

Lin has been supervising PhD students in data mining, machine learning and bioinformatics. She also supervised PhD... Read more

UniSA STEM

Harnessing connections across science, technology, engineering and mathematics, UniSA STEM creates innovative solutions and groundbreaking developments across teaching, learning and research.

Tweets by @UniversitySA

Research

Research focus

Information and Computing Sciences
Information Systems
Artificial Intelligence and Image Processing
Biological Sciences
Mathematical Sciences

Highlights

Data mining
machine learning
Causal inference and causal discovery
Bioinformatics

Research

Outputs

Research outputs for the last seven years are shown below. Some long-standing staff members may have older outputs included. To see earlier years visit ORCID or Scopus

Open access indicates that an output is open access.

Highlights

Year	Output
2021	Zhang, W, Liu, L & Li, J 2021, 'Treatment effect estimation with disentangled latent factors', Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), Association for the Advancement of Artificial Intelligence, pp. 10923-10930. Open access
2020	Yu, K, Liu, L, Li, J, Ding, W & Le, TD 2020, 'Multi-source causal feature selection', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp.2240-2256. Open access 81 69
2017	Weijia Zhang , Le, TD, Liu, L, Zhou, Z-H & Li, J 2017, 'Mining heterogeneous causal effects for personalized cancer treatment', Bioinformatics, vol. 33, no. 15, pp. 2372-2378. Open access 30 30 4
2013	Le, TD, Liu, L, Tsykin, A, Goodall, GJ, Liu, B, Sun, B-Y & Li, J 2013, 'Inferring microRNA-mRNA causal regulatory relationships from expression data', Bioinformatics, vol. 29, no. 6, pp. 765-771. Open access 68 66
2010	Li, J, Liu, B, Green, JE, Zhu, M, Kim, CH, Tsykin, A, Goodall, G & Liu, L 2010, 'Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation', Bioinformatics, vol. 26, no. 24, pp. 3105-3111. Open access 85 83

Books

Year	Output
2015	Li, J, Liu, L & Le, TD 2015, Practical approaches to causal relationship exploration, Springer, US.

Chapters

Year	Output
2024	Park, JY, Liu, L, Liu, J & Li, J 2024, 'Causal disentanglement for adversarial defense', in T Liu et al. (eds), Australasian Joint Conference on Artificial Intelligence AI 2023: AI 2023: Advances in Artificial Intelligence, Springer, Singapore, ch. 25, pp. 315-327.
2023	Tabassum, F, Mubarak, S, Liu, L & Du, JT 2023, 'How many features do we need to identify bots on Twitter?', Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, Springer, Singapore, pt. 1, pp. 312-327. Open access 1
2023	Xu, T, Zhang, Y, Li, J, Liu, L, Xu, Z, Cheng, D & Feng, Z 2023, 'A data-driven approach to finding K for K nearest neighbor matching in average causal effect estimation', in F Zhang et al. (eds), Web Information Systems Engineering –WISE 202324th International Conference Melbourne, VIC, Australia, October 25–27, 2023 Proceedings, Springer, Singapore, ch. 55, pp. 723-732.
2023	Xu, Z, Liu, J, Cheng, D, Li, J, Liu, L & Wang, K 2023, 'Disentangled representation with causal constraints for counterfactual fairness', in H Kashima, T Ide & W Peng (eds), Pacific-Asia Conference on Knowledge Discovery and Data Mining: PAKDD 2023: Advances in Knowledge Discovery and Data Mining, Springer, Switzerland, pp. 471-482. Open access 1
2022	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2022, 'Recommending personalized interventions to increase employability of disabled jobseekers', in J Gama et al. (eds), Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part III, Springer, Switzerland, pp. 92-104. Open access 3 2
2020	Zhang, J, Nguyen, T, Truong, B, Liu, L, Li, J & Le, TD 2020, 'Computational methods for predicting autism spectrum disorder from gene expression data', ADMA 2020: Advanced Data Mining and Applications, Springer, Singapore, pp. 395-409.
2019	Le, TD, Ong, KL, Zhao, Y, Jin, WH, Wong, S, Liu, L & Williams, G 2019, 'Preface', Data mining: AusDM: Australasian Conference on Data Mining, Springer Nature, Singapore, pp. v-vi.
2014	Liu, L & Li, J 2014, 'Building Naïve Bayes Classifiers with high-dimensional and small-sized datasets', in A Agah (ed.), Medical applications of artificial intelligence, CRC Press, Boca Raton, Florida, ch. 8, pp. 115-135. Open access 16
2013	Liu, B, Liu, L, Tsykin, A, Goodall, G, Cairns, MJ & Li, J 2013, 'Discovering the functional microRNA-mRNA regulatory modules in heterogeneous data', in U Schmitz, O Wolkenhauer & J Vera (eds), MicroRNA cancer regulation : advanced concepts, bioinformatics and systems biology tools, Springer, UK, ch. 14, pp. 267-289. 2

Journal Articles

Year	Output
2024	Cheng, D, Li, J, Liu, L, Liu, J & Le, TD 2024, 'Data-driven causal effect estimation based on graphical causal modelling: a survey', Journal of the Association for Computing Machinery (ACM), vol. 56, no. 5, article no. 127, pp. 1-37. Open access 2
2024	Cheng, D, Li, J, Liu, L, Yu, K, Le, TD & Liu, J 2024, 'Discovering ancestral instrumental variables for causal inference from observational data', IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 8, pp. 11542-11552. Open access 5 2
2024	Deho, OB, Liu, L, Li, J, Liu, J, Zhan, C & Joksimovic, S 2024, 'When the past != the future: assessing the impact of dataset drift on the fairness of learning analytics models', IEEE Transactions on Learning Technologies, vol. 17, pp. 1007-1020.
2024	Furqon, M, Pratama, M, Liu, L, Habibullah, H & Dogancay, K 2024, 'Mixup domain adaptations for dynamic remaining useful life predictions', Knowledge-Based Systems, vol. 295, article no. 111783, pp. 1-13. Open access 2
2024	Guo, X, Yu, K, Liu, L, Cao, F & Li, J 2024, 'Causal feature selection with dual correction', IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 1, pp. 938-951. 7 5
2024	Liu, J, Li, J, Liu, L, Le, T, Ye, F & Li, G 2024, 'Fairmod: making predictions fair in multiple protected attributes', Knowledge and Information Systems, vol. 66, no. 3, pp. 1861-1884. 1
2024	Ma'sum, MA, Pratama, M, Lughofer, E, Liu, L, Habibullah & Kowalczyk, R 2024, 'Few-shot continual learning via flat-to-wide approaches', IEEE Transactions on Neural Networks and Learning Systems, online, pp. 1-13. Open access
2024	Ma'sum, MA, Sarkar, MR, Pratama, M, Ramasamy, S, Anavatti, S, Liu, L, Habibullah, H & Kowalczyk, R 2024, 'Dynamic long-term time-series forecasting via meta transformer networks', IEEE Transactions on Artificial Intelligence, vol. 5, no. 8, pp. 4258-4581. Open access
2024	Masum, MA, Pratama, M, Ramasamy, S, Liu, L & Habibullah, H 2024, 'Unsupervised few-shot continual learning for remote sensing image scene classification', IEEE Transactions on Geoscience and Remote Sensing, online, pp. 1-14. Open access
2024	Yu, K, Ling, Z, Liu, L, Li, P, Wang, H & Li, J 2024, 'Feature selection for efficient local-to-global Bayesian network structure learning', ACM Transactions on Knowledge Discovery from Data, vol. 18, no. 2, pp. 1-27. Open access
2024	Zhang, Z, Yao, J, Liu, L, Li, J, Li, L & Wu, X 2024, 'Partial label feature selection: an adaptive approach', IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 8, pp. 4178-4191. 1
2023	Bewong, M, Wondoh, J, Kwashie, S, Liu, J, Liu, L, Li, J, Islam, MZ & Kernot, D 2023, 'DATM: A novel data agnostic topic modelling technique with improved effectiveness for both short and long text', IEEE Access, vol. 11, pp. 1-11. Open access 1
2023	Cheng, D, Li, J, Liu, L, Yu, K, Le, TD & Liu, J 2023, 'Toward unique and unbiased causal effect estimation from data with hidden variables', IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 9, pp. 6108-6120. 10 13 1
2023	Cheng, D, Li, J, Liu, L, Zhang, J, Liu , J & Le, TD 2023, 'Local search for efficient causal effect estimation', IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 9, pp. 8823-8837. Open access 4
2023	Deho, OB, Joksimovic, S, Li, J, Zhan, C, Liu, J & Liu, L 2023, 'Should learning analytics models include sensitive attributes? Explaining the why', IEEE Transactions on Learning Technologies, vol. 16, no. 4, pp. 560-572. Open access 6
2023	Guo, X, Yu, K, Liu, L, Li, P & Li, J 2023, 'Adaptive Skeleton construction for accurate DAG Learning', IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 10, pp. 10526-10539. Open access 7
2023	Li, J, Liu, L, Zhang, S, Ma, S, Le, TD & Liu, J 2023, 'Causal heterogeneity discovery by bottom-up pattern search for personalised decision making', Applied Intelligence, vol. 53, no. 7, pp. 8180-8194. Open access 2
2023	Liu, J, Li, J & Liu, L 2023, 'FastOPM-a practical method for partial match of time series', Pattern Recognition, vol. 130, article no. 108808, pp. 1-12. Open access 1
2023	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2023, 'Personalized interventions to increase the employment success of people with disability', IEEE Transactions on Big Data, vol. 9, no. 6, pp. 1561-1574.
2023	Yang, S, Yu, K, Cao, F, Liu, L, Wang, H & Li, J 2023, 'Learning causal representations for robust domain adaptation', IEEE Transactions on Knowledge and Data Engineering, vol. 35, no. 3, pp. 2750-2764. Open access 20 14 1
2023	Yu, K, Cai, M, Wu, X, Liu, L & Li, J 2023, 'Multilabel feature selection: a local causal structure learning approach', IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 6, pp. 3044-3057. Open access 16 16 1
2023	Zhang, J, Liu, L, Wei, X, Zhao, C & Li, S 2023, 'Pan-cancer characterization of ncRNA synergistic competition uncovers potential carcinogenic biomarkers', PLoS Computational Biology, vol. 19, no. 10, pp. 1-28. Open access
2023	Zhang, Z, Liu, L, Li, J & Wu, X 2023, 'Integrating global and local feature selection for multi-label learning', ACM Transactions on Knowledge Discovery from Data, vol. 17, no. 1, article no. 4, pp. 1-37. Open access 5 1
2023	Zhang, Z, Zhang, Z, Yao, J, Liu, L, Li, J, Wu, G & Wu, X 2023, 'Multi-label feature selection via adaptive label correlation estimation', ACM Transactions on Knowledge Discovery from Data, vol. 17, no. 9, pp. 1-28. Open access 6
2022	Cheng, D, Li, J, Liu, L, Le, TD, Liu, J & Yu, K 2022, 'Sufficient dimension reduction for average causal effect estimation', Data Mining and Knowledge Discovery, vol. 36, no. 3, pp. 1174-1196. Open access 6 4 1
2022	Cifuentes Bernal, AM, Pham, VVH, Li, X, Liu, L, Li, J & Le, TD 2022, 'Dynamic cancer drivers: a causal approach for cancer driver discovery based on bio-pathological trajectories', Briefings in Functional Genomics, vol. 21, no. 6, pp. 455-465. Open access 1 1 2
2022	Deho, OB, Zhan, C, Li, J, Liu, J, Liu, L & Le, TD 2022, 'How do the existing fairness metrics and unfairness mitigation algorithms contribute to ethical learning analytics?', British Journal of Educational Technology, vol. 53, no. 4, pp. 822-843. Open access 31 17 2
2022	Li, X, Liu, L, Whitehead, C, Li, J, Thierry, B, Le, TD & Winter, M 2022, 'Identifying preeclampsia-associated genes using a control theory method', Briefings in Functional Genomics, vol. 21, no. 4, pp. 296-309. Open access 4 4
2022	Ling, Z, Yu, K, Liu, L, Li, J, Zhang, Y & Wu, X 2022, 'PSL: An algorithm for partial Bayesian network structure learning', ACM Transactions on Knowledge Discovery from Data, vol.16, no. 5, article no. 93, pp. 1-25. Open access 2 2
2022	Ling, Z, Yu, K, Zhang, Y, Liu, L & Li, J 2022, 'Causal learner: a toolbox for causal structure and Markov blanket learning', Pattern Recognition Letters, vol. 163, pp. 92-95. 14 13
2022	Zamecnik, A, Kovanović, V, Joksimović, S & Liu, L 2022, 'Exploring non-traditional learner motivations and characteristics in online learning: a learner profile study', Computers and Education: Artificial Intelligence, vol. 3, article no. 100051. Open access 18 13
2022	Zhang, J, Liu, L, Xu, T, Zhang, W, Li, J, Rao, N & Le, TD 2022, 'Time to infer miRNA sponge modules', Wiley interdisciplinary reviews. RNA, vol. 13, no. 2, pp. 1-21. Open access 14 12 2
2022	Zhang, J, Liu, L, Zhang, W, Li, X, Zhao, C, Li, S, Li, J & Le, TD 2022, 'miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation', Bioinformatics Advances, vol. 2, no. 1, article no. vbac063, pp. 1-3. Open access 1 1
2022	Zhang, W, Li, J & Liu, L 2022, 'A unified survey of treatment effect heterogeneity modelling and uplift modelling', ACM Computing Surveys, vol. 54, no. 8, article no. 162, pp. 1-36. Open access 29 26
2021	Cifuentes-Bernal, AM, Pham, VV, Li, X, Liu, L, Li, J & Le, TD 2021, 'A pseudotemporal causality approach to identifying miRNA-mRNA interactions during biological processes', Bioinformatics, vol. 37, no. 6, pp. 807-814. Open access 3 2 9
2021	Li, J, Zhang, W, Liu, L, Yu, K, Le, TD & Liu, J 2021, 'A general framework for causal classification', International Journal of Data Science and Analytics, vol. 11, no. 2, pp. 127-139. 5 6 3
