Professor Rao Kotagiri

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

Research interests

  • Large Databases, Machine Leraning, Data Mining, Information Retrieval, Network Security, Big Data Analytics, Cloud Computing (Databases, Machine Leraning, Information Retrieval, Data mining)

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. Zhang X, Li Y, Kotagiri R, Wu L, Tari Z, Cheriet M. KRNN: k Rare-class Nearest Neighbour classification. PATTERN RECOGNITION. Pergamon-Elsevier Science. 2017, Vol. 62.
  2. Ghosh S, Li J, Cao L, Kotagiri R. Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns. Journal of Biomedical Informatics. Academic Press. 2017, Vol. 66.
  3. Roy P, Bhuiyari A, Lee KY, Wong TY, Kotagiri R. A novel computer aided quantification method of focal arteriolar narrowing using colour retinal image. COMPUTERS IN BIOLOGY AND MEDICINE. Pergamon-Elsevier Science. 2016, Vol. 74.
  4. Li H, Kulik L, Kotagiri R. Automatic Generation and Validation of Road Maps from GPS Trajectory Data Sets. 25th ACM International Conference on Information and Knowledge Management (CIKM). Association for Computing Machinery Inc.. 2016, Vol. 24-28-October-2016.
  5. Hussain M, Bhuiyan A, Turpin A, Luu C, Smith RT, Guymer R, Kotagiri R. Automatic Identification of Pathology Distorted Retinal Layer Boundaries using SD-OCT Imaging. IEEE Transactions on Biomedical Engineering. IEEE - Institute of Electrical and Electronic Engineers. 2016.
  6. Hussain M, Bhuiyan A, Kotagiri R. Automatic Retinal Minimum Distance Band (MDB)Computation from SD-OCT Images. 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015. 2016.
  7. Wu C, Buyya R, Kotagiri R. Big Data Analytics = Machine Learning + Cloud Computing. Big Data: Principles and Paradigms. 2016.
  8. Nguyen X, Chan J, Romano S, Bailey J, Leckie C, Kotagiri R, Pei J. Discovering outlying aspects in large datasets. DATA MINING AND KNOWLEDGE DISCOVERY. Kluwer Academic Publishers. 2016, Vol. 30, Issue 6.
  9. Liu Q, Li J, Wong L, Kotagiri R. Efficient mining of pan-correlation patterns from time course data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2016, Vol. 10086 LNAI.
  10. Poola D, Kotagiri R, Buyya R. Enhancing Reliability of Workflow Execution Using Task Replication and Spot Instances. ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS. Association for Computing Machinery Inc.. 2016, Vol. 10, Issue 4.
  11. Panyam NC, Verspoor C, Cohn T, Kotagiri R. Exploiting tree kernels for high performance chemical induced disease relation extraction. 7th International Symposium on Semantic Mining in Biomedicine (SMBM). 2016, Vol. 1650.
  12. Sanchez I, Aye Z, Rubinstein B, Kotagiri R. Fast trajectory clustering using Hashing methods. 2016 International Joint Conference on Neural Networks (IJCNN). 2016, Vol. 2016-October.
  13. Aye Z, Kotagiri R, Rubinstein B. Large Scale Metric learning. 2016 International Joint Conference on Neural Networks (IJCNN). 2016, Vol. 2016-October.
  14. Rashidi L, Kan A, Bailey J, Chan J, Leckie C, Liu W, Rajasegarar S, Kotagiri R. Node re-ordering as a means of anomaly detection in time-evolving graphs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2016, Vol. 9852 LNAI.
  15. Goel P, Kulik L, Kotagiri R. Privacy-Aware Dynamic Ride Sharing. ACM Transactions on Spatial Algorithms and Systems. 2016, Vol. 2, Issue 1.

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