Professor Rui Zhang

  • Room: Level: 07 Room: 7.05
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Big Data
  • Cloud Computing
  • Data Mining
  • Data analysis Data analytics
  • Database systems
  • Management of Data and Information
  • artificial intelligence (AI)

Personal webpage

http://www.ruizhang.info

Biography

Rui Zhang is a Professor and Reader in the Department of Computing and Information Systems at The University of Melbourne. He has been an Australian Research Council Future Fellow (http://www.arc.gov.au/ncgp/futurefel/future_default.htm).

He obtained his Bachelor Degree from Tsinghua University and PhD from National University of Singapore. He has been a visiting scientist at AT&T labs-research New Jersey, Microsoft Research Redmond, and Microsoft Research Asia.

His research interest includes big data, cloud computing, database, data mining, artificial intelligence, deep learning and information management in general, particularly in areas of indexing techniques, moving object management, web services, data streams and sequence databases.

If you are looking for a PhD supervisor, please visit my personal website (http://www.ruizhang.info) before sending me an email.

Recent publications

  1. Wang S, Bao Z, Huang S, Zhang R. A unified processing paradigm for interactive location-based web search. WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining. 2018, Vol. 2018-Febuary. DOI: 10.1145/3159652.3159667
  2. Li M, Bao Z, Sellis T, Yan S, Zhang R. HomeSeeker: A visual analytics system of real estate data. JOURNAL OF VISUAL LANGUAGES AND COMPUTING. Academic Press - Elsevier Science. 2018, Vol. 45. DOI: 10.1016/j.jvlc.2018.02.001
  3. 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. 2018. DOI: 10.1007/s11280-018-0570-5
  4. 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
  5. Wang X, Wen J-R, Dou Z, Sakai T, Zhang R. Search Result Diversity Evaluation Based on Intent Hierarchies. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. IEEE Computer Society. 2018, Vol. 30, Issue 1. DOI: 10.1109/TKDE.2017.2729559
  6. Zheng T, Zheng X, Zhang Y, Deng Y, Dong EX, Zhang R, Liu X. SmartVM: a SLA-aware microservice deployment framework. World Wide Web. Springer. 2018. DOI: 10.1007/s11280-018-0562-5
  7. 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
  8. 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
  9. Sun Y, Yuan NJ, Xie X, McDonald K, Zhang R. Collaborative Intent Prediction with Real-Time Contextual Data. ACM TRANSACTIONS ON INFORMATION SYSTEMS. Association for Computing Machinery Inc.. 2017, Vol. 35, Issue 4. DOI: 10.1145/3041659
  10. Aljubayrin S, Qi J, Jensen CS, Zhang R, He Z, Li Y. Finding lowest-cost paths in settings with safe and preferred zones. VLDB JOURNAL. Springer. 2017, Vol. 26, Issue 3. DOI: 10.1007/s00778-017-0455-8
  11. 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.
  12. 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. DOI: 10.1145/2898363
  13. Gu Y, Liu G, Qi J, Xu H, Yu G, Zhang R. The Moving K Diversified Nearest Neighbor Query (Extended Abstract). 2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017). IEEE Computer Society. 2017. DOI: 10.1109/ICDE.2017.22
  14. Sun Y, Yuan NJ, Xie X, McDonald K, Zhang R. Collaborative nowcasting for contextual recommendation. 25th International World Wide Web Conference, WWW 2016. 2016. DOI: 10.1145/2872427.2874812
  15. Sun Y, Yuan NJ, Wang Y, Xie X, McDonald K, Zhang R. Contextual intent tracking for personal assistants. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2016, Vol. 13-17-August-2016. DOI: 10.1145/2939672.2939676

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