2021	Li, X, Truong, B, Xu, T, Liu, L, Li, J & Le, TD 2021, 'Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis', BMC Bioinformatics, vol. 300, pp. 1-22. Open access 5 5 2
2021	Pham, VV, Li, X, Truong, B, Nguyen, T, Liu, L, Li, J & Le, TD 2021, 'The winning methods for predicting cellular position in the DREAM single-cell transcriptomics challenge', Briefings in Bioinformatics, vol. 22, no. 3, pp. 1-4. Open access 1 2 9
2021	Pham, VV, Liu, L, Bracken, CP, Nguyen, T, Goodall, GJ, Li, J & Le, TD 2021, 'pDriver: a novel method for unravelling personalized coding and miRNA cancer drivers', Bioinformatics, vol. 37, no. 9, pp. 3285-3292. Open access 11 10 2
2021	Pham, VVH, Liu, L, Bracken, C, Goodall, G, Li, J & Le, TD 2021, 'Computational methods for cancer driver discovery: a survey', Theranostics, vol. 11, no. 11, pp. 5553-5568. Open access 17 14 1
2021	Yu, K, Liu, L & Li, J 2021, 'A unified view of causal and non-causal feature selection', ACM Transactions on Knowledge Discovery from Data, vol. 15, no. 4, article no. 3436891, pp. 1-46. Open access 48 47
2021	Zhang, J, Liu, L, Xu, T, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2021, 'Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data', BMC Bioinformatics, vol.22, no. 1, article no. 578, pp. 1-19. Open access 9 9 11
2021	Zhang, J, Liu, L, Xu, T, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2021, 'miRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data', RNA Biology, vol. 18, no. 12, pp. 2308-2320. Open access 6 3
2020	Ansah, J, Liu, L, Kang, W, Liu, J & Li, J 2020, 'Leveraging burst in Twitter network communities for event detection', World Wide Web, vol. 23, no. 12, pp. 2851-2876. Open access 14 9 3
2020	Li, J, Liu, L, Le, TD & Liu, J 2020, 'Accurate data-driven prediction does not mean high reproducibility', Nature Machine Intelligence, vol. 2, pp. 13-15. 29 28 75
2020	Li, X, Liu, L, Goodall, GJ, Schreiber, A, Xu, T, Li, J & Le, TD 2020, 'A novel single-cell based method for breast cancer prognosis', PLoS Computational Biology, vol. 16, no. 8, article no. e1008133, pp. 1-20. Open access 13 13 12
2020	Pham, VV, Liu, L, Bracken, CP, Goodall, GJ, Li, J & Le, TD 2020, 'DriverGroup: a novel method for identifying driver gene groups', Bioinformatics, vol. 36, no. S2, pp. i583-i591. Open access 6 6 1
2020	Yu, K, Guo, X, Liu, L, Li, J, Wang, H, Ling, Z & Wu, X 2020, 'Causality-based feature selection: methods and evaluations', ACM Computing Surveys, vol. 53, no. 5, article no. 111, pp. 1-36. Open access 108 90 1
2020	Yu, K, Liu, L & Li, J 2020, 'Learning Markov blankets from multiple interventional data sets', IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 6, pp. 2005-2019. Open access 18 15
2020	Yu, K, Liu, L, Li, J, Ding, W & Le, TD 2020, 'Multi-source causal feature selection', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, no. 9, pp.2240-2256. Open access 81 69
2020	Zhan, C, Roughead, E, Liu, L, Pratt, N & Li, J 2020, 'Detecting high-quality signals of adverse drug-drug interactions from spontaneous reporting data', Journal of Biomedical Informatics, vol. 112, article no. 103603, pp. 1-13. Open access 9 7 1
2020	Zhan, C, Roughead, E, Liu, L, Pratt, N & Li, J 2020, 'Detecting potential signals of adverse drug events from prescription data', Artificial Intelligence in Medicine, vol. 104, article no. 101839, pp. 1-14. Open access 10 9 2
2020	Zhang, J, Xu, T, Liu, L, Zhang, W, Zhao, C, Li, S, Li, J, Rao, N & Le, TD 2020, 'LMSM: A modular approach for identifying lncRNA related miRNA sponge modules in breast cancer', PLoS Computational Biology, vol. 16, no. 4, article no. e1007851. Open access 17 17 3
2019	Bewong, M, Liu, J, Liu, L & Li, J 2019, 'Privacy preserving serial publication of transactional data', Information Systems, vol. 82, pp. 53-70. Open access 10 8
2019	Bewong, M, Liu, J, Liu, L, Li, J & Choo, K-KR 2019, 'A relative privacy model for effective privacy preservation in transactional data', Concurrency and Computation: Practice and Experience, vol. 31, no. 23, article no. e4923, pp. 1-13. Open access 6 6
2019	Choobdar, S, Ahsen, ME, Crawford, J, Tomasoni, M, Le, TD, Li, J, Liu, L, Zhang, W & Marbach, D and 168 other authors and 1 consortia 2019, 'Assessment of network module identification across complex diseases', Nature Methods, vol. 16, no. 9, pp. 843-852. Open access 167 162 101
2019	Helal, S, Li, J, Liu, L, Ebrahimie, E, Dawson, S & Murray, DJ 2019, 'Identifying key factors of student academic performance by subgroup discovery', International Journal of Data Science and Analytics, vol. 7, no. 3, pp. 227-245. Open access 36 28
2019	Kwashie, S, Liu, J, Li, J, Liu, L, Stumptner, M & Yang, L 2019, 'Certus: an effective entity resolution approach with graph differential dependencies (GDDs)', Proceedings of the VLDB Endowment, vol. 12, n o. 6, pp. 653-666. Open access 24 19
2019	Le, TD, Hoang, T, Li, J, Liu, L, Liu, H & Hu, S 2019, 'A fast PC algorithm for high dimensional causal discovery with multi-core PCs', IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 13, no. 9, pp. 1483-1495. Open access 72 62 7
2019	Ling, Z, Yu, K, Wang, H, Liu, L, Ding, W & Wu, X 2019, 'BAMB: A balanced markov blanket discovery approach to feature selection', ACM Transactions on Intelligent Systems and Technology, vol. 10, no. 5, article no. 52, pp. 1-25. 43 37
2019	MA, S, Liu, L, LI, J & LE, TD 2019, 'Data-driven discovery of causal interactions', International Journal of Data Science and Analytics, vol. 8, pp. 285-297. Open access 1 2
2019	Ma, S, Li, J, Liu, L & Le, TD 2019, 'Discovering context specific causal relationships', Intelligent Data Analysis, vol. 23, no. 4, pp. 917-931. Open access
2019	Pham, VV, 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', PLoS Computational Biology, vol. 15, no. 12, article no. e1007538, pp. 1-12. Open access 22 21 5
2019	Pham, VV, Zhang, J, Liu, L, Truong, B, 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, article no. 143, pp. 1-12. Open access 18 19 5
2019	Zhang, J, Le, TD, Liu, L & Li, J 2019, 'Inferring and analyzing module-specific lncRNA-mRNA causal regulatory networks in human cancer', Briefings in Bioinformatics, vol. 20, no. 4, pp. 1403-1419. Open access 34 32 1
2019	Zhang, J, Liu, L, Xu, T, Xie, Y, Zhao, C, Li, J & Le, TD 2019, 'MiRspongeR: An R/Bioconductor package for the identification and analysis of miRNA sponge interaction networks and modules', BMC Bioinformatics, vol. 20, no. 1, article no. 235, pp. 1-12. Open access 30 26 4
2019	Zhang, J, Pham, VVH, Liu, L, Xu, T, Truong, B, Li, J, Rao, N & Le, TD 2019, 'Identifying miRNA synergism using multiple-intervention causal inference', BMC Bioinformatics, vol. 20, article no. 613, pp. 1-11. Open access 10 11
2018	Helal, S, Li, J, Liu, L, Ebrahimie, E, Dawson, S, Murray, DJ & Long, Q 2018, 'Predicting academic performance by considering student heterogeneity', Knowledge-Based Systems, vol. 161, pp. 134-146. Open access 146 95
2018	Liu, L, Li, J, Zhang, K, Kıcıman, E & Kiyavash, N 2018, 'Guest editorial: special issue on causal discovery 2017', International Journal of Data Science and Analytics, vol. 6, no. 1, pp. 1-2. Open access 1
2018	Thuyen, T, Suriyanarayanan, T, Zeng, G, Le, TD, Liu, L, Li, J, Tong, C, Wang, Y & Seneviratne, CJ 2018, 'Use of haploid model of Candida albicans to uncover mechanism of action of a novel antifungal agent', Frontiers in Cellular and Infection Microbiology, vol. 8, article no. 164, pp. 1-14. Open access 14 13 1
2018	Xu, T, Su, N, Liu, L, Zhang, J, Wang, H, Zhang, W, Gui, J, Yu, K, Li, J & Le, T 2018, 'miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase', BMC Bioinformatics, vol. 19, article no. 514, pp. 1-10. Open access 49 44 1
2018	Yu, K, Liu, L, Li, J & Chen, H 2018, 'Mining Markov blankets without causal sufficiency', IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6333-6347. Open access 26 22
2018	Zhan, C, Roughead, E, Liu, L, Pratt, N & Li, J 2018, 'A data-driven method to detect adverse drug events from prescription data', Journal of Biomedical Informatics, vol. 85, pp. 10-20. Open access 9 8 2
2018	Zhang, J, Liu, L, Li, J & Le, TD 2018, 'LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer', Bioinformatics, vol. 34, no. 24, pp. 4232-4240. 57 54 2
2018	Zhang, W, Le, DT, Lui, L & Li, J 2018, 'Estimating heterogeneous treatment effect by balancing heterogeneity and fitness', BMC Bioinformatics, vol. 19, article no. 518, pp. 1-12. Open access 5 4 1
2018	Zhang, Z, Liu, L, Wang, H, Li, J, Hu, D, Yan, J, Algesheimer, R & Meierer, M 2018, 'Collective behavior learning by differentiating personal preference from peer influence', Knowledge-Based Systems, vol. 159, pp. 233-243. Open access 5 4
2018	Zhang, Z, Wang, H, Liu, L & Li, J 2018, 'Multi-label relational classification via node and label correlation', Neurocomputing, vol. 292, pp. 72-81. Open access 9 8
2017	Azfar, A, Choo, K-KR & Liu, L 2017, 'Forensic taxonomy of Android social apps', Journal of Forensic Sciences, vol. 62, no. 2, pp. 435-456. 21 16
2017	Azfar, A, Choo, K-KR & Liu, L 2017, 'Forensic taxonomy of android productivity apps', Multimedia Tools and Applications, vol. 76, no. 3, pp. 3313-3341. 19 16
2017	Le, TD, Zhang, J, Liu, L & Li, J 2017, 'Computational methods for identifying miRNA sponge interactions', Briefings in Bioinformatics, vol. 18, no. 4, pp. 577-590. Open access 73 65 2
2017	Li, J, Liu, L, Liu, J & Green, R 2017, 'Building Diversified Multiple Trees for classification in high dimensional noisy biomedical data', Health Information Science and Systems, vol. 5, no. 5, pp. 1-10. Open access 4
2017	Li, J, Ma, S, Le, T, Liu, L & Liu, J 2017, 'Causal Decision Trees', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 2, pp. 257-271. Open access 43 31 1
2017	Liu, H, Liu, L, Le, TD, Lee, I, Sun, S & Li, J 2017, 'Nonparametric sparse matrix decomposition for cross-view dimensionality reduction', IEEE Transactions on Multimedia, vol. 19, no. 8, article no. 7879190, pp. 1848-1859. 17 16
2017	Weijia Zhang , Le, TD, Liu, L, Zhou, Z-H & Li, J 2017, 'Mining heterogeneous causal effects for personalized cancer treatment', Bioinformatics, vol. 33, no. 15, pp. 2372-2378. Open access 30 30 4
2017	Xu, T, Le, TD, Liu, L, Su, N, Wang, R, Sun, B, Colaprico, A, Bontempi, G & Li, J 2017, 'CancerSubtypes: an R/Bioconductor package for molecular cancer subtype identification, validation and visualization', Bioinformatics, vol. 33, n. 19, pp. 3131-3133. Open access 165 162 16
2017	Zhang, J, Le, TD, Liu, L & Li, J 2017, 'Identifying miRNA sponge modules using biclustering and regulatory scores', BMC Bioinformatics, vol. 18, suppl. 3, article no. 44, pp. 1-12. Open access 18 16 2
2017	Zhang, J, Le, TD, Liu, L & Li, J 2017, 'Inferring miRNA sponge co-regulation of protein-protein interactions in human breast cancer', BMC Bioinformatics, vol. 18, no. 243, pp. 1-12. Open access 23 20 2
2016	Azfar, A, Choo, K- KR & Liu, L-L 2016, 'An android communication app forensic taxonomy', Journal of Forensic Sciences, vol. 61, no. 5, pp. 1337-1350. 39 30 1
2016	Azfar, A, Choo, R & Liu, L 2016, 'Android mobile VoIP apps: a survey and examination of their security and privacy', Electronic Commerce Research, vol.16, no. 1, pp. 73-111. Open access 23 31
2016	Li, J, Le, TD, Liu, L, Liu, J, Jin, Z, Sun, B & Ma, S 2016, 'From observational studies to causal rule mining', ACM Transactions on Intelligent Systems and Technology, vol. 7, no. 2, article no. 14. Open access 33 14 1
2016	Ma, S, Li, J, Liu, L & Le, TD 2016, 'Mining combined causes in large data sets', Knowledge-Based Systems, vol. 92, pp. 104-111. Open access 16 11
2016	Masud, K, Liu, L, Le, TD & Li, J 2016, 'Identification of miRNA-mRNA regulatory modules by exploring collective group relationships', BMC Genomics, vol. 17, no. S1, pp. 71-84. Open access 25 20 2
2016	Weijia Zhang , Le, TD, Liu, L, Zhou, Z-H & Li, J 2016, 'Predicting miRNA targets by integrating gene regulatory knowledge with expression profiles', PLoS One, vol. 11, no. 4, article no. e0152860, pp. 1-19. Open access 15 19 2
2016	Xu, T, Le, TD, Liu, L, Wang, R, Sun, B & Li, J 2016, 'Identifying cancer subtypes from miRNA-TFmRNA regulatory networks and expression data', PLoS One, vol. 11, no. 4, pp. 1-20. Open access 62 49 8
2016	Zhang, J, Le, TD, Liu, L, He, J & Li Jiuyong, 2016, 'A novel framework for inferring condition-specific TF and miRNA co-regulation of protein-protein interactions', Gene, vol. 557, no. 1, pp. 55-64. 9 10 1
2016	Zhang, J, Le, TD, Liu, L, He, J & Li, J 2016, 'Identifying miRNA synergistic regulatory networks in heterogeneous human data via network motifs', Molecular Biosystems, vol. 12, no. 2, pp. 454-463. 8 8 1
2015	Le, TD, Liu, L, Zhang, J, Liu, B & Li, J 2015, 'From miRNA regulation to miRNA-TF co-regulation: computational approached and challenges', Briefings in Bioinformatics, vol. 16, no. 9, pp. 475-496. Open access 37 31 2
2015	Le, TD, Zhang, J, Liu, L & Li, J 2015, 'Ensemble methods for MiRNA target prediction from expression data', PLoS One, vol. 10, no. 6, pp. 1-19. Open access 26 20 2
2015	Le, TD, Zhang, J, Liu, L, Liu, H & Li, J 2015, 'miRLAB: An R Based Dry Lab for Exploring miRNA-mRNA Regulatory Relationships', PLoS One, vol. 10, no. 12, pp.1-15. Open access 24 18 8
2014	Irwin, AS, Slay, J, Choo, K-KR & Lui, L 2014, 'Money laundering and terrorism financing in virtual environments: a feasibility study', Journal of Money Laundering Control, vol. 17, no. 1, pp. 50-75. Open access 23 10
2014	Zhang, J, Le, TD, Liu, L, Liu, B, He, J, Goodall, GJ & Li, J 2014, 'Inferring condition-specific miRNA activity from matched miRNA and mRNA expression data', Bioinformatics, v 30, no. 21, pp. 3070-3077. Open access 19 17 3
2014	Zhang, J, Le, TD, Liu, L, Liu, B, Jianfeng, H, Goodall, GJ & Li, J 2014, 'Identifying direct miRNA-mRNA causal regulatory relationships in heterogeneous data', Journal of Biomedical Informatics, vol. 52, pp. 438-447. Open access 25 23
2013	Irwin, AS, Slay, J, Choo, K-KR & Liu, L 2013, 'Are the financial transactions conducted inside virtual environments truly anonymous?: An experimental research from an Australian perspective', Journal of Money Laundering Control, vol. 16, no. 1, pp. 6-40. 10 3
2013	Le, TD, Liu, L, Liu, B, Tsykin, A, Goodall, G, Satou, K & Li, J 2013, 'Inferring microRNA and transcription factor regulatory networks in heterogeneous data', BMC Bioinformatics, vol. 14, article no. 92, pp. 1-13. Open access 37 38
2013	Le, TD, Liu, L, Tsykin, A, Goodall, GJ, Liu, B, Sun, B-Y & Li, J 2013, 'Inferring microRNA-mRNA causal regulatory relationships from expression data', Bioinformatics, vol. 29, no. 6, pp. 765-771. Open access 68 66
2013	Liu, H, Li, J, Liu, L, Liu, J, Lee, I & Zhao, J 2013, 'Exploring groups from heterogeneous data via sparse learning', in J Pei et al. (ed.), Advances in Knowledge Discovery and Data Mining. 17th Pacific-Asia Conference, PAKDD 2013, Springer, vol. 7818, pp. 556-567. 1
2012	Irwin, ASM, Choo, K-KR & Liu, L 2012, 'Modelling of money laundering and terrorism financing typologies', Journal of Money Laundering Control, vol. 15, no. 3, pp. 316-335. 22 12
2012	Irwin, ASM, Choo, KK & Liu, L 2012, 'An analysis of money laundering and terrorism financing typologies', Journal of Money Laundering Control, vol. 15, no. 1, pp. 85-111. Open access 46 16
2011	Zhang, Z, Liu, L, Li, J & Zhang, Z 2011, 'Spectral representation of protein sequences', Journal of Computational and Theoretical Nanoscience, vol. 8, no. 7, pp. 1335-1339. 7 6
2010	Li, J, Liu, B, Green, JE, Zhu, M, Kim, CH, Tsykin, A, Goodall, G & Liu, L 2010, 'Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation', Bioinformatics, vol. 26, no. 24, pp. 3105-3111. Open access 85 83
2009	Liu, B, Li, J, Tsykin, A, Liu, L, Guar, AB & Goodall, GJ 2009, 'Exploring complex miRNA-mRNA interactions with Bayesian networks by splitting-averaging strategy', BMC Bioinformatics, vol. 10, article no. 408. Open access 67 57
2008	Liu, L, Cozzolino, D, Cynkar, W, Dambergs, R, Janik, L, O'Neill, B, Colby, C & Gishen, M 2008, 'Preliminary study on the application of visible-near infrared spectroscopy and chemometrics to classify Riesling wines from different countries', Food Chemistry, vol. 106, no. 2, pp. 781-786. 118 111

