Sanjay Chawla

PhD (University of Tennessee)
Professor

Contact Information

Office: School of IT, J12. Room 4W-424.
Phone: +61 2 9351 3516
Email: fname.lname@sydney.edu.au

Sound Advice

"....For years, I always responded to students who asked, "Can I do this?" by saying something like, "You can do anything you want, but if you use Method M, you'll be open to criticism Z. You can argue your case effectively, however, if you use procedure P and are lucky enough to get result R. If you don't get R, then I am afraid you'll have to settle for a weaker claim. ''
--Robert P. Abelson in Statistics as a Principled Argument

Research Interests

My interests straddle data mining, machine learning and spatial data management. I also enjoy discussing philosophical issues related to data mining. My current emphasis is on problems such as :

  • Anomaly detection in high dimensional space.
  • Classification for imbalanced data.
  • Learning in adversarial environments.

Best Paper Awards

  • An Efficient Adversarial Learning Strategy for Constructing Robust Classification Boundaries:
    Australasian Joint Conference on Artificial Intelligence 2012
  • On Mining Anomalous Patterns in Road Traffic Streams. ADMA (2) 2011:237 -251
  • Finding Local Anomalies in Very High Dimensional Space. IEEE ICDM 2010:128-137
  • Spatio-temporal Outlier Detection in Precipitation Data. KDD Workshop on Knowledge Discovery from Sensor Data 2008:115-133
  • Mining for Outliers in Sequential Databases. SIAM International Conference on Data Mining, 2006.

Recent Publications

  • Didi Surian, Sanjay Chawla: Mining Outlier Participants: Insights Using Directional Distributions in Latent Models (Accepted ECML-PKDD 2013)
  • Aditya Menon, Harikrishna Narasimhan, Shivani Agarwal and Sanjay Chawla: On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance. (ICML, 2013) [PDF].
  • Sanjay Chawla, Aris Gionis: k-means--:A Unified Approach to Clustering and Outlier Detection. (To appear in SDM 2013)[PDF]
  • Sanjay Chawla, Yu Zheng, Jiafeng Hu: Inferring the Root Cause in Road Traffic Anomalies. IEEE ICDM 2012: 141-150
  • Timothy de Vries, Hui Ke, Sanjay Chawla and Peter Christen: Robust Record Linkage Blocking using Suffix Arrays and Bloom Filters. ACM Transactions on Knowledge Discovery from Data (TKDD). Volume 5, Number 2, February 2011. DOI 10.1145/1921632.1921635 [PDF] [BibTeX]
  • Timothy de Vries, Sanjay Chawla and Michael Houle: Density-preserving Projections for Large-scale Local Anomaly Detection. Knowledge and Information Systems. DOI 10.1007/s10115-011-0430-4 [PDF]
  • Timothy de Vries, Sanjay Chawla and Michael Houle: Finding Local Anomalies in Very High Dimensional Space. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM), Sydney, December 2010. ( Best Research Paper Award) [PDF]
  • Wei Liu and Sanjay Chawla: Mining Adversarial Patterns via Regularized Loss Minimization. Machine Learning (Special issue for ECML PKDD 2010). Volume 81, Issue 1, Pages 69-83. (Top Seven Papers at ECML) [PDF]

For a complete list, see my DBLP and my Google Scholar page.