Research interests

  • Artificial Intelligence (machine learning, data mining)
  • Behaviour Analytics (temporal modelling for dynamic behaviour, behaviour pattern analytics, user segmentation)
  • Educational Data Mining (learning anlytics)

Personal webpage


Ling is a Lecturer at the School of Computing and Information Systems, University of Melbourne. Before joining UoM, Ling was an associate lecturer at UTS, and a postdoctoral research fellow at Analytics, Data61 (formerly NICTA), CSIRO. Ling completed PhD in the area of data mining and machine learning at the University of Sydney, 2017, under the supervision of Dr Irena Koprinska from the School of Computer Science, University of Sydney and Dr Bin Li from Data61 (now at Fudan University). Ling has been awarded the Springer Theses Award in 2019 and Google PhD Fellowship in Machine Learning in 2017. Ling received Bachelor of Engineering (Software) with Honours Class I in 2012 from the University of Sydney.

Recent publications

  1. Luo, L. Temporal Modelling of Customer Behaviour. . Springer International Publishing. 2020. DOI: 10.1007/978-3-030-18289-2
  2. Chang, Y.; Li, Z.; Zhang, B.; Luo, L.; Sowmya, A.; Wang, Y.; Chen, F. Recovering DTW Distance Between Noise Superposed NHPP. Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer. 2019, pp. 229-241. DOI: 10.1007/978-3-030-16145-3_18
  3. Luo, L.; Liu, W.; Koprinska, I.; Chen, F. DAAR: A Discrimination-Aware Association Rule Classifier for Decision Support. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2017, Vol. 10420, pp. 47-68. DOI: 10.1007/978-3-662-55608-5_3
  4. Luo, L.; Li, B.; Berkovsky, S.; Koprinska, I.; Chen, F. Online engagement for a healthier you: A case study of web-based supermarket health program. Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion. International World Wide Web Conferences Steering Committee. 2017, pp. 1053-1061. DOI: 10.1145/3041021.3055129
  5. Luo, L.; Li, B.; Koprinska, I.; Berkovsky, S.; Chen, F. Tracking the evolution of customer purchase behavior segmentation via a fragmentation-coagulation process. IJCAI. International Joint Conferences on Artificial Intelligence Organization. 2017, pp. 2414-2420. DOI: 10.24963/ijcai.2017/336
  6. Luo, L.; Li, B.; Koprinska, I.; Berkovsky, S.; Chen, F. Discovering Temporal Purchase Patterns with Different Responses to Promotions. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ASSOC COMPUTING MACHINERY. 2016, Vol. 24-28-October-2016, pp. 2197-2202. DOI: 10.1145/2983323.2983665
  7. Luo, L.; Li, B.; Berkovsky, S.; Koprinska, I.; Chen, F. Who Will Be Affected by Supermarket Health Programs? Tracking Customer Behavior Changes via Preference Modeling. Pacific Asia Conference on Knowledge Discovery and Data Mining. SPRINGER-VERLAG BERLIN. 2016, Vol. 9651, pp. 527-539. DOI: 10.1007/978-3-319-31753-3_42
  8. Luo, L.; Liu, W.; Koprinska, I.; Chen, F. Discovering Causal Structures from Time Series Data via Enhanced Granger Causality. Australasian Joint Conference on Artificial Intelligence. SPRINGER-VERLAG BERLIN. 2015, Vol. 9457, pp. 365-378. DOI: 10.1007/978-3-319-26350-2_32
  9. Luo, L.; Liu, W.; Koprinska, I.; Chen, F. Discrimination-Aware Association Rule Mining for Unbiased Data Analytics. International Conference on Big Data Analytics and Knowledge Discovery. SPRINGER-VERLAG BERLIN. 2015, Vol. 9263, pp. 108-120. DOI: 10.1007/978-3-319-22729-0_9
  10. Luo, L.; Koprinska, I.; Liu, W. Discrimination-Aware Classifiers for Student Performance Prediction. . International Educational Data Mining Society. 2015.
  11. Luo, L.; Taib, R. Assessing recovery from cognitive load through pen input. CHI’13 Extended Abstracts on Human Factors in Computing Systems. ACM Press. 2013, pp. 1353-1358. DOI: 10.1145/2468356.2468597
  12. Luo, L.; Taib, R.; Anthony, L.; Lai, J. Further Investigating Pen Gesture Features Sensitive to Cognitive Load. . Workshop on Interacting with Smart Objects, International Conference on Intelligent User Interfaces. 2013, pp. 10-10.