Conferences

Year	Output
2024	Cheng, D, Xu, Z, Li, J, Liu, L, Liu, J & Le, TD 2024, 'Conditional instrumental variable regression with representation learning for causal inference', 12th International Conference on Learning Representations, ICLR 2024, International Conference on Learning Representations (ICLR), pp. 1-17. Open access
2024	Cheng, D, Xu, Z, Liu, L, Gao, W & Le, TD 2024, 'Instrumental variable estimation for causal inference in longitudinal data with time-dependent latent confounders', 38th AAAI Conference on Artificial Intelligence, AAAI 2024, Association for the Advancement of Artificial Intelligence, vol. 38, no. 10, pp. 11480-11488. Open access
2024	Guo, X, Yu, K, Liu, L & Li, J 2024, 'FedCSL: a scalable and accurate approach to federated causal structure learning', in M Wooldridge, J Dy & S Natarajan (eds), Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI Press, vol. 38, no. 11, pp. 12235-12243.
2024	Xu, Z, Cheng, D, Li, J, Liu, J, Liu, L & Yu, K 2024, 'Causal inference with conditional front-door adjustment and identifiable variational autoencoder', 12th International Conference on Learning Representations, ICLR 2024, International Conference on Learning Representations (ICLR), pp. 1-22. Open access
2023	Chen, X, Li, J, Liu, J, Peters, S, Liu, L, Le, TD & Walsh, A 2023, 'Improve interpretability of information bottlenecks for attribution with layer-wise relevance propagation', in J He et al. (eds), 2023 IEEE International Conference on Big Data (BigData), IEEE, pp. 1064-1069.
2023	Cheng, D, Xie, Y, Xu, Z, Li, J, Liu, L, Liu, J, Zhang, Y & Feng, Z 2023, 'Disentangled latent representation learning for tackling the confounding M-bias problem in causal inference', 23rd IEEE International Conference on Data Mining, ICDM 2023, IEEE, pp. 51-60. Open access 1
2023	Cheng, D, Xu, Z, Li, J, Liu, L, Le, TD & Liu, J 2023, 'Learning conditional instrumental variable representation for causal effect estimation', in D Koutra et al. (eds), European Conference, ECML PKDD 2023, Springer, pp. 525-540. 1
2023	Cheng, D, Xu, Z, Li, J, Liu, L, Liu, J & Le, DT 2023, 'Causal inference with conditional instruments using deep generative models', 37th AAAI Conference on Artificial Intelligence, AAAI 2023, Association for the Advancement of Artificial Intelligence, vol. 37, pp. 7122-7130. Open access 4
2023	Deho, OB, Joksimovic, S, Liu, L, Li, J, Zhan, C & Liu, J 2023, 'Assessing the fairness of course success prediction models in the face of (un)equal demographic group distribution', 10th ACM Conference on Learning @ Scale, L@S 2023, Association for Computing Machinery, pp. 48-58. 2 8
2023	Tran, HX, Le, TD, Li, J, Liu, L, Li, X, Liu, J & Waters, T 2023, 'Stabilising job survival analysis for disability employment services in unseen environments', 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM, pp. 4970-4980.
2023	Xu, Z, Cheng, D, Li, J, Liu, J, Liu, L & Wang, K 2023, 'Disentangled representation for causal mediation analysis', 37th AAAI Conference on Artificial Intelligence, AAAI 2023, Association for the Advancement of Artificial Intelligence, vol. 37, pp. 10666-10674. Open access 1
2022	Cheng, D, Li, J, Liu, L, Zhang, J, Le, TD & Liu, J 2022, 'Ancestral instrument method for causal inference without complete knowledge', in Luc De Raedt (ed.), Thirty-First International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 4843-4849. Open access
2022	Deho, BO, Liu, L, Joksimovic, S, Li, J, Zhan, C & Liu, J 2022, 'Assessing the causal impact of online instruction due to COVID-19 on students' grades and its aftermath on grade prediction models', 2022 ACM Conference on Information Technology for Social Good, Association for Computing Machinery, pp. 32-38. Open access
2022	Le, TD, Liu, L, Kiciman, E, Triantafyllou, S & Liu, H 2022, 'The KDD 2022 workshop on causal discovery (CD2022)', Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, article no. 181896, pp. 4884-4885. Open access
2022	Le, TD, Liu, L, Kıcıman, E, Triantafyllou, S & Liu, H 2022, 'Preface: the 2022 ACM SIGKDD workshop on causal discovery', Workshop on Causal Discovery, CD 2022, held in conjunction with the 2022 International Conference on Knowledge Discovery and Data Mining, KDD 2022, ML Research Press, vol. 185, pp. 1-2. Open access
2022	Park, JY, Liu, L, Liu, J & Li, J 2022, 'Randomize adversarial defense in a light way', IEEE International Conference on Big Data, Big Data 2022, IEEE, pp. 1080-1089. Open access 1
2022	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2022, 'What is the most effective intervention to increase job retention for this disabled worker?', the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, ACM - Association for Computing Machinery Inc, pp. 3981-3991. Open access 3
2022	Xu, Z, Xu, Z, Liu, J, Cheng, D, Li, J, Liu, L & Wang, K 2022, 'Assessing classifier fairness with collider bias', Springer, pp. 262-276. Open access 1 1
2022	Xuan Tran, H, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2022, 'Decision support for disability employment using counterfactual survival analysis', IEEE International Conference on Big Data, Big Data 2022, IEEE, pp. 2103-2112. Open access
2021	Lu, S, Liu, L, Li, J, Le, TD & Liu, J 2021, 'Divide and conquer: targeted adversary detection using proximity and dependency', in Z Gong, X Li, SG Oguducu, L Chen, BF Manjon, X Wu (eds), 12th IEEE International Conference on Big Knowledge, IEEE, pp. 125-132.
2021	Park, J-Y, Liu, L, Li, J & Liu, J 2021, 'Training neural networks with random noise images for adversarial robustness', CIKM '21, Association for Computing Machinery, pp. 3358-3362. Open access
2021	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2021, 'Intervention recommendation for improving disability employment', 8th IEEE International Conference on Big Data, Big Data 2020, IEEE, pp. 1671-1680. Open access 5 4
2021	Tran, HX, Le, TD, Li, J, Liu, L, Liu, J, Zhao, Y & Waters, T 2021, 'Recommending the most effective intervention to improve employment for job seekers with disability', The 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD'21), Association for Computing Machinery, pp. 3616-3626. Open access 9 6 31
2021	Zhang, W, Liu, L & Li, J 2021, 'Treatment effect estimation with disentangled latent factors', Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), Association for the Advancement of Artificial Intelligence, pp. 10923-10930. Open access
2020	Cheng, D, Li, J, Liu, L, Liu, J, Yu, K & Le, TD 2020, 'Causal query in observational data with hidden variables', in G De Giacomo et al. (eds), 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020, IOS Press, pp. 2551-2558. Open access 8
2020	Islam, MZ, Liu, J, Li, J, Liu, L & Kang, W 2020, 'Evidence weighted tree ensembles for text classification', 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, ACM, pp. 1737-1740. 1
2020	Liu, J, Li, J, Ye, F, Liu, L, Le, T, Xiong, P & Liu, H-c 2020, 'Building fair predictive models', in M Gallagher, N Moustafa & E Lakshika (eds), 33rd Australasian Joint Conference on Artificial Intelligence, AI 2020, Springer Nature, pp. 216-229. Open access
2020	Lu, S, Liu, L, Li, J, Le, TD & Liu, J 2020, 'LoPAD: A local prediction approach to anomaly detection', 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, Springer, vol. 12085, pp. 660-673. 2
2020	Zhang, W, Liu, L & Li, J 2020, 'Robust multi-instance learning with stable instances', in G De Giacomo et al. (eds), 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020, IOS Press, pp. 1682-1689. Open access 8
