Professor Rui Zhang

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

Research interests

  • Artificial Intelligence (AI, Machine Learning, Chatbot, Recommender Systems, Knowledge base)
  • Big Data Analytics
  • Data Mining (Data analytics)
  • Database systems (Database management, Management of Data and Information)

Personal webpage

http://www.ruizhang.info

Biography

Dr Rui Zhang is a Professor and leader of the Big Data and Knowledge Research Theme at the School of Computing and Information Systems of the University of Melbourne. He is an internationally leading researcher in the area of big data, data mining and machine learning. Professor Zhang has won several awards including the prestigious Future Fellowship by the Australian Research Council in 2012, Chris Wallace Award for Outstanding Research by the Computing Research and Education Association of Australasia (CORE) in 2015, and Google Faculty Research Award in 2017. His inventions have been adopted by major IT companies such as AT&T and Microsoft. He proposed a novel technique for computing primitive statistics efficiently on extremely fast TCP/IP packet streams. He developed a temporal index called version compressed TSB-tree, which has been implemented in Microsoft’s flagship database product, Microsoft SQL Server. Dr Rui Zhang obtained his Bachelor's degree from Tsinghua University in 2001, PhD from National University of Singapore in 2006, and has then started as a faculty member in The University of Melbourne since 2007. Before joining the University of Melbourne, he has been a visiting research scientist at AT&T labs-research in New Jersey and at Microsoft Research in Redmond, Washington. Recently, he has been a visiting researcher at Microsoft Research Asia in Beijing regularly collaborating on his ARC Future Fellowship project. Dr Zhang's research interests include big data and AI, particularly in areas of recommendation systems, chatbot, knowledge bases, spatial and temporal data analytics, moving object management and data streams.

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. 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. Li, A.; Qi, J.; Zhang, R.; Kotagiri, R. Boosted GAN with Semantically Interpretable Information for Image Inpainting. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8851926
  3. Huang, X.; Qi, J.; Sun, Y.; Zhang, R.; Zheng, HT. CARL: Aggregated Search with Context-Aware Module Embedding Learning. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8851716
  4. Zhao, Y.; Qi, J.; Zhang, R. CBHE: Corner-based building height estimation for complex street scene images. The World Wide Web Conference on - WWW '19. ACM. 2019, pp. 2436-2447. DOI: 10.1145/3308558.3313394
  5. Wang, Z.; Zhang, R.; Qi, J.; Yuan, B. DBSVEC: Density-based clustering using support vector expansion. 2019 IEEE 35th International Conference on Data Engineering (ICDE). IEEE. 2019, Vol. 2019-April, pp. 280-291. DOI: 10.1109/ICDE.2019.00033
  6. Trisedya, BD.; Qi, J.; Zhang, R. Entity Alignment between Knowledge Graphs Using Attribute Embeddings. THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE. ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE. 2019, Vol. 33, pp. 297-304. DOI: 10.1609/aaai.v33i01.3301297
  7. Jiang, W.; Qi, J.; Yu, JX.; Huang, J.; Zhang, R. HyperX: A Scalable Hypergraph Framework. IEEE Transactions on Knowledge and Data Engineering. IEEE COMPUTER SOC. 2019, Vol. 31, Issue 5, pp. 909-922. DOI: 10.1109/TKDE.2018.2848257
  8. Wang, Y.; Zheng, HT.; Chen, W.; Zhang, R. LambdaGAN: Generative Adversarial Nets for Recommendation Task with Lambda Strategy. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8851869
  9. Su, Y.; Erfani, SM.; Zhang, R. MMF: Attribute Interpretable Collaborative Filtering. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8852452
  10. Li, C.; Gu, Y.; Qi, J.; Zhang, R.; Yu, G. Moving kNN query processing in metric space based on influential sets. Information Systems. PERGAMON-ELSEVIER SCIENCE LTD. 2019, Vol. 83, pp. 126-144. DOI: 10.1016/j.is.2019.03.008
  11. 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
  12. Chen, D.; Zhang, R.; Qi, J.; Yuan, B. Sequence-Aware recommendation with long-Term and short-Term attention memory networks. 2019 20th IEEE International Conference on Mobile Data Management (MDM). IEEE. 2019, Vol. 2019-June, pp. 437-442. DOI: 10.1109/MDM.2019.000-6
  13. Zheng, T.; Zheng, X.; Zhang, Y.; Deng, Y.; Dong, E.; Zhang, R.; Liu, X. SmartVM: a SLA-aware microservice deployment framework. World Wide Web. SPRINGER. 2019, Vol. 22, Issue 1, pp. 275-293. DOI: 10.1007/s11280-018-0562-5
  14. Chen, W.; Zheng, HT.; Wang, Y.; Wang, W.; Zhang, R. Utilizing Generative Adversarial Networks for Recommendation based on Ratings and Reviews. Proceedings of the International Joint Conference on Neural Networks. IEEE. 2019, Vol. 2019-July. DOI: 10.1109/IJCNN.2019.8851822
  15. 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. 2018, Vol. 10939 LNAI, pp. 597-609. DOI: 10.1007/978-3-319-93040-4_47
  16. Wang, S.; Bao, Z.; Huang, S.; Zhang, R. A unified processing paradigm for interactive location-based web search. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining - WSDM '18. Association for Computing Machinery (ACM). 2018, Vol. 2018-Febuary, pp. 601-609. DOI: 10.1145/3159652.3159667
  17. Zhang, Y.; Dai, Y.; Qi, J.; Xu, X.; Zhang, R. Citation field learning by RNN with limited training data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2018, Vol. 11154 LNAI, pp. 219-232. DOI: 10.1007/978-3-030-04503-6_23
  18. Yin, C.; Zhang, R.; Qi, J.; Sun, Y.; Tan, T. Context-Uncertainty-Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 10937, pp. 500-512. DOI: 10.1007/978-3-319-93034-3_40
  19. Qi, J.; Kumar, V.; Zhang, R.; Tanin, E.; Trajcevski, G.; Scheuermann, P. Continuous maintenance of range sum heat maps. 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE. 2018, pp. 1625-1628. DOI: 10.1109/ICDE.2018.00192
  20. Qi, J.; Zhang, R.; Jensen, CS.; Ramamohanarao, K.; He, J. Continuous Spatial Query Processing: A Survey of Safe Region Based Techniques. ACM Computing Surveys. ASSOC COMPUTING MACHINERY. 2018, Vol. 51, Issue 3. DOI: 10.1145/3193835

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