Research interests

  • Artificial Intelligence and Image Processing
  • Knowledge Representation and Machine Learning (adversarial machine learning, anomaly detection)


Sandamal is a researcher in the adversarial machine learning group at the School of Computing and Information Systems, University of Melbourne. His research interests include adversarial machine learning, anomaly detection, and game theory.

Recent publications

  1. Weerasinghe, S.; Erfani, SM.; Alpcan, T.; Leckie, C.; Riddle, J. Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning. 2018 IEEE 43rd Conference on Local Computer Networks (LCN). IEEE. 2019, Vol. 2018-October, pp. 469-472. DOI: 10.1109/LCN.2018.8638065
  2. Weerasinghe, S.; Alpcan, T.; Erfani, SM.; Leckie, C.; Pourbeik, P.; Riddle, J. Deep Learning Based Game-Theoretical Approach to Evade Jamming Attacks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 11199, pp. 386-397. DOI: 10.1007/978-3-030-01554-1_22
  3. Alpcan, T.; Weerasinghe, P.; Kuijper, M.; Monazam Erfani, S.; Leckie, C. Unsupervised Adversarial Anomaly Detection using One-Class Support Vector Machines. . Hong Kong University of Science and Technology. 2018.