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. 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.
  2. 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. 2017, Vol. 64, Issue 7.
  3. Wen Z, Li B, Kotagiri R, Chen J, Chen Y, Zhang R. Improving efficiency of SVM k-fold cross-validation by alpha seeding. 31st AAAI Conference on Artificial Intelligence, AAAI 2017. 2017.
  4. Neelofar N, Naish L, Lee J, Kotagiri R. Improving spectral-based fault localization using static analysis. Software - Practice and Experience. John Wiley & Sons. 2017, Vol. 47, Issue 11.
  5. 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.
  6. Zhang X, Dou W, He Q, Zhou R, Leckie C, Kotagiri R, Salcic Z. LSHiForest: A Generic Framework for Fast Tree Isolation based Ensemble Anomaly Analysis. 2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017). IEEE Computer Society. 2017.
  7. Wen Z, Zhang R, Kotagiri R, Yang L. Scalable and fast SVM regression using modern hardware. World Wide Web. Springer. 2017.
  8. 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.
  9. Kotagiri R, Xie H, Kulik L, Karunasekera S, Tanin E, Zhang R, Bin Khunayn E. SMARTS: Scalable Microscopic Adaptive Road Traffic Simulator. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY. ACM Press. 2017, Vol. 8, Issue 2.
  10. Neelofar N, Naish L, Kotagiri R. Spectral-based fault localization using hyperbolic function. Software - Practice and Experience. John Wiley & Sons. 2017.
  11. Bin Khunayn E, Karunasekera S, Xie H, Kotagiri R. Straggler Mitigation for Distributed Behavioral Simulation. 2017 IEEE 37TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2017). IEEE Computer Society. 2017. Editors: Lee K, Liu L.
  12. Vedernikov O, Kulik L, Kotagiri R. The hitchhiker's guide to the optimal route planning. Proceedings - 18th IEEE International Conference on Mobile Data Management, MDM 2017. 2017.
  13. 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.
  14. 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.
  15. 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.

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