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. 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
  2. Hussain M, Bhuiyan A, Ishikawa H, Smith RT, Schuman JS, Kotagiri R. An automated method for choroidal thickness measurement from Enhanced Depth Imaging Optical Coherence Tomography images. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS. Pergamon. 2018, Vol. 63. DOI: 10.1016/j.compmedimag.2018.01.001
  3. Hussain MA, Bhuiyan A, Luu C, Smith RT, Guymer R, Ishikawa H, Schuman JS, Kotagiri R. Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm. PLOS ONE. Public Library of Science. 2018, Vol. 13, Issue 6. DOI: 10.1371/journal.pone.0198281
  4. Liu Q, Ghosh S, Li J, Wong L, Kotagiri R. Discovering pan-correlation patterns from time course data sets by efficient mining algorithms. 12th International Conference on Advanced Data Mining and Applications (ADMA). Springer Wien. 2018, Vol. 100, Issue 4. DOI: 10.1007/s00607-018-0606-9
  5. Panyam NC, Verspoor C, Cohn T, Kotagiri R. Exploiting graph kernels for high performance biomedical relation extraction. JOURNAL OF BIOMEDICAL SEMANTICS. Biomed Central. 2018, Vol. 9. DOI: 10.1186/s13326-017-0168-3
  6. Aye Z, Rubinstein B, Kotagiri R. Fast manifold landmarking using locality-sensitive hashing. 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_36
  7. Ganji M, Chan J, Stuckey P, Bailey J, Leckie C, Kotagiri R, Davidson I. Image constrained blockmodelling: A constraint programming approach. SIAM International Conference on Data Mining, SDM 2018. 2018.
  8. Dissanayake CM, Kotagiri R, Halgamuge MN, Moran B. Improving accuracy of elephant localization using sound probes. APPLIED ACOUSTICS. Elsevier Science. 2018, Vol. 129. DOI: 10.1016/j.apacoust.2017.07.007
  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. Springer. 2018. DOI: 10.1007/s11280-018-0570-5
  10. Mahmud R, Srirama SN, Kotagiri R, Buyya R. Quality of Experience (QoE)-aware placement of applications in Fog computing environments. Journal of Parallel and Distributed Computing. Academic Press. 2018. DOI: 10.1016/j.jpdc.2018.03.004
  11. Wen Z, Zhang R, Kotagiri R, Yang L. Scalable and fast SVM regression using modern hardware. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS. Springer. 2018, Vol. 21, Issue 2. DOI: 10.1007/s11280-017-0445-1
  12. Kottaram A, Johnston L, Ganella E, Pantelis C, Kotagiri R, Zalesky A. Spatio-temporal dynamics of resting-state brain networks improve single-subject prediction of schizophrenia diagnosis. Human Brain Mapping. Wiley-Liss. 2018. DOI: 10.1002/hbm.24202
  13. Neelofar N, Naish L, Kotagiri R. Spectral-based fault localization using hyperbolic function. SOFTWARE-PRACTICE & EXPERIENCE. John Wiley & Sons. 2018, Vol. 48, Issue 3. DOI: 10.1002/spe.2527
  14. Xie H, Karunasekera S, Kulik L, Tanin E, Zhang R, Kotagiri R. A Simulation Study of Emergency Vehicle Prioritization in Intelligent Transportation Systems. 2017 IEEE 85TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING). IEEE. 2017, Vol. 2017-June. DOI: 10.1109/VTCSpring.2017.8108282
  15. 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

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