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. Wen, Z.; Deng, D.; Zhang, R.; Kotagiri, R. 2ED: An efficient entity extraction algorithm using two-level edit-distance. 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE. 2019, Vol. 2019-April, pp. 998-1009. DOI: 10.1109/ICDE.2019.00093
  2. He, J.; Qi, J.; Ramamohanarao, K. A joint context-aware embedding for trip recommendations. 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE. 2019, Vol. 2019-April, pp. 292-303. DOI: 10.1109/ICDE.2019.00034
  3. Moghaddam, SK.; Buyya, R.; Ramamohanarao, K. ACAS: An anomaly-based cause aware auto-scaling framework for clouds. Journal of Parallel and Distributed Computing. ACADEMIC PRESS INC ELSEVIER SCIENCE. 2019, Vol. 126, pp. 107-120. DOI: 10.1016/j.jpdc.2018.12.002
  4. Demirović, E.; Stuckey, PJ.; Bailey, J.; Chan, J.; Leckie, C.; Ramamohanarao, K.; 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. 2019, Vol. 11494 LNCS, pp. 241-257. DOI: 10.1007/978-3-030-19212-9_16
  5. Kottaram, A.; Johnston, LA.; Cocchi, L.; Ganella, EP.; Everall, I.; Pantelis, C.; Kotagiri, R.; Zalesky, A. Brain network dynamics in schizophrenia: Reduced dynamism of the default mode network. Human Brain Mapping. WILEY. 2019, Vol. 40, Issue 7, pp. 2212-2228. DOI: 10.1002/hbm.24519
  6. 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. 2019, Vol. 11448 LNCS, pp. 515-519. DOI: 10.1007/978-3-030-18590-9_78
  7. Correa, O.; Khan, AKMMR.; Tanin, E.; Kulik, L.; Ramamohanarao, K. Congestion-Aware Ride-Sharing. ACM Transactions on Spatial Algorithms and Systems. Association for Computing Machinery. 2019, Vol. 5, Issue 1. DOI: 10.1145/3317639
  8. Hassan, MU.; 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 INC ELSEVIER SCIENCE. 2019, Vol. 131, pp. 69-80. DOI: 10.1016/j.jpdc.2019.04.012
  9. Ilager, S.; Ramamohanarao, K.; Buyya, R. ETAS: Energy and thermal-aware dynamic virtual machine consolidation in cloud data center with proactive hotspot mitigation. Concurrency and Computation: Practice and Experience. Wiley. 2019, pp. e5221-e5221. DOI: 10.1002/cpe.5221
  10. Jia, Y.; Bailey, J.; Ramamohanarao, K.; Leckie, C.; Ma, X. Exploiting patterns to explain individual predictions. Knowledge and Information Systems. Springer Science and Business Media LLC. 2019. DOI: 10.1007/s10115-019-01368-9
  11. Gill, SS.; Garraghan, P.; Stankovski, V.; Casale, G.; Thulasiram, RK.; Ghosh, SK.; Ramamohanarao, K.; Buyya, R. Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge. Journal of Systems and Software. ELSEVIER SCIENCE INC. 2019, Vol. 155, pp. 104-129. DOI: 10.1016/j.jss.2019.05.025
  12. Mahmud, R.; Ramamohanarao, K.; Buyya, R. Latency-Aware Application Module Management for Fog Computing Environments. ACM Transactions on Internet Technology. ASSOC COMPUTING MACHINERY. 2019, Vol. 19, Issue 1. DOI: 10.1145/3186592
  13. Sarwar, T.; Ramamohanarao, K.; Zalesky, A. Mapping connectomes with diffusion MRI: deterministic or probabilistic tractography?. Magnetic Resonance in Medicine. WILEY. 2019, Vol. 81, Issue 2, pp. 1368-1384. DOI: 10.1002/mrm.27471
  14. Kardani-moghaddam, S.; Buyya, R.; Ramamohanarao, K. Performance anomaly detection using isolation-trees in heterogeneous workloads of web applications in computing clouds. Concurrency and Computation: Practice and Experience. Wiley Press. 2019, pp. e5306-e5306. DOI: 10.1002/cpe.5306
  15. Hashem, T.; Kulik, L.; Ramamohanarao, K.; Zhang, R.; Soma, SC. Protecting privacy for distance and rank based group nearest neighbor queries. World Wide Web. SPRINGER. 2019, Vol. 22, Issue 1, pp. 375-416. DOI: 10.1007/s11280-018-0570-5
  16. Mahmud, R.; Srirama, SN.; Ramamohanarao, K.; Buyya, R. Quality of Experience (QoE)-aware placement of applications in Fog computing environments. Journal of Parallel and Distributed Computing. ACADEMIC PRESS INC ELSEVIER SCIENCE. 2019, Vol. 132, pp. 190-203. DOI: 10.1016/j.jpdc.2018.03.004
  17. He, J.; Qi, J.; Ramamohanarao, K. Query-aware bayesian committee machine for scalable gaussian process regression. SIAM International Conference on Data Mining, SDM 2019. SIAM. 2019, pp. 208-216. DOI: 10.1137/1.9781611975673.24
  18. Ganji, M.; Chan, J.; Stuckey, PJ.; Bailey, J.; Leckie, C.; Ramamohanarao, K.; 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 International Publishing. 2019, Vol. 11052 LNAI, pp. 158-174. DOI: 10.1007/978-3-030-10928-8_10
  19. Zameni, M.; Sadri, A.; Ghafoori, Z.; Moshtaghi, M.; Salim, FD.; Leckie, C.; Ramamohanarao, K. Unsupervised online change point detection in high-dimensional time series. Knowledge and Information Systems. Springer Science and Business Media LLC. 2019. DOI: 10.1007/s10115-019-01366-x
  20. Zameni, M.; He, M.; Moshtaghi, M.; Ghafoori, Z.; Leckie, C.; Bezdek, JC.; Ramamohanarao, K. 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 International Publishing. 2019, Vol. 11053 LNAI, pp. 553-568. DOI: 10.1007/978-3-030-10997-4_34

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