Professor Rao Kotagiri

  • Room: Level: 07 Room: 710
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Machine Learning, Artificial Intelligence, Data Mining, Big Data Analytics, Information Retrieval, Cloud Computing, Network Security. (Artificial Intelligence, Machine Learning, Data mining, Databases, Information Retrieval)

Personal webpage

http://www.cloudbus.org/rao/

Biography

Current research interests 

Machine Learning and Data mining
Robust Agent Systems
Information Retrieval
Intrusion Detection
Logic Programming and Deductive Databases
Distributed Systems
Bioinformatics and Medical Imaging

Recent publications

  1. Kardani Moghaddam S, Buyya R, Kotagiri R. ACAS: An anomaly-based cause aware auto-scaling framework for clouds. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING. Academic Press. 2019, Vol. 126. DOI: 10.1016/j.jpdc.2018.12.002
  2. Karazhma Kottaram A, Johnston L, Cocchi L, Ganella E, Everall I, Pantelis C, Kotagiri R, Zalesky A. Brain network dynamics in schizophrenia: Reduced dynamism of the default mode network. HUMAN BRAIN MAPPING. Wiley-Liss. 2019, Vol. 40, Issue 7. DOI: 10.1002/hbm.24519
  3. Ul Hassan M, Rehmani MH, Kotagiri R, Zhang J, Chen J. Differential privacy for renewable energy resources based smart metering. Journal of Parallel and Distributed Computing. Academic Press. 2019, Vol. 131. DOI: 10.1016/j.jpdc.2019.04.012
  4. Ilager S, Kotagiri R, Buyya R. ETAS: Energy and thermal-aware dynamic virtual machine consolidation in cloud data center with proactive hotspot mitigation. Concurrency Computation. John Wiley & Sons. 2019. DOI: 10.1002/cpe.5221
  5. Gill S, Garraghan P, Stankovski V, Casale G, Thulasiram RK, Ghosh SK, Kotagiri R, Buyya R. Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge. Journal of Systems and Software. Elsevier. 2019, Vol. 155. DOI: 10.1016/j.jss.2019.05.025
  6. Mahmud R, Kotagiri R, Buyya R. Latency-Aware Application Module Management for Fog Computing Environments. ACM TRANSACTIONS ON INTERNET TECHNOLOGY. Association for Computing Machinery Inc.. 2019, Vol. 19, Issue 1. DOI: 10.1145/3186592
  7. Sarwar T, Kotagiri R, Zalesky A. Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography?. MAGNETIC RESONANCE IN MEDICINE. John Wiley & Sons. 2019, Vol. 81, Issue 2. DOI: 10.1002/mrm.27471
  8. Kardani-Moghaddam S, Buyya R, Kotagiri R. Performance anomaly detection using isolation-trees in heterogeneous workloads of web applications in computing clouds. Concurrency Computation. John Wiley & Sons. 2019. DOI: 10.1002/cpe.5306
  9. Hashem T, Kulik L, Kotagiri R, Zhang R, Soma SC. Protecting privacy for distance and rank based group nearest neighbor queries. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS. Springer. 2019, Vol. 22, Issue 1. DOI: 10.1007/s11280-018-0570-5
  10. He J, Qi J, Kotagiri R. Query-aware bayesian committee machine for scalable gaussian process regression. SIAM International Conference on Data Mining, SDM 2019. 2019.
  11. 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
  12. 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
  13. 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
  14. Wang X, Qi J, Kotagiri R, Sun Y, Li B, Zhang R. A joint optimization approach for personalized recommendation diversification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018, Vol. 10939 LNAI. DOI: 10.1007/978-3-319-93040-4_47
  15. Correa O, Kulik L, Tanin E, Kotagiri R. Activity-based ride-sharing in action. GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2018. DOI: 10.1145/3274895.3274991

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