Professor Christopher Leckie

  • Room: Level: 07 Room: 7.11
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Data Mining, Network Intrusion Detection, Artificial Intelligence for Telecommunications, Bioinformatics

Personal webpage

http://scholar.google.com/citations?user=wUsI0cAAAAAJ

Biography

Chris Leckie is a Professor in the Department of Computing and Information Systems at The University of Melbourne.

Research interests
- Artificial Intelligence (AI)
- telecommunications
- machine learning, fault diagnosis, distributed systems and design automation 

Prof Leckie has a strong interest in developing AI techniques for a variety of applications in telecommunications, such as network intrusion detection, network management, fault diagnosis and wireless sensor networks. He also has an interest in scalable data mining algorithms for tasks such as clustering and anomaly detection with applications in bioinformatics.

Recent publications

  1. Rathore P, Ghafoori Z, Bezdek J, Palaniswami M, Leckie C. Approximating Dunn's Cluster Validity Indices for Partitions of Big Data. IEEE TRANSACTIONS ON CYBERNETICS. Institute of Electrical and Electronics Engineers. 2019, Vol. 49, Issue 5. DOI: 10.1109/TCYB.2018.2806886
  2. Zameni M, Ghafoori Z, Sadri A, Leckie C, Ramamohanarao K. Change Point Detection for Streaming High-Dimensional Time Series. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2019, Vol. 11448 LNCS. DOI: 10.1007/978-3-030-18590-9_78
  3. Fahiman F, Disano S, Monazam Erfani S, Mancarella P, Leckie C. Data-Driven Dynamic Probabilistic Reserve Sizing Based on Dynamic Bayesian Belief Networks. IEEE Transactions on Power Systems. IEEE - Institute of Electrical and Electronic Engineers. 2019, Vol. 34, Issue 3. DOI: 10.1109/TPWRS.2018.2884711
  4. Weerasinghe S, Monazam Erfani S, Alpcan T, Leckie C, Riddle J. Detection of Anomalous Communications with SDRs and Unsupervised Adversarial Learning. Proceedings - Conference on Local Computer Networks, LCN. 2019, Vol. 2018-October. DOI: 10.1109/LCN.2018.8638065
  5. Tang Z, Kuijper M, Chong MS, Mareels I, Leckie C. Linear system security-Detection and correction of adversarial sensor attacks in the noise-free case. AUTOMATICA. Pergamon-Elsevier Science. 2019, Vol. 101. DOI: 10.1016/j.automatica.2018.11.048
  6. Yan M, Chan C, Gygax A, Yan J, Campbell L, Nirmalathas A, Leckie C. Modeling the Total Energy Consumption of Mobile Network Services and Applications. ENERGIES. MDPIAG. 2019, Vol. 12, Issue 1. DOI: 10.3390/en12010184
  7. Moshtaghi M, Bezdek J, Monazam Erfani S, Leckie C, Bailey J. Online cluster validity indices for performance monitoring of streaming data clustering. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS. John Wiley & Sons. 2019, Vol. 34, Issue 4. DOI: 10.1002/int.22064
  8. Doan M, Qi J, Rajasegarar S, Leckie C. Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. 2019. DOI: 10.1109/BigData.2018.8622122
  9. Ganji M, Chan J, Stuckey P, Bailey J, Leckie C, Kotagiri R, Park L. Semi-supervised blockmodelling with pairwise guidance. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2019, Vol. 11052 LNAI. DOI: 10.1007/978-3-030-10928-8_10
  10. Zameni M, Sadri A, Ghafoori Z, Moshtaghi M, Salim FD, Leckie C, Kotagiri R. Unsupervised online change point detection in high-dimensional time series. Knowledge and Information Systems. Springer London. 2019. DOI: 10.1007/s10115-019-01366-x
  11. Zameni M, He M, Moshtaghi M, Ghafoori Z, Leckie C, Bezdek J, Kotagiri R. Urban sensing for anomalous event detection: Distinguishing between legitimate traffic changes and abnormal traffic variability. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2019, Vol. 11053 LNAI. DOI: 10.1007/978-3-030-10997-4_34
  12. Leckie C, Tang Z, Kuijper M, Mareels I. Attack correction for noise-free linear systems subject to sensor attacks. 23rd International Symposium on Mathematical Theory of Networks and Systems. 2018.
  13. Yang M, Rashidi L, Sridhara Rao A, Rajasegarar S, Ganji M, Palaniswami M, Leckie C. Cluster-based Crowd Movement Behavior Detection. 2018 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA). IEEE. 2018. Editors: Murshed M, Paul M, Asikuzzaman M, Pickering M, Natu A, Robleskelly A, You S, Zheng L, Rahman A. DOI: 10.1109/DICTA.2018.8615809
  14. Yang M, Rashidi L, Rajasegarar S, Leckie C, Sridhara Rao A, Palaniswami M. Crowd Activity Change Point Detection in Videos via Graph Stream Mining. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE. 2018, Vol. 2018-June. DOI: 10.1109/CVPRW.2018.00059
  15. Kumar D, Ghafoori Z, Bezdek J, Leckie C, Kotagiri R, Palaniswami M. Dealing with Inliers in Feature Vector Data. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS. World Scientific Publishing Co. 2018, Vol. 26. DOI: 10.1142/S021848851840010x

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