Wei Liu (刘伟)

    

Phone: +61 2 9514 3782

Email: wei.liu[at]uts.edu.au

Address: Room 11.07.307, Level 7, Building 11 (the Broadway building)PO Box 123, Broadway NSW 2007, AUSTRALIA


Lecturer at the Advanced Analytics Institute, School of Software, Faculty of Engineering and IT, the University of Technology, Sydney.

Visiting researcher in the Machine Learning Research Group at NICTA.

Before joining UTS, I was a Research Fellow at the University of Melbourne working with Rao Kotagiri, James Bailey, and Chris Leckie, and then a Machine Learning Researcher at NICTA working with the transportation industry. I was educated at the University of Sydney where I obtained my PhD degree in Sanjay Chawla's group. During my PhD, I visited Microsoft Research Asia in Yu Zheng's research group.

I have been publishing papers in the following research areas (which are my major research interests): tensor factorization, graph mining, causal inference, game theory, data imbalance handling, spatio-temporal data mining, discrimination-free learning, and anomaly detection.


Publications (here is my Google Scholar page):

      Selected top-tier papers: 
  • Khoa Nguyen, Wei Liu, Fang Chen, Peter Runcie, et al.: Using Tensor Analysis for Damage Identification in Civil Structures. In proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2015). Accepted as a Long Presentation -- acceptance rate 7%
    ERA ranking: A
  • Xinxin Jiang, Wei Liu, Longbing Cao, Guodong Long: Coupled Collaborative Filtering for Context-aware Recommendation. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015). 
    ERA ranking: A
  • Jingyu Shao, Junfu Yin, Wei Liu, Longbing Cao: Actionable Combined High Utility Itemset Mining. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015). 
    ERA ranking: A
  • Fei Wang, Wei Liu, Sanjay Chawla: On Sparse Feature Attacks in Adversarial Learning. In proceedings of the 2014 IEEE International Conference on Data Mining (ICDM 2014). (Acceptance rate: 19%)
    ERA ranking: A
  • Wei Liu, Dong Lee, and Rao Kotagiri: Significantly Improving General Supervised Learners by Using Local Information.  In proceedings of the 23rd ACM Conference on Information and Knowledge Management (CIKM 2014). (Acceptance rate: 17%)
    ERA ranking: A
  • Victor Chu, Wei Liu, Raymond Wong, Fang Chen, and Charles Perng: Traffic Analysis as a Service via a Unified Model. In proceedings of the 11th IEEE International Conference on Services Computing (IEEE SCC 2014). 
    ERA ranking: A
  • Victor Chu, Wei Liu, Raymond Wong, and Fang Chen: Causal Structure Discovery for Spatio-temporal Data. In proceedings of the 19th International Conference on Database Systems for Advanced Applications (DASFAA 2014). 
    ERA ranking: A
  • Jeffrey Chan, Wei Liu, James Bailey, Christopher Leckie, and Rao Kotagiri: Structure-aware Distance Measures for Comparing Clusterings in Graphs. In proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014). 
    ERA ranking: A

         Other papers

      • Linsey Pang, Sanjay Chawla, Wei Liu and Yu Zheng: On Detection of Emerging Anomalous Traffic Patterns Using GPS Data. Data & Knowledge Engineering journal, vol. 87, pages 357-373, 2013. 
        ERA ranking: B
           

         Thesis


      Current Student Collaboration / Supervision:

      • Shoujin Wang, PhD student, on non-i.i.d. pattern mining 
      • Xinxin Jiang, PhD student, on context-aware recommendation systems
      • Ling Luo, PhD student, on causal inference for spatio-temporal data   
      • Fei Wang, PhD student, on game theory for machine learning  

      Completed Student Supervision / Collaboration

      • Victor Chu, PhD student, causal structure discovery from road traffic data  
      • Goce Ristanoski, PhD student, on time series regression (with Prof James Bailey) 
      • Mohammad Mazraehshahi, Master student, on soft-cut decision trees (with Prof Rao Kotagiri)
      • DongHawn Lee, Master student, on lazy learning methods (with Prof Rao Kotagiri) 
      • Jinheng Liu, Master student, ensembles for outlier detection
      • Emma Wang, Master student, feature creation for Bagging 
      • Chun Yuan Lee, Summer intern student, Causality Models for Understanding Road Traffic Changes
      • Amogh Sarda, Summer intern student, Incident impact analysis by earning historical road traffic data 
      • Han Zhou, Summer intern student, Mining social networks for early detection of events  
      • Zeyang Yu, Summer intern student, on Twitter-based road incident detection. 
      • Mingxuan Li, Summer intern student (winner of NICTA summer scholar prize), on mining dynamic road traffics.

       

      My Readings/Focus (some via library login)

        A* / A ranking venues (rankings are from arc.gov.au):

       Others: