LiuW

Wei Liu

Researcher
Australian Technology Park Laboratory

Wei_Liu

Phone: +61 2 9376 2122

Email: wei.liu@nicta.com.au

Researcher in the machine learning research group at NICTA.

Honorary research fellow at the University of Melbourne.

Before joining NICTA at Sydney, I was a Research Fellow at the University of Melbourne. I completed my PhD at the University of Sydney in 2011. In 2010 I spent three months at Microsoft Research Asia as an intern.

For Potential Students:

We are actively seeking high-quality post-graduate research students in machine learning or data mining research. NICTA has excellent research environment, and is able to provide financial supports to both local and international students. NICTA has scholarship opportunities and enhanced PhD program with the University of Sydney, University of New South Wales, and other Australian universities. Please send your CV to me if you are interested.

Current Student Supervision/Collaboration:

Victor Chu, PhD student, on mining taxi trajectories (with Dr Raymond Wong and Prof Fang Chen)

Fei Wang, PhD student, on game theory for machine learning (with Prof Sanjay Chawla)
Goce Ristanoski, PhD student, on time series regression (with A/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)

Mingxuan Li, Summer Project student (winner of NICTA summer scholar prize), on mining dynamic road traffics (supervised by myself).

Teaching

I'm co-lecturing the Data Mining subject (COMP5318) at the University of Sydney.

My Publications:

Goce Ristanoski, Wei Liu, and James Bailey: Time-Dependent Loss Enhanced SVMs for Time Series Regression. In proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2013).
ERA ranking: A

Timothy Havens, James Bezdek, Christopher Leckie, Jeffery Chan, Wei Liu, James Bailey, Kotagiri Romamohanarao and Marimuthu Palaniswami: Clustering and Visualization of Fuzzy Communities In Social Networks. In proceedings of the 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013).
ERA ranking: A

Wei Liu, James Bailey, Christopher Leckie, Rao Kotagiri: Mining Labelled Tensors by Discovering both their Common and Discriminative Subspaces. In proceedings of the 2013 SIAM Conference on Data Mining (SDM 2013). (Supplementary material)
ERA ranking: A

Goce Ristanoski, Wei Liu, James Bailey: Time Series Forecasting using Distribution Enhanced Linear Regression. In proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013).
ERA ranking: A

Pengyi Yang, Wei Liu, Bingbing Zhou, Sanjay Chawla, Albert Zomaya: Ensemble-based wrapper methods for feature selection and class imbalance learning. In proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013).
ERA ranking: A

Wei Liu, Jeffrey Chan, James Bailey, Christopher Leckie and Rao Kotagiri: Utilizing Common Substructures to Speedup Tensor Factorization for Mining Dynamic Graphs. In proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM 2012). [Code]
ERA ranking: A

Wei Liu, Andrey Kan, James Bailey, Christopher Leckie, Jian Pei and Rao Kotagiri: On Compressing Weighted Time-evolving Graphs. In proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM 2012).
ERA ranking: A

Wei Liu, Sanjay Chawla, James Bailey, Christopher Leckie and Rao Kotagiri: An Efficient Adversarial Learning Strategy for Constructing Robust Classification Boundaries. In proceedings of the 25th Australasian Joint Conference on Artificial Intelligence (AI 2012).
This paper won the best paper award.
ERA ranking: B

Jeffrey Chan, Wei Liu, Christopher Leckie, James Bailey and Rao Kotagiri: SeqiBloc: Mining Multi-time Spanning Blockmodels in Dynamic Graphs. In proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2012), pages 651–659.
ERA ranking: A

Linsey Pang, Sanjay Chawla, Wei Liu and Yu Zheng: On Detection of Emerging Anomalous Traffic Patterns Using GPS Data. To appear in Data & Knowledge Engineering journal.
ERA ranking: B

Wei Liu: Advanced Algorithms for Knowledge Discovery from Imbalanced and Adervsrial Data.
PhD Thesis. August, 2011.

Wei Liu, Yu Zheng, Sanjay Chawla, Jing Yuan and Xing Xie: Discovering Causal Interactions among Spatio-Temporal Outliers from Traffic Data Streams. In Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2011), pages 1010–1018.
ERA ranking: A

Linsey Xiaolin Pang, Sanjay Chawla, Wei Liu and Yu Zheng: On Mining Emerging Patterns on Traffic Networks. In proceedings of the 7th International Conference on Advanced Data Mining and Applications (ADMA 2011).
This paper won the best paper award.
ERA ranking: B

Wei Liu and Sanjay Chawla: Class Confidence Weighted kNN Algorithms for Imbalanced Data Sets. In Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2011), Part II, pages 345–356.
ERA ranking: A

Wei Liu and Sanjay Chawla: A Quadratic Mean based Supervised Learning Model for Handling Data Skewness. In Proceedings of the 2011 SIAM International Conference on Data Mining (SDM 2011), pages 188–198.
ERA ranking: A

Wei Liu and Sanjay Chawla: Mining Adversarial Patterns via Regularized Loss Minimization. Machine Learning, vol. 81, num. 1, pages 69-83, 2010. [code]
This paper is selected as one of the seven best papers in ECML PKDD 2010.
ERA ranking: A*

Wei Liu, Sanjay Chawla, David Cieslak and Nitesh Chawla: A Robust Decision Tree Algorithm for Imbalanced Data Sets. In Proceedings of the Tenth SIAM International Conference on Data Mining (SDM 2010), pages 766-777. [code]
ERA ranking: A

Wei Liu and Sanjay Chawla: A Game Theoretical Model for Adversarial Learning. In Proceedings of the 2009 International Workshop on Domain Driven Data Mining joint with IEEE ICDM 2009, pages 25-30.
ERA ranking: C

Elizabeth Wu, Wei Liu, and Sanjay Chawla: Spatio-Temporal Outlier Detection in Precipitation Data. In Proceedings of SensorKDD 2008 workshop joint with KDD 2008. (I was in charge of the Approx-Grid algorithms in Section 4.2 and corresponding experiments.)
This paper won the best paper award.