2019	Ansah, J, Kwashie, S, Liu, L, Liu, J, Kang, W & Li, J 2019, 'A graph is worth a thousand words: Telling event stories using timeline summarization graphs', World Wide Web Conference, WWW 2019, ACM Digital Library, pp. 2565-2571. Open access 27
2019	Islam, MZ, Liu, J, Li, J, Liu, L & Kang, W 2019, 'A semantics aware random forest for text classification', 28th ACM International Conference on Information and Knowledge Management, CIKM 2019, ACM, pp. 1061-1070. Open access 58
2019	Islam, MZ, Liu, J, Liu, L, Li, J & Kang, W 2019, 'Semantic explanations in ensemble learning', in Q Yang et al. (eds), 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, Springer, pp. 29-41. 3
2019	Liu, J, Kwashie, S, Li, J, Liu, L & Bewong, M 2019, 'Linking graph entities with multiplicity and provenance', in G Cheng, K Gunaratna, and J Wang (eds), 2nd International Workshop on EntitY REtrieval: EYRE’19, Rheinisch-Westfaelische Technische Hochschule Aachen Lehrstuhl Informatik V, vol. 2446, pp. 1-7. Open access
2019	Lu, S, Liu, L, Li, J & Le, TD 2019, 'Effective outlier detection based on Bayesian Network and Proximity', International Conference on Big Data, Big Data 2018, IEEE, article no. 8622230, pp. 134-139. Open access 4 3
2018	Ansah, J, Kang, W, Liu, L, Liu, J & Li, J 2018, 'Information propagation trees for protest event prediction', in Phung, D et al (eds), 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), Springer, pp. 777-789. 9
2018	Ansah, J, Kang, W, Liu, L, Liu, J & Li, J 2018, 'SensorTree: bursty propagation trees as sensors for protest event detection', in H Hacid et al. (eds), WISE: International conference on Web Information Systems Engineering, Springer, pp. 281-296. 6
2018	Le, TD, Xu, T, Liu, L, Shu, H, Hoang, T & Li, J 2018, 'ParallelPC: An R package for efficient causal exploration in genomic data', 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2018, Springer Nature, pp. 207-218. 8
2018	Zhang, Z, Li, J, Wang, H, Liu, L & Liu, J 2018, 'Which type of classifier to use for networked data, connectivity based or feature based?', in H Hacid et al. (eds), 19th International Conference on Web Information Systems Engineering, WISE 2018, Springer, pp. 364-380. Open access
2017	Bewong, M, Liu, J, Liu, L & Li, J 2017, 'Utility aware clustering for publishing transactional data', in J Kim et al (eds), 21st Pacific-Asia conference on knowledge discovery and data mining, Springer, pp. 481-494. 7
2017	Bewong, M, Liu, J, Liu, L, Li, J & Choo, K-KR 2017, 'A relative privacy model for effective privacy preservation in transactional data', 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 11th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Conference on Embedded Software and Systems, Trustcom/BigDataSE/ICESS 2017, IEEE, pp. 394-401. Open access 6 2
2017	Kang, W, Chen, J, Li, J, Liu, J, Liu, L, Osborne, G, Lothian, N, Cooper, B, Moschou, T & Neale, G 2017, 'Carbon: forecasting civil unrest events by monitoring news and social media', in G Cong et al. (eds), 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, Springer, pp. 859-865. Open access 10 7 1
2017	Le, TD, Zhang, J, Liu, L, Thanh Truong, BM, Hu, S, Xu, T & Li, J 2017, 'Identifying microRNA targets in epithelial-mesenchymal transition using joint-intervention causal inference', 8th International Conference on Computational Systems-Biology and Bioinformatics, (CSBio 2017), ACM - Association for Computing Machinery, pp. 34-41. 2
2017	Li, J, Liu, J, Liu, L, Thuc, DL, Ma, S & Han, Y 2017, 'Discrimination detection by causal effect estimation', IEEE International Conference on Big Data (IEEE Big Data), IEEE, pp. 1087-1094. Open access 10 6
2017	Liu, J, Liu, L & Chen, T 2017, 'Evaluating and improving SIP non-INVITE transaction to alleviate the losing race problem', in W van der Aalst & E Best (eds), 38th International Conference on Applications and Theory of Petri Nets and Concurrency, Springer, ch. 5, pp. 57-77. Open access 2 2
2016	Azfar, A, Choo, K-KR & Liu, L 2016, 'An android social app forensics adversary model', 49th Annual Hawaii International Conference on System Sciences, HICSS 2016, IEEE, vol. 2016, pp. 5597-5606. 34 10
2016	Chen, J, Kang, W, Li, J, Liu, J, Liu, L, Cooper, B, Lothian, N, Osborne, G & Moschou, T 2016, 'A temporal classification based predictive model of recurring societal events', The 14th Australasian Data Mining Conference (AusDM 2016), Australian Computer Society, pp. 93-99.
2015	Azfar, A, Choo, K-KR & Liu, L 2015, 'Forensic taxonomy of popular Android mHealth apps', Twenty-first Americas Conference on Information Systems, Association for Information Systems, pp. 1-19. Open access
2014	Azfar, A, Choo, KKR & Liu, L 2014, 'A study of ten popular Android mobile VoIP applications: are the communications encrypted?', in RH Sprague (ed.), 2014 47th Hawaii International Conference on System Sciences, IEEE, pp. 4838-4847. Open access 21 15 4
2014	Liu, J & Liu, L 2014, 'A coloured petri net approach to the functional and performance analysis of SIP non-INVITE transaction', in M Koutny, S Haddad & A Yakovlev (eds), 34th International Conference on Application and Theory of Petri Nets and Concurrency, Petri Nets 2013 and 13th International Conference on Application of Concurrency to System Design, ACSD 2013, Springer, pp. 147-177. 5
2014	Masud, K, Liu, L & Li, J 2014, 'Discovering collective group relationships', in E Burke & M Trick (eds), 25th Australasian Database Conference; ADC 2014, Springer, pp. 110-121. 2 2
2013	Li, J, Le, TD, Liu, L, Liu, J, Jin, Z & Sun, B 2013, 'Mining causal association rules', IEEE 13th International Conference on Data Mining Workshops 2013, IEEE Press, pp. 114-123. 38 29
2012	Jin, Z, Li, J, Liu, L, Le, TD, Sun, B & Wang, R 2012, 'Discovery of causal rules using partial association', 2012 IEEE 12th International Conference on Data Mining, IEEE, pp. 309-318. 26 21
2011	Liu, L 2011, 'Uncovering SIP vulnerabilities to DoS attacks using coloured Petri nets', 10th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), IEEE, pp. 29-36. Open access 7
2011	Wang, Y & Liu, L 2011, 'Controller design using coloured Petri nets: with a case study of the papermaking process control', 2011 International Conference on Modelling, Identification and Control, IEEE, article no. 5973741, pp. 415-421. Open access 2
2011	Zhang, Z, Liu, L, Li, J & Zhang, Z 2011, 'Spectral representation of DNA sequences and its application', 2010 IEEE Fifth International Conference on Bio-Inspired Computing, IEEE, article no. 5645116, pp. 1023-1027. Open access 5
2010	Liu, L 2010, 'Security analysis of Session Initiation Protocol- A Methodology Based on Coloured Petri Nets', in Professor Craig Valli, 1st International Cyber Resilience Conference, Security Research Centre, School of Computer and Security Science, Edith Cowan University, pp. 69-77.
2010	Liu, L, Li, Y, Liu, B & Li, J 2010, 'A simple yet effective data integration approach to tree-based microarray data classification', in Nigel Lovell, 32nd annual international conference of the IEEE engineering in medicine and biology society, IEEE, pp. 1503-1506. Open access 1
2009	Billington, J & Liu, L 2009, 'Recursive Parametric Automata and E-Removal', in David Lee, Antonia Lopes & Arnd Poetz, 11th International Conference on Formal Methods for Open Object-Based Distributed Systems, Springer, pp. 90-105. Open access
2009	Liu, L 2009, 'Verification of the SIP Transaction Using Coloured Petri Nets', in Bernard Mans, 32nd Australasian Computer Science Conference, Austrailan Computer Society, pp. 75-84. Open access 4
2008	Liu, L & Ding, LG 2008, 'Modelling and Analysis of the INVITE Transaction of the Session Initiation Protocol Using Coloured Petri Nets', in Kees M. van Hee, Rudiger Valk, Springer, pp. 132-151. 13 3

External engagement & recognition

Collaborations

Highlights

Associate editor of BMC Bioinformatics (2020 - present)
Associatte editor of IEEE Transactions on Aritificial Intelligence (2024 - present)
Editorial board member of International Journal of Data Science and Analytics (Springer) (2022 - present)
Steering committee member Australasian Data Mining (AusDM) conference series (2019 - present)
Conference co-chair of AusDM 2019, and PC co-chair of AusDM 2013, AusDM2014, and AusDM 2017)
Co-chair of SIGKDD Workshop on Causal Discovery in 2016, 2017, 2018, 2020 and 2022
PC member of leading AI/machine learning/data mining conferences, such as NeurIPS, ICML, AAAI, IJCAI, UAL, ICLR, KDD and PAKDD
Regular reviewer of journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Bioinformatics, Briefings in Bioinformatics, BMC Bioinformatics, and Artificial Intelligence in Medicine

External engagement & recognition

Collaborations

Organisation	Country
Agency for Science Technology & Research (ASTAR)	UNITED STATES
Agency for Science, Technology and Research (A*STAR)	SINGAPORE
Anhui University	CHINA
Arizona State University	UNITED STATES
Carnegie Mellon University	UNITED STATES
Charles Sturt University	AUSTRALIA
Children's Cancer Institute Australia	AUSTRALIA
Chinese Academy of Sciences	CHINA
Consilium Technology	AUSTRALIA
Consilium Technology Pty Ltd	AUSTRALIA
CSIRO Australia (Commonwealth Scientific Industrial Research organisation)	AUSTRALIA
CSIRO Data61	AUSTRALIA
Dali University	CHINA
Data to Decisions CRC	AUSTRALIA
Deakin University	AUSTRALIA
Defence Science and Technology Group	AUSTRALIA
East China Normal University	CHINA
Green Triangle Forest Industries Hub	AUSTRALIA
Guangxi University of Finance and Economics	CHINA
Hanson Institute	AUSTRALIA
Heifei University of Technology	CHINA
Hong Kong Baptist University	HONG KONG
Huazhong Agricultural University	CHINA
Huazhong University of Science and Technology	CHINA
Icahn School of Medicine at Mount Sinai	UNITED STATES
Institute of Medical and Veterinary Science	AUSTRALIA
Jiangsu University of Technology	CHINA
Johannes Kepler University of Linz	AUSTRIA
Kanazawa University	JAPAN
Kunming University of Science and Technology	CHINA
La Trobe University	AUSTRALIA
Lingnan University	HONG KONG
Max Planck Institute for Intelligent Systems	GERMANY
Maxima Training Group (Aust) Ltd.	AUSTRALIA
Microsoft	AUSTRALIA
Microsoft Research	UNITED KINGDOM
Ministry of Education	CHINA
Ministry of Education of the People's Republic of China	CHINA
Nanjing University	CHINA
National Cancer Institute	UNITED STATES
National University of Defense Technology	CHINA
National University of Singapore	SINGAPORE
Norris Cotton Cancer Center	UNITED STATES
Pham Ngoc Thach University of Medicine	VIET NAM
SA Pathology	AUSTRALIA
Shanxi University	CHINA
Simon Fraser University	CANADA
The Australian Wine Research Institute	AUSTRALIA
Tufts University	UNITED STATES
University Libre Bruxelles	BELGIUM
University of Adelaide	AUSTRALIA
University of Crete	GREECE
University of Electronic Science and Technology of China	CHINA
University of Illinois at Urbana-Champaign	UNITED STATES
University of Lausanne	SWITZERLAND
University of Massachusetts Boston	UNITED STATES
University of Melbourne	AUSTRALIA
University of Michigan	UNITED STATES
University of New South Wales	AUSTRALIA
University of Newcastle	AUSTRALIA
University of Pennsylvania	UNITED STATES
University of Pittsburgh	UNITED STATES
University of Science and Technology of China	CHINA
University of South Australia	AUSTRALIA
University of Zurich	SWITZERLAND
Yunnan Open University	CHINA
Zhejiang Normal University	CHINA

