Dr Sarah Monazam Erfani

  • Room: Level: 07 Room: 16
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Big Data (Scalable Learning, Data Integration, Data Analysis)
  • Computer Security & Privacy (Cybersecurity, Data Privacy)
  • Data Mining
  • Machine Learning

Biography

Sarah Erfani is a lecturer in the School of Computing and Information Systems (CIS) at The University of Melbourne. Research interests:

  • Artificial Intelligence
  • Machine Learning
  • Cyber Security
  • Large-scale Data Mining
  • Data Privacy

Recent publications

  1. Li, L.; Chan, CA.; Erfani, S.; Leckie, C. Adaptive Edge Caching based on Popularity and Prediction for Mobile Networks. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8851794
  2. Srivastava, N.; Velloso, E.; Lodge, JM.; Erfani, S.; Bailey, J. Continuous Evaluation of Video Lectures from Real-Time Difficulty Self-Report. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19. ACM Press. 2019. DOI: 10.1145/3290605.3300816
  3. Fahiman, F.; Disano, S.; Erfani, SM.; Mancarella, P.; Leckie, C. Data-Driven Dynamic Probabilistic Reserve Sizing Based on Dynamic Bayesian Belief Networks. IEEE Transactions on Power Systems. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2019, Vol. 34, Issue 3, pp. 2281-2291. DOI: 10.1109/TPWRS.2018.2884711
  4. Yang, M.; Rajasegarar, S.; Erfani, SM.; Leckie, C. Deep Learning and One-class SVM based Anomalous Crowd Detection. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8852256
  5. 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
  6. Su, Y.; Erfani, SM.; Zhang, R. MMF: Attribute Interpretable Collaborative Filtering. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8852452
  7. Moshtaghi, M.; Bezdek, JC.; Erfani, SM.; Leckie, C.; Bailey, J. Online cluster validity indices for performance monitoring of streaming data clustering. International Journal of Intelligent Systems. WILEY. 2019, Vol. 34, Issue 4, pp. 541-563. DOI: 10.1002/int.22064
  8. Fahiman, F.; Erfani, SM.; Leckie, C. Robust and Accurate Short-Term Load Forecasting: A Cluster Oriented Ensemble Learning Approach. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8852460
  9. Weerasinghe, S.; Erfani, SM.; Alpcan, T.; Leckie, C. Support vector machines resilient against training data integrity attacks. Pattern Recognition. Elsevier BV. 2019, Vol. 96. DOI: 10.1016/j.patcog.2019.106985
  10. 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
  11. Ma, X.; Wang, Y.; Houle, ME.; Zhou, S.; Erfani, SM.; Xia, S-T.; Wijewickrema, S.; Bailey, J. Dimensionality-Driven Learning with Noisy Labels. 35th International Conference on Machine Learning, ICML 2018. JMLR. 2018, Vol. 8, pp. 5332-5341.
  12. Ghafoori, Z.; Erfani, SM.; Rajasegarar, S.; Bezdek, JC.; Karunasekera, S.; Leckie, C. Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines. IEEE Transactions on Neural Networks and Learning Systems. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2018, Vol. 29, Issue 10, pp. 5057-5070. DOI: 10.1109/TNNLS.2017.2785792
  13. Rathore, P.; Bezdek, JC.; Erfani, SM.; Rajasegarar, S.; Palaniswami, M. Ensemble Fuzzy Clustering Using Cumulative Aggregation on Random Projections. IEEE Transactions on Fuzzy Systems. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2018, Vol. 26, Issue 3, pp. 1510-1524. DOI: 10.1109/TFUZZ.2017.2729501
  14. Cheng, W.; Erfani, S.; Zhang, R.; Ramamohanarao, K. Learning Datum-Wise Sampling Frequency for Energy-Efficient Human Activity Recognition. THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2018, pp. 2143-2150.
  15. Wang, Y.; Dai, B.; Kong, L.; Erfani, SM.; Bailey, J.; Zha, H. Learning deep hidden nonlinear dynamics from aggregate data. 34th Conference on Uncertainty in Artificial Intelligence 2018, UAI 2018. AUAI Press. 2018, Vol. 1, pp. 83-92.
  16. Zhou, S.; Erfani, S.; Bailey, J. Online CP Decomposition for Sparse Tensors. 2018 IEEE International Conference on Data Mining (ICDM). IEEE. 2018, Vol. 2018-November, pp. 1458-1463. DOI: 10.1109/ICDM.2018.00202
  17. Cheng, W.; Erfani, S.; Zhang, R.; Ramamohanarao, K. Predicting complex activities from ongoing multivariate time series. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2018, Vol. 2018-July, pp. 3322-3328.
  18. Han, Y.; Rubinstein, BIP.; Abraham, T.; Alpcan, T.; De Vel, O.; Erfani, S.; Hubczenko, D.; Leckie, C.; Montague, P. Reinforcement learning for autonomous defence in software-defined networking. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11199 LNCS, pp. 145-165. DOI: 10.1007/978-3-030-01554-1_9
  19. Amsaleg, L.; Bailey, J.; Barbe, D.; Erfani, S.; Houle, ME.; Nguyen, V.; Radovanovic, M. The vulnerability of learning to adversarial perturbation increases with intrinsic dimensionality. 2017 IEEE Workshop on Information Forensics and Security (WIFS). IEEE Explore. 2018, Vol. 2018-January, pp. 1-6. DOI: 10.1109/WIFS.2017.8267651
  20. 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.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile