Professor Christopher Leckie
- Data Mining, Network Intrusion Detection, Artificial Intelligence for Telecommunications, Bioinformatics
Chris Leckie is a Professor in the Department of Computing and Information Systems at The University of Melbourne.
- Artificial Intelligence (AI)
- 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.
- DemiroviĆ E, Stuckey PJ, Bailey J, Chan J, Leckie C, Kotagiri R, Guns T. An Investigation into PredictionÂ�Â�Optimisation for the Knapsack Problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2019, Vol. 11494 LNCS. DOI: 10.1007/978-3-030-19212-9_16
- 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
- Ma J, Chan J, Ristanoski G, Rajasegarar S, Leckie C. Bus travel time prediction with real-time traffic information. Transportation Research Part C: Emerging Technologies. Pergamon-Elsevier Science. 2019, Vol. 105. DOI: 10.1016/j.trc.2019.06.008
- Zameni M, Ghafoori Z, Sadri A, Leckie C, Kotagiri R. 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
- 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
- Weerasinghe S, Monazam Erfani S, 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. DOI: 10.1109/LCN.2018.8638065
- Jia Y, Bailey J, Kotagiri R, Leckie C, Ma X. Exploiting patterns to explain individual predictions. Knowledge and Information Systems. Springer London. 2019. DOI: 10.1007/s10115-019-01368-9
- 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
- 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
- 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
- Doan M, Qi J, Rajasegarar S, Leckie C. Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data. 2018 IEEE International Conference on Big Data (Big Data). IEEE. 2019. DOI: 10.1109/BigData.2018.8622122
- 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
- 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
- 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
- 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.
View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile