This page has been moved to www.ruizhang.info
Rui  Zhang   (Rui is pronounced as Ray)

Professor, School of Computing and Information Systems, The University of Melbourne

Leader of Big Data and Knowledge Research Theme

Future Fellow, Australian Research Council (2012-2016)

Office:        Level 7, Room 7.05, Doug McDonell Building
                   Map of office location in the Doug McDonell Building.
Email:        (my first name) (dot) zhang@unimelb.edu.au
Phone:        +61 3 83441345
Mailing Address:  Dept of Computing & Information Systems
                   Level 8, Doug McDonell Building (Building 168)
                   University of Melbourne, Parkville, Victoria, Australia 3052

LinkedIn: Click here 
 

If you want to be my PhD student, intern, or do a Master project with me (UoM coursework-Master students only), please read carefully the message at the bottom of this page before you email me.

 


General Information

Dr Rui Zhang is a Professor and leader of the Big Data and Knowledge Research Theme at the Department 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 and PhD from National University of Singapore in 2006. 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, data mining and databases, particularly in areas of spatial and temporal data analytics, recommender systems, moving object management and data streams.

 

Research Fellow (Postdoc) Position Available: Research Fellow (up to AU$102,743 per annum package including superannuation)


Research   

Selected publications         Full list         Most Significant Publications

          Recommendation and Chatbot

  1. Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi. KDGAN: Knowledge Distillation with Generative Adversarial Networks, 32nd Conference on Neural Information Processing Systems (NIPS) 2018.
     
  2. Xiaojie Wang, Jianzhong Qi, Ramamohanarao Kotagiri, Yu Sun, Bo Li, and Rui Zhang. Joint Optimization Approach for Personalized Recommendation Diversification. 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD) 2018.
     
  3. Chuandong Yin, Rui Zhang, Jianzhong Qi, Yu Sun, and Tenglun Tan. Context-Uncertainty-Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning. 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD) 2018.
     
  4. Yu Sun, Nicholas Jing Yuan, Xing Xie, Kieran McDonald, Rui Zhang. Collaborative Intent Prediction with Real-Time Contextual Data, ACM Transactions on Information Systems (TOIS), 35 (4), 30, 2017.
     
  5.   Yu Sun, Nicholas Jing Yuan, Yingzi Wang, Xing Xie, Kieran McDonald, Rui Zhang. Contextual Intent Tracking for Personal Assistants, 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2016.  Best Student Paper Award for the Applied Data Science track.   Video   Slides
     
  6. Yu Sun, Nicholas Jing Yuan, Xing Xie, Kieran McDonald, Rui Zhang. Collaborative Nowcasting for Contextual Recommendation, WWW conference 2016.

    Activity Recognition
     
  7. Weihao Cheng, Sarah Erfani, Rui Zhang, Kotagiri Ramamohanarao. Predicting Complex Activities from Ongoing Multivariate Time Series. International Joint Conference on Artificial Intelligence (IJCAI), 2018.
     
  8. Weihao Cheng, Sarah M. Erfani, Rui Zhang, Kotagiri Ramamohanarao, Learning Datum-Wise Sampling Frequency for Energy-Efficient Human Activity Recognition, Proceedings of the 32th AAAI Conference on Artificial Intelligence (AAAI 2018).
     
  9. Weihao Cheng, Sarah M. Erfani, Rui Zhang, Kotagiri Ramamohanarao: Accurate Recognition of the Current Activity in the Presence of Multiple Activities. 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD) 2017: 39-50

    Spatial and MOOC Data Mining
     
  10. Bayu Distiawan Trisedya, Jianzhong Qi, Rui Zhang, Wei Wang. GTR-LSTM: A Triple Encoder for Sentence Generation from RDF Data56th Annual Meeting of the Association for Computational Linguistics (ACL) 2018.
     
  11. Sheng Wang, Zhifeng Bao, Shixun Huang, Rui Zhang, A Unified Processing Paradigm for Interactive Location-based Web Search, The 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
     
  12. Xiaojie Wang, Ji-Rong Wen, Zhicheng Dou, Tetsuya Sakai, Rui Zhang, Search Result Diversity Evaluation based on Intent Hierarchies, IEEE Transactions on Knowledge and Data Engineering (TKDE), 30 (1): 156-169, 2018.
     
  13. Zeyi Wen, Rui Zhang, Kotagiri Ramamohanarao, Li Yang, Scalable and fast SVM regression using modern hardware, World Wide Web Journal (WWWJ), accepted in April 2017.
     
  14. Zeyi Wen, Bin Li, Rao Kotagiri, Jian Chen, Yawen Chen, Rui Zhang. Improving Efficiency of SVM k-fold Cross-validation by Alpha Seeding. Proceedings of the 31th AAAI Conference on Artificial Intelligence (AAAI'2017).
     
  15. Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, and Jeffrey Chan. MOOCs Meet Measurement Theory: A Topic-Modelling Approach. Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'2016).
     
  16. Jiazhen He, James Bailey, Benjamin Rubinstein, Rui Zhang, Identifying At-Risk Students in Massive Open Online Courses, Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015.
     
  17. Zeyi Wen, Rui Zhang, Kotagiri Ramamohanarao, Jianzhong Qi and Kerry Taylor. MASCOT: Fast and Highly Scalable SVM Cross-validation using GPUs and SSDs. The IEEE International Conference on Data Mining (ICDM), 2014.

    Databases and Others
     
  18. Wenkai Jiang, Jianzhong Qi, Jeffrey Xu Yu, Jin Huang, Rui Zhang. HyperX: A Scalable Hypergraph Framework. IEEE Transactions on Knowledge and Data Engineering (TKDE), Accepted in June 2018.
     
  19. Tanzima Hashem, Lars Kulik, Kotagiri Ramamohanarao, Rui Zhang, Subarna Chowdhury Soma, Protecting Privacy for Distance and Rank Based Group Nearest Neighbor Queries, World Wide Web Journal (WWWJ), accepted in April 2018.
     
  20. Xi Zheng, Yuqun Zhang, Tianlei Zheng, Yao Deng, ErXi Dong, Rui Zhang, Xiao Liu, SmartVM: a SLA-aware microservice deployment framework,  World Wide Web Journal (WWWJ), accepted in April 2018.
     
  21. Jianzhong Qi, Yufei Tao, Yanchuan Chang, Rui Zhang, Theoretically Optimal and Empirically Efficient Rtrees with Strong Parallelizability, Proceedings of the VLDB Endowment (PVLDB), 11(5), 2018.
     
  22. Jianzhong Qi, Vivek Kumar, Rui Zhang, Egemen Tanin, Goce Trajcevski, and Peter Scheuermann. Continuous Maintenance of Range Sum Heat Maps. Proceedings of the 33th IEEE International Conference on Data Engineering (ICDE) 2018. (demo).
     
  23. Saad Aljubayrin, Jianzhong Qi, Christian S. Jensen, Rui Zhang, Zhen He, Yuan Li. Finding Lowest-Cost Paths in Settings with Safe and Preferred Zones. VLDB Journal, 26(3): 373-397, 2017.
     
  24. Yu Gu, Guanli Liu, Jianzhong Qi, Hongfei Xu, Ge Yu, and Rui Zhang. The Moving K Diversified Nearest Neighbor Query. IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(10): 2778-2792, 2016.
     
  25. Yu Sun, Rui Zhang, Andy Yuan Xue, Jianzhong Qi, Xiaoyong Du. Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration, Proceedings of the 31th IEEE International Conference on Data Engineering (ICDE) 2016.  see RNN heat maps for cities around the world.
     
  26. Chuanwen Li, Yu Gu, Jianzhong Qi, Ge Yu, Rui Zhang, and Qingxu Deng. INSQ: An Influential Neighbor Set Based Moving kNN Query Processing System. Proceedings of the 31th IEEE International Conference on Data Engineering (ICDE) 2016. (demo).
     
  27. Jin Huang, Rui Zhang, Rajkumar Buyya, Jian Chen, Yongwei Wu, HEADS-JOIN: Efficient Earth Mover¨s Distance Similarity Joins on Hadoop, IEEE Transactions on Parallel and Distributed Systems (TPDS), 27(6): 1660-1673, 2016.
     
  28. Jin Huang, Rui Zhang, and Jeffrey Xu Yu. Scalable Hypergraph Processing, The IEEE International Conference on Data Mining (ICDM), 2015. (Short)
     
  29. Weichao Guo, Kang Chen, Huan Feng, Yongwei Wu, Rui Zhang, Weimin Zheng. MARS: Mobile Application Relaunching Speed-up through Flash-Aware Page Swapping, IEEE Transactions on Computers, 65(3): 916-928, 2016.
     
  30. Thi Nguyena, Zhen He, Rui Zhang, Philip G. D. Ward, Exploiting velocity distribution skew to speed up moving object indexing, Information Systems, 51(c):72-104, 2015.
     
  31. Yu Sun, Jianzhong Qi, Yu Zheng, Rui Zhang, K-Nearest Neighbor Temporal Aggregate Queries, EDBT 2015.
     
  32. Saad Aljubayrin, Jianzhong Qi, Christian Jensen, Rui Zhang, Zhen He, Zeyi Wen. The Safest Path via Safe Zones. Proceedings of the 31th IEEE International Conference on Data Engineering (ICDE) 2015.
     
  33. Chuanwen Li, Yu Gu, Jianzhong Qi, Ge Yu, Rui Zhang, and Yi Wang. Processing Moving kNN Queries Using Influential Neighbor Sets. Proceedings of the VLDB Endowment (PVLDB), vol.8 (2): 113 - 124, 2014. Source code.
     
  34. Andy Yuan Xue, Jianzhong Qi, Xing Xie, Rui Zhang, Jin Huang, and Yuan Li. Solving the Data Sparsity Problem in Destination Prediction. VLDB Journal, 24 (2): 219-243, 2014.
     
  35. Phillip G. D. Ward, Zhen He, Rui Zhang and Jianzhong Qi. Real-time Continuous Intersection Joins over Large Sets of Moving Objects using Graphic Processing Units. VLDB Journal, 23(6): 965-985, 2014.
     
  36. Yanqiu Wang, Rui Zhang, Chuanfei Xu, Jianzhong Qi, Yu Gu and Ge Yu. Continuous Visible k Nearest Neighbor Query on Moving Objects. Information Systems, 44: 1-21, 2014.
     
  37. Rui Zhang, Jianzhong Qi, Martin Stradling and Jin Huang. Towards a Painless Index for Spatial Objects. ACM Transactions on Data Base Systems (TODS), 39 (3), 19, 2014. source code
     
  38. Dongsheng Duan, Yuhua Li , Ruixuan Li, Rui Zhang, Xiwu Gu, Kunmei Wen. LIMTopic: A Framework of Incorporating Link based Importance into Topic Modeling. IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(10): 2493-2506. 2014.
     
  39. Jin Huang, Rui Zhang, Rajkumar Buyya, and Jian Chen. MELODY-Join: Efficient Earth Mover's Distance Similarity Join Using MapReduce. Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE) 2014. Slides, Source code and Datasets.
     
  40. Jianzhong Qi, Rui Zhang, Kotagiri Ramamohanarao, Hongzhi Wang, Zeyi Wen and Dan Wu. Indexable Online Time Series Segmentation with Error Bound Guarantee. WWW Journal,  accepted in September 2013.
     
  41. Jianzhong Qi, Rui Zhang, Yanqiu Wang, Andy Yuan Xue, Ge Yu, Lars Kulik. The Min-dist Location Selection and Facility Replacement Queries. WWW Journal, 17(6): 1261-1293, 2014.
     
  42. Andy Yuan Xue, Rui Zhang, Yu Zheng, Xing Xie, Jianhui Yu, Yong Tang. DesTeller: A System for Destination Prediction Based on Trajectories with Privacy Protection. (Demo) Proceedings of the VLDB Endowment (PVLDB) vol.6(12):1198-1201, 2013. Play the Demo
     
  43. Andy Yuan Xue, Rui Zhang, Yu Zheng, Xing Xie, Jin Huang, Zhenghua Xu. Destination Prediction by Sub-Trajectory Synthesis and Privacy Protection Against Such Prediction. IEEE International Conference on Data Engineering (ICDE) 2013.  Slides
     
  44. Tanzima Hashem, Lars Kulik, Rui Zhang. Countering Overlapping Rectangle Privacy Attack for Moving kNN Queries. Information Systems. 38(3): 430-453, 2013.
     
  45. Dongsheng Duan, Yuhua Li, Ruixuan Li, Rui Zhang, Aiming Wen. RankTopic: Ranking Based Topic Modeling. IEEE International Conference on Data Mining (ICDM) 2012.
     
  46. Thi Nguyen, Zhen He, Rui Zhang, Phillip Ward. Boosting Moving Object Indexing through Velocity Partitioning. Proceedings of the VLDB Endowment (PVLDB) 2012, vol.5(9):860-871 / (VLDB) 2012.
     
  47. Zhenghua Xu, Rui Zhang, Ramamohanarao Kotagiri, Udaya Parampalli. An Adaptive Algorithm for Online Time Series Segmentation with Error Bound Guarantee. 15th International Conference on Extending Database Technology (EDBT) 2012.
     
  48. Jianzhong Qi, Rui Zhang, Lars Kulik, Dan Lin, Yuan Xue. The Min-dist Location Selection Query. IEEE International Conference on Data Engineering (ICDE) 2012.
     
  49. Rui Zhang, Jianzhong Qi, Dan Lin, Wei Wang, Raymond Chi-Wing Wong. A Highly Optimized Algorithm for Continuous Intersection Join Queries over Moving Objects, VLDB Journal, 21(4): 561-586, 2012.
     
  50. Dan Lin, Christian Jensen, Rui Zhang, Lu Xiao, Jiaheng Lu. A Moving Object Index for Efficient Query Processing with Peer-Wise Location Privacy, Proceedings of the VLDB Endowment (PVLDB) 2011, vol.5 / (VLDB) 2012. slides
     
  51. Sarana Nutanong, Egemen Tanin, Jie Shao, Rui Zhang, and Kotagiri Ramamohanarao, Continuous Detour Queries in Spatial Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 24(7): 1201-1215, 2012.
     
  52. Alex Hindle, Jie Shao, Dan Lin, Jiaheng Lu, Rui Zhang. Clustering Web Video Search Results based on Integration of Multiple Features. World Wide Web Journal (WWWJ), 14(1): 53-73, 2011.
     
  53. Rui Zhang, Martin Stradling. The HV-tree: a Memory Hierarchy Aware Version Index. Proceedings of the VLDB Endowment (PVLDB), 3(1): 397-408, 2010. slides
     
  54. Rui Zhang, H. V. Jagadish, Bing Tian Dai, Kotagiri Ramamohanarao. Optimized Algorithms for Predictive Range and KNN Queries on Moving Objects. Information Systems, 35(8): 911-932, 2010.
     
  55. Mohammed Eunus Ali, Egemen Tanin, Rui Zhang, Lars Kulik. A Motion-Aware Approach for Efficient Evaluation of Continuous Queries on 3D Object Databases, VLDB Journal, 19(5): 603-632, 2010.
     
  56. Rui Zhang, Nick Koudas, Beng Chin Ooi, Divesh Srivastava, Pu Zhou. Streaming Multiple Aggregations Using Phantoms, VLDB Journal, 19(4): 557-583, 2010.
     
  57. Tanzima Hashem, Lars Kulik, Rui Zhang. Privacy Preserving Group Nearest Neighbor Queries, EDBT 2010.
     
  58. Xiaoyan Liu, Xindong Wu, Huaiqing Wang, Rui Zhang, James Bailey, Kotagiri Ramamohanarao . Mining Distribution Change in Stock Order Streams, ICDE 2010 (short paper).
     
  59. Sarana Nutanong, Rui Zhang, Egemen Tanin, Lars Kulik. Analysis and Evaluation of V*-kNN: An Efficient Algorithm for Moving kNN Queries, VLDB Journal, 19(3): 307-332, 2010. Slides
     
  60. Sarana Nutanong, Egemen Tanin, Rui Zhang. Incremental Evaluation of Visible Nearest Neighbor Queries. IEEE Transactions on Knowledge & Data Engineering (TKDE), 22(5): 665-681, 2010.
     
  61. Sarana Nutanong, Rui Zhang, Egemen Tanin, Lars Kulik. V*-kNN: an Efficient Algorithm for Moving k Nearest Neighbor Queries. International Conference on Data Engineering (ICDE), Shanghai, China, 2009. Play the Demo
     
  62. Sarana Nutanong, Rui Zhang, Egemen Tanin, Lars Kulik. The V*-Diagram: A Query Dependent Approach to Moving KNN Queries. Proceedings of the VLDB Endowment (VLDB), 1, 1095-1106, 2008. Slides   Source code.
     
  63. David Lomet, Mingsheng Hong, Rimma Nehme, Rui Zhang. Transaction Time Indexing with Version Compression. Proceedings of the VLDB Endowment (VLDB), 1, 870-881, 2008.
     
  64. Rui Zhang, Dan Lin, Kotagiri Ramamohanarao, Elisa Bertino. Continuous Intersection Joins Over Moving Objects. International Conference on Data Engineering (ICDE), Cancun, Mexico, 2008. Slides
     
  65. Mohammed Eunus Ali, Rui Zhang, Egemen Tanin, Lars Kulik. A Motion-Aware Approach to Continuous Retrieval of 3D Objects. International Conference on Data Engineering (ICDE), Cancun, Mexico, 2008. Slides
     
  66. Anthony Tung, Rui Zhang, Nick Koudas, Beng Chin Ooi. Similarity Search: A Matching Based Approach. International Conference on Very Large Data Bases (VLDB), Seoul, 2006. Slides
     
  67. Christian S. Jensen, Dan Lin, Beng Chin Ooi, Rui Zhang. Effective Density Queries of Continuously Moving Objects. International Conference on Data Engineering (ICDE), Atlanta, 2006.
     
  68. Rui Zhang, Nick Koudas, Beng Chin Ooi, Divesh Srivastava. Multiple Aggregations Over Data Streams. ACM SIGMOD International Conference on Management of Data (SIGMOD), Baltimore, 2005. Slides
     
  69. Rui Zhang, Panos Kalnis, Beng Chin Ooi, Kian-Lee Tan. Generalized Multi-dimensional Data Mapping and Query Processing. ACM Transactions on Data Base Systems (TODS), 30(3): 661-697, 2005.
     
  70. H.V. Jagadish, Beng Chin Ooi, Kian-Lee Tan, Cui Yu, Rui Zhang. iDistance: An Adaptive B+-tree Based Indexing Method for Nearest Neighbor Search. ACM Transactions on Data Base Systems (TODS), 30(2), 364-397, 2005.
     
  71. Nick Koudas, Beng Chin Ooi, Kian-Lee Tan, Rui Zhang. Approximate NN queries on Streams with Guaranteed Error/performance Bounds. International Conference on Very Large Data Bases (VLDB), Toronto, 2004. Slides
     
  72. Rui Zhang, Beng Chin Ooi, Kian-Lee Tan. Making the Pyramid Technique Robust to Query Types and Workload. International Conference on Data Engineering (ICDE), Boston, 2004. Slides
 
Selected Professional Activities        Full list
  • 2019: PC member of ICDE
  • 2018: PC member of ICDE, General Chair of ADC, CIKM Senior PC
  • 2017: CIKM Senior PC
  • 2016: Associate Editor of Distributed and Parallel Databases, PC member of MDM, IEEE BigDataSE
  • 2015: CIKM Local Co-Chair, PC member of SIGMOD, General Chair of ADC 2015 (co-located with SIGMOD).
  • 2014: ICDE Industry Track PC member, SIGMOD Exhibits Co-Chair.
  • 2013: Program Committee Co-Chair for Australasian Database Conference 2013; Demo Co-Chair of ICDE; PC member of SIGMOD, ICDE; Publication Co-Chair of ApWeb; WISE Demo Chair.
  • 2012: Program Committee Co-Chair for Australasian Database Conference 2012, PC member of ICDE, VLDB, Vice Chair of ACM SIGSPATIAL Australia Chapter.
  • 2011: PC member of ICDE, DASFAA
  • 2010: Review board of Proceedings of the VLDB Endowment; PC member of KDD, CIKM, DASFAA
  • 2009: Review board of Proceedings of the VLDB Endowment; PC member of ICDE, DASFAA
  • 2008: Review board of Proceedings of the VLDB Endowment; DASFAA
  • 2007: PC member of SIGMOD, DASFAA
  • Reviewer for VLDB Journal, ACM Trans. on Database Systems, IEEE Trans. on Knowledge and Data Engineering, IEEE Trans. on Computers, Information Systems
 
Research Interests and Projects
 
  • Big Data analytics
  • Artificial Intelligence (AI), Machine Learning
  • Spatial and temporal data management, including high-dimensional data and moving object management
    
 
Research Grants
  • 2013 - 2015 ARC Discovery $275,000
  • 2013 - 2015 ARC Discovery $452,000
  • 2013 - 2016 ARC Future Fellow $564,747 + $200,000
  • 2008 - 2011 ARC Discovery $590,000
  • 2008 - 2010 ARC Discovery $234,000
  • 2008, Melbourne Early Career Researcher (ECR) Grant. $10,000
  • 2007, Melbourne Early Career Researcher (ECR) Grant. $50,000
 
Released Code and Datasets
  • iDistance: State-of-the-Art for k Nearest Neighbor queries in metric spaces   [Wikipedia Entry of iDistance]
  • GiMP: A framework for Mapping-based multi-dimensional indexing
  • P+-tree: State-of-the-Art for high-dimensional window queries
  • V*-Diagram and INS: State-of-the-Art for moving k nearest neighbor queries.
  • HomePub: Publication Strings from Academic Homepages
 
Patent
  • US patent: with Divesh Srivastava and Nick Koudas. System and method for managing data streams, US patent number 7,631,074,  Issuing date: Dec 8, 2009
 

Research Students

Name Program Topic Time Main Outcomes Employment Intern
Xinting Huang Postgrad 2018-
Yunxiang Zhao Postgrad 2017-
Ang Li PhD 2017-
Bayu Distiawan Trisedya PhD 2017- ACL, AAAI
Yimeng Dai PhD 2017-
Xiaojie Wang PhD 2016- TKDE, PAKDD, NIPS
Chenxu Zhao Master 2016- WISE
Chuandong Yin Master 2016- PAKDD, EMNLP
Wenkai Jiang Master 2015- TKDE
Yiqing Zhang Master 2015- EMNLP
Weihao Cheng PhD Human Activity Recognition 2015-2018 PAKDD, AAAI, IJCAI Microsoft Microsoft
Yu Sun PhD Location Based Social Network 2013-2017 ICDE, WWW, KDD, UbiComp, TOIS Twitter (US) Microsoft
Google(US)
Jiazhen He PhD Mining MOOC Data 2013-2016 AAAIx2 U. of Melbourne
Saad Aljubayrin PhD Safest Route Problem 2012-2016 ICDE, VLDBJ Shaqra University Aalborg U.
Yuan Xue PhD GPS Trajectory Mining 2012-2015 ICDEx2, WWWJ, VLDBJ startup
Jin Huang PhD Advanced Similarity Analysis on Big Data 2012-2015 ICDEx2, TODS, VLDBJ, TPDS, ICDM Google (US)
Zeyi Wen PhD Improving Data Mining by GPU 2011-2015 CIKM, ICDM, ICDE National U. of Singapore Baidu
Jianzhong Qi PhD Correlating large datasets 2010-2014 VLDBJ, ICDE, WWWJx2, TODS, IS, PVLDB, ICDM U. of Melbourne Microsoft
Dana Zhang PhD Role based Access Control 2006-2010 SACMAT, ACSAC Google (US) Google
Mohammed Eunus Ali PhD 3D objects retrieval 2006-2010 ICDE,VLDBJ BUET
Sarana Nutanong PhD V*-diagram 2006-2009 VLDB, TKDE, VLDBJ U. of Maryland  
Han Li Master 2014-2017
Gitansh Khirbat Master 2014-2017
Xiaojie Lin Master Linking Twits with News 2014-2016
Zhenghua Xu Master Approximating Time Series Data 2011-2012 EDBT Oxford U. (PhD)
Martin Stradling Master Spatio-temporal indexing 2008-2012 Pro. Patent, VLDB
Mei Ma Master Sequence indexing 2007-2010 WestPac
Pu Zhou Master Data streams 2007-2009 VLDBJ
Elizabeth Antoine Master Spatial join 2007-2009 ADC
Katsuya Noguchi Honors Detour Query 2009   Oxford U.(postgrad)  
Alex Hindle Honors Video clustering 2009 WWWJ IBM (Australia)  

 

If you want to be my PhD student:

 

I have a number of PhD positions. Applicants are preferred who have outstanding record which may be evidenced by one or more of the following achievements:

       (i) Top 3% in your department/major from a well-known university, or

       (ii) Top 30% in your department/major from a world or region leading university (e.g., Tsinghua and Peking University if from China), or

       (iii) Awards or prize in major competitions such as Mathematics competition and  ACM-ICPC with near one of the above, or

       (iv) Strong industrial or system software development experience together with near one of the above.

 

Please send me an email with the following items:

       (i) The email briefly explains your most impressive achievements (e.g., one or more of the above mentioned).

       (ii) Attach CV including English test result (IELTS or TOEFL), your GPA and department ranking if possible.

       (iii) Attach detailed undergraduate transcript; if you are a postgraduate student, also attach detailed postgraduate transcript.

 

Please keep your email short so that your most impressive achievements stand out and I won't miss them. Due to the limitation on the number of students I can supervise and the high competition, I may only respond to some of the requests. If you are self-funded, please state it in the title of the email.

 

If you want to be an intern/visiting student in my group:

 

You need to be self-funded and have a strong record like the above described for PhD student. We have very limited space in the department, so intern/visiting student opportunities are very limited.

 

If you want to do a Master Project with me (this is for UoM Course-work Master students only):

 

Please email me:

(i) a CV (includes your education, GPA, research or work experience, etc)

(ii) undergrad transcript, and

(iii) the scores of the subject you have done in UoM.

 


Teaching    

See a list of all the subjects I teach.