Scholar
Ling Luo
Google Scholar ID: iDYAxCcAAAAJ
School of Computing and Information Systems, The University of Melbourne
Citations & Impact
Citations
463
H-index
9
i10-index
9
Publications
20
Co-authors
27
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published a book titled 'Temporal Modelling of Customer Behaviour' in the Springer Theses series; Awarded the Springer Theses Award in 2019 and the Google PhD Fellowship in Machine Learning in 2017; Published papers such as 'Dynamic customer segmentation via hierarchical fragmentation-coagulation processes' in the Machine Learning journal, and a survey on 'Bayesian Nonparametric Space Partitions' at IJCAI-21 Survey Track; The IJCAI-17 paper 'Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process' was highlighted in the press release opening the conference.
Research Experience
- Before joining the University of Melbourne, served as an Associate Lecturer at UTS and a postdoctoral research fellow in data analytics at Data61 (formerly NICTA), CSIRO. During her PhD studies, designed and applied novel techniques for customer behavior modeling.
Education
- PhD: 2017, in the area of data mining and machine learning from the University of Sydney; Supervisors: Associate Professor Irena Koprinska from the School of Computer Science, University of Sydney, and Associate Professor Bin Li from Fudan University. Bachelor's Degree: 2012, Bachelor of Engineering (Software Engineering) with Honours Class I, University of Sydney.
Background
- Research Interests: data mining, machine learning, temporal modelling, stochastic processes, and user behaviour pattern analysis. Brief Introduction: Lecturer at the School of Computing and Information Systems, University of Melbourne, Australia.
Miscellany
- Links include LinkedIn, Google Scholar, ORCID: https://orcid.org/0000-0002-1363-8308