External engagement & recognition

Engagement/recognition	Year
Associate Editor BMC Bioinformatics	2022
Co-chair Association for Computing Machinery (ACM) SIGKDD Workshop on Causal Discovery	2022
Editorial board member International Journal of Data Science and Analytics	2022
Organising committee member & job-matching chair The 2021 IEEE International Conference on Data Mining (ICDM)	2022
Program committee member International Conference on Learning Representations (ICLR)	2022
Program committee member The Conference on Uncertainty in Artificial Intelligence (UAI)	2022
Program committee member ACM International Conference on Web Search and Data Mining (WSDM)	2022
Program committee member International Joint Conference on Artificial Intelligence	2022
Program committee member AAAI Conference on Artificial Intelligence (AAAI)	2022
Program committee member ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2022
Program committee member Annual Conference on Neural Information Processing Systems (NeurIPS)	2022
Steering Committee Member Australasian Data Mining Conference (AusDM)	2022
Associate Editor BMC Bioinformatics	2021
Best Application Paper Award 2020 IEEE International Conference on Big Data (IEEE BigData 2020)	2021
Outstanding Reviewer Award of NeurIPS 2021 35th Conference on Neural Information Processing Systems	2021
Outstanding Reviewer Award of WSDM 2021 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)	2021
Program committee member International Joint Conference on Artificial Intelligence	2021
Program committee member ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2021
Program committee member Annual Conference on Neural Information Processing Systems (NeurIPS)	2021
Program committee member AAAI Conference on Artificial Intelligence (AAAI)	2021
Program committee member ACM International Conference on Web Search and Data Mining (WSDM)	2021
Program committee member International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)	2021
Program committee member Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)	2021
Steering Committee Member Australasian Data Mining Conference (AusDM)	2021
Associate Editor BMC Bioinformatics	2020
Best Application Paper Award 2020 IEEE International Conference on Big Data (IEEE BigData 2020)	2020
Co-chair Association for Computing Machinery (ACM) SIGKDD Workshop on Causal Discovery	2020
Program committee member International Joint Conference on Artificial Intelligence	2020
Program committee member AAAI Conference on Artificial Intelligence (AAAI)	2020
Program committee member Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)	2020
Program committee member ACM International Conference on Web Search and Data Mining (WSDM)	2020
Steering Committee Member Australasian Data Mining Conference Series	2020
Conference Co-chair Australasian Data Mining Conference 2019	2019
Program committee member AAAI Conference on Artificial Intelligence (AAAI)	2019
Program committee member International Joint Conference on Artificial Intelligence	2019
Program committee member Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)	2019
Co-chair Association for Computing Machinery (ACM) SIGKDD Workshop on Causal Discovery	2018
Program Committee Member 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018), Melbourne	2018
Program Committee Member European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018)	2018
Program Committee Member The Web Conference 2018 (WWW 2018)	2018
Program Committee Member 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, USA	2018
Co-chair Association for Computing Machinery (ACM) SIGKDD Workshop on Causal Discovery	2017
Guest editor, Special issues on Causal Discovery, Spring International Journal of Data Science and Analytics	2017
Program Committee Co-chair 15th Australasian Data Mining Conference (AusDM)	2017
Program Committee Member 26th International Joint Conference on Artificial Intelligence	2017
Program Committee Member Australasian Computer Science Conference	2017
Program Committee Member Australasian Data Mining Conference	2017
Program Committee Member ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2017
Co-chair Association for Computing Machinery (ACM) SIGKDD Workshop on Causal Discovery	2016
Program Committee Member Australasian Data Mining Conference	2016
Program Committee Member Australasian Computer Science Conference	2016
Program Committee Member ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2016
Program Committee Member ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2015
Program Committee Member Australasian Data Mining Conference	2015
Program Committee Co-chair 12th Australasian Data Mining Conference (AusDM)	2014
Program Committee Member Australasian Data Mining Conference	2014
Co-chair 1st IEEE ICDM Workshop on Causal Discovery	2013
Program Committee Co-chair 11th Australasian Data Mining Conference (AusDM)	2013
Program Committee Member Australasian Data Mining Conference	2013
Program Committee Member Australasian Computer Science Conference	2013
Program Committee Member Australasian Data Mining Conference	2012
Program Committee Member International Conference on Application of Concurrency to System Design	2010
Program Committee Member 23rd Australasian Joint Conference on Artificial Intelligence	2010

Teaching & student supervision

Research degree supervision

Supervisions from 2010 shown

Thesis title	Student status
110459 - Advancing machine learning for human-machine partnership in decision making	Current
Advanced Continual Machine Learning	Current
Advanced continual reinforcement learning	Current
Computational methods for finding causal biomarkers and treatments for COVID-19	Current
Develop causal outcome prediction models for trustworthy interpretation	Current
Develop causality-based models for robust and adaptive drought predictions	Current
Developing causal-based methods for recommending the repurposed drugs for a disease and applications in breast cancer and SARS-CoV-2	Current
Developing Effective Algorithms for Estimating Causal Effects in Observational Network Data	Current
Heterogeneous Causal Effect of Price Promotion on Consumer Purchase Behaviour	Current
Image captioning and cognitive object classification	Current
Individual and intersectional group fairness in machine learning models	Current
Manipulation detection in social media combining text and rich structural features	Current
Transformer-based causal inference methods for temporal data with latent confounders	Current
Work-integrated learning for international students: Prepare them for working life in the global job market	Current
A data mining approach to analyse the influence of student features on their academic outcomes	Completed
A general model of forensic data recovery framework for digital CCTV systems	Completed
Causal inference with deep generative models	Completed
Computational causal discovery from observational data and application in bioinformatics	Completed
Computational modelling for breast cancer prognosis in precision medicine	Completed
Data governance in internet of things	Completed
Dependency-based anomaly detection and applications	Completed
Developing computational methods for detecting signals of adverse drug events from healthcare data	Completed
Developing data mining methods for finding causal relationships involving multiple factors	Completed
Developing data mining methods to reveal collective group relationships	Completed
Developing network inference methods for cancer driver discovery	Completed
Discovering functional miRNA-mRNA regulatory modules in data	Completed
Dynamic causal inference methods for modelling biological processes in cancer	Completed
Extracting insights from social media to predict, detect and summarize civil unrest	Completed
Forensic taxonomies of android apps (ForTAApps)	Completed
Improving adversarial robustness of machine learning models	Completed
Inferring miRNA-mRNA regulatory relationships using causal inference methods	Completed
Intervention recommendation for disability employment service	Completed
Investigating social media users' collaborative information seeking behaviours during group trip planning and the execution of travelling	Completed
Investigating the fairness of predictive learning analytics models in static and dynamic environments	Completed
Leveraging prediction semantics in ensemble methods for text classification	Completed
Money laundering and terrorism financing in virtual environments - a feasibility study	Completed
Privacy preserving publication of transactional data	Completed
Towards efficient and unbiased causal effect estimation from observational data	Completed

Professor Lin Liu

About me

About me

UniSA STEM

About me

Professional Associations

Experience

Qualifications

Research

Research focus

Highlights

Projects

Other projects

Outputs

Highlights

Books

Chapters

Journal Articles

Conferences

Current research & highlights

External engagement & recognition

Collaborations

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Collaborations

External engagement & recognition

Associate Editor

Co-chair

Editorial board member

Organising committee member & job-matching chair

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Steering Committee Member

Associate Editor

Best Application Paper Award

Outstanding Reviewer Award of NeurIPS 2021

Outstanding Reviewer Award of WSDM 2021

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Steering Committee Member

Associate Editor

Best Application Paper Award

Co-chair

Program committee member

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Steering Committee Member

Conference Co-chair

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Co-chair

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Co-chair

Guest editor, Special issues on Causal Discovery, Spring

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Co-chair

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