Dr Sarah Monazam Erfani

  • Room: Level: 07 Room: 14
  • 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 Department of Computing and Information Systems at The University of Melbourne. Research interests: - Machine Learning - Large-scale Data Mining - Cyber Security - Data Privacy

Recent publications

  1. Ghafoori Z, Monazam Erfani S, 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. 2018. DOI: 10.1109/TNNLS.2017.2785792
  2. Cheng W, Monazam Erfani S, Zhang R, Kotagiri R. Accurate recognition of the current activity in the presence of multiple activities. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2017, Vol. 10235 LNAI. DOI: 10.1007/978-3-319-57529-2_4
  3. Iredale T, Monazam Erfani S, Leckie C. An efficient visual assessment of cluster tendency tool for large-scale time series data sets. IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers. 2017. DOI: 10.1109/FUZZ-IEEE.2017.8015587
  4. Rathore P, Bezdek J, Monazam Erfani S, Rajasegarar S, Palaniswami M. Ensemble Fuzzy Clustering using Cumulative Aggregation on Random Projections. IEEE Transactions on Fuzzy Systems. IEE Institute of Electronic Engineers. 2017. DOI: 10.1109/TFUZZ.2017.2729501
  5. Moshtaghi M, Monazam Erfani S, Leckie C, Bezdek J. Exponentially Weighted Ellipsoidal Model for Anomaly Detection. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS. John Wiley & Sons. 2017, Vol. 32, Issue 9. DOI: 10.1002/int.21875
  6. Monazam Erfani S, Baktashmotlagh M, Moshtaghi M, Nguyen V, Leckie C, Bailey J, Kotagiri R. From shared subspaces to shared landmarks: A robust multi-source classification approach. 31st AAAI Conference on Artificial Intelligence (AAAI). 2017.
  7. Fahiman F, Bezdek J, Monazam Erfani S, Palaniswami M, Leckie C. Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms. IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers. 2017. DOI: 10.1109/FUZZ-IEEE.2017.8015525
  8. Fahiman F, Monazam Erfani S, Rajasegarar S, Palaniswami M, Leckie C. Improving load forecasting based on deep learning and K-shape clustering. Proceedings of the International Joint Conference on Neural Networks. 2017, Vol. 2017-May. DOI: 10.1109/IJCNN.2017.7966378
  9. Alipourchavary E, Monazam Erfani S, Leckie C. Summarizing significant changes in network traffic using contrast pattern mining. International Conference on Information and Knowledge Management, Proceedings. 2017, Vol. Part F131841. DOI: 10.1145/3132847.3133111
  10. Lyu L, Law YW, Monazam Erfani S, Leckie C, Palaniswami M. An Improved Scheme for Privacy-Preserving Collaborative Anomaly Detection. 2016 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATION WORKSHOPS (PERCOM WORKSHOPS). IEEE. 2016. DOI: 10.1109/PERCOMW.2016.7457159
  11. Ghafoori Z, Monazam Erfani S, Rajasegarar S, Karunasekera S, Leckie C. Anomaly Detection in Non-stationary Data: Ensemble based Self-Adaptive OCSVM. 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). IEEE. 2016, Vol. 2016-October. DOI: 10.1109/IJCNN.2016.7727507
  12. Monazam Erfani S, Rajasegarar S, Karunasekera S, Leckie C. High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning. PATTERN RECOGNITION. Pergamon-Elsevier Science. 2016, Vol. 58. DOI: 10.1016/j.patcog.2016.03.028
  13. Glennan T, Leckie C, Monazam Erfani S. Improved classification of known and unknown network traffic flows using semi-supervised machine learning. 21st Australasian Conference on Information Security and Privacy (ACISP). Springer Verlag. 2016, Vol. 9723. DOI: 10.1007/978-3-319-40367-0_33
  14. Monazam Erfani S, Baktashmotlagh M, Rajasegarar S, Nguyen V, Leckie C, Bailey J, Kotagiri R. R1STM: One-class support tensor machine with randomised kernel. 16th SIAM International Conference on Data Mining 2016, SDM 2016. 2016.
  15. Monazam Erfani S, Baktashmotlagh M, Moshtaghi M, Nguyen V, Leckie C, Bailey J, Kotagiri R. Robust domain generalisation by enforcing distribution invariance. 25th International Joint Conference on Artificial Intelligence (IJCAI). AAAI Press. 2016, Vol. 2016-January.

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