Jianzhong Qi Senior Lecturer School of Computing and Information Systems The University of Melbourne

Contact

General Information

• My research interests include machine learning and data management and analytics, with a focus on spatial, temporal, and textual data.


• February 2018: Visited the School of Computer Science and Engineering, University of New South Wales.
• June 2017 - July 2017: Visited the Department of Electrical Engineering and Computer Science, Northwestern University, as a Visiting Assistant Professor.
• November 2013 - January 2014: Interned at Microsoft Redmond working on SkyDrive (now OneDrive).
• February 2009 - May 2009: Interned at Toshiba China R&D Center working on text to speech (TTS) projects.


• I am recruiting PhD students. To apply, please email me your academic transcripts and CV (including English test results, GPA, and ranking if available).

Selected Papers and Source Code (full paper list)

1. Guanli Liu, Jianzhong Qi, Christian S. Jensen, James Bailey, and Lars Kulik. Efficiently Learning Spatial Indices. ICDE, accepted to appear in 2023. (source code)


2. Yanchuan Chang, Jianzhong Qi, Yuxuan Liang, and Egemen Tanin. Contrastive Trajectory Similarity Learning with Dual-Feature Attention. ICDE, accepted to appear in 2023.


3. Yufan Sheng, Xin Cao, Yixiang Fang, Kaiqi Zhao, Jianzhong Qi, Gao Cong, and Wenjie Zhang. WISK: A Workload-aware Learned Index for Spatial Keyword Queries. SIGMOD, accepted to appear in 2023.


4. Yunxiang Zhao, Jianzhong Qi, Bayu D. Trisedya, Yixin Su, Rui Zhang, and Hongguang Ren. Learning Region Similarities via Graph-based Deep Metric Learning. TKDE, accepted in 2023.


5. Bayu D. Trisedya, Jianzhong Qi, Haitao Zheng, Flora D. Salim, and Rui Zhang. TransCP: A Transformer Pointer Network for Generic Entity Description Generation with Explicit Content-Planning. TKDE, accepted in 2023.


6. Miao Li, Jianzhong Qi, and Jey Han Lau. Compressed Heterogeneous Graph for Abstractive Multi-document Summarization. AAAI, accepted to appear in 2023.


7. Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Haibing Jin, Peizhen Yang, Siqi Shen, and Cheng Wang. FedGS: Federated Graph-based Sampling with Arbitrary Client Availability. AAAI, accepted to appear in 2023.


8. Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, Jianzhong Qi, Chaochao Chen, and Longbiao Chen. INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging. The Web Conference, 673-683, 2023.


9. Jianzhong Qi, Zhuowei Zhao, Egemen Tanin, Tingru Cui, Neema Nassir, and Majid Sarvi. A Graph and Attentive Multi-Path Convolutional Network for Traffic Prediction. TKDE, accepted in 2022. (source code)


10. Rui Zhang, Bayu D. Trisedya, Miao Li, Yong Jiang, and Jianzhong Qi. A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning. VLDB Journal, 31(5): 1143-1168, 2022. (source code)


11. Zhen Song, Yu Gu, Jianzhong Qi, Zhigang Wang, and Ge Yu. EC-Graph: A Distributed Graph Neural Network System with Error-Compensated Compression. ICDE, 648-660, 2022.


12. Yu Gu, Kaiqiang Yu, Zhen Song, Jianzhong Qi, Zhigang Wang, Ge Yu, and Rui Zhang. Distributed Hypergraph Processing Using Intersection Graphs. TKDE, 34(7): 3182-3195, 2022.


13. Bayu D. Trisedya, Jianzhong Qi, Wei Wang, and Rui Zhang. GCP: Graph Encoder with Content-Planning for Sentence Generation from Knowledge Base. TPAMI, 44(11): 7521-7533, 2022.


14. Yunxiang Zhao, Jianzhong Qi, Qingwei Liu, and Rui Zhang. WGCN: Graph Convolutional Networks with Weighted Structural Features. SIGIR, 624-633, 2021. (source code)


15. Zheng Wang, Xiaoliang Fan, Jianzhong Qi, Chenglu Wen, Cheng Wang, and Rongshan Yu. Federated Learning with Fair Averaging. IJCAI, 1615-1623, 2021. (source code)


16. Aili Shen, Meladel Mistica, Bahar Salehi, Hang Li, Timothy Baldwin, and Jianzhong Qi. Evaluating Document Coherence Modelling. TACL, 9: 621-640, 2021.


17. Yimeng Dai, Rui Zhang, and Jianzhong Qi. Automatic Webpage Briefing. ICDE, 1727-1738, 2021.


18. Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. Combating Selection Biases in Recommender Systemswith A Few Unbiased Ratings. WSDM, 427-435, 2021.


19. Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi. Adversarial Distillation for Learning with Privileged Provisions. TPAMI, 43(3): 786-797, 2021.


20. Jianzhong Qi, Guanli Liu, Christian S. Jensen, and Lars Kulik. Effectively Learning Spatial Indices. PVLDB, 13(11): 2341-2354, 2020. (source code)


21. Jianzhong Qi, Yufei Tao, Yanchuan Chang, and Rui Zhang. Packing R-trees with Space-Filling Curves: Theoretical Optimality, Empirical Efficiency, and Bulk-loading Parallelizability. ACM TODS, 14:1-14:47, 2020. (binary package)


22. Jianzhong Qi, Wei Wang, Rui Zhang, and Zhuowei Zhao. A Learning Based Approach to Predict Shortest-Path Distances. EDBT, 367-370, 2020. (source code)


23. Yimeng Dai, Jianzhong Qi, and Rui Zhang. Joint Recognition of Names and Publications in Academic Homepages. WSDM, 133-141, 2020.


24. Xinting Huang, Jianzhong Qi, Yu Sun, and Rui Zhang. Semi-Supervised Dialogue Policy Learning via Stochastic Reward Estimation. ACL, 660-670, 2020.


25. Xinting Huang, Jianzhong Qi, Yu Sun, and Rui Zhang. MALA: Cross-Domain Dialogue Generation with Action Learning. AAAI, 7977-7984, 2020.


26. Bayu D. Trisedya, Jianzhong Qi, and Rui Zhang. Sentence Generation for Entity Description with Content-plan Attention. AAAI, 9057-9064, 2020.


27. Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, and Jianzhong Qi. GMAN: A Graph Multi-Attention Network for Traffic Prediction. AAAI, 1234-1241, 2020. (source code)


28. Hongfei Xu, Yu Gu, Yu Sun, Jianzhong Qi, Ge Yu, and Rui Zhang. Efficient Processing of Moving Collective Spatial Keyword Queries. VLDB Journal, 29(4): 841-865, 2020.


29. Bayu D. Trisedya, Gerhard Weikum, Jianzhong Qi, and Rui Zhang. Neural Relation Extraction for Knowledge Base Enrichment. ACL, 229-240, 2019. (source code)


30. Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, and Kotagiri Ramamohanarao. Generative Image Inpainting with Submanifold Alignment. IJCAI, 811-817, 2019.


31. Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random. ICML, 6638-6647, 2019.


32. Yunxiang Zhao, Jianzhong Qi, and Rui Zhang. CBHE: Corner-based Building Height Estimation for Complex Street Scene Images. WWW, 2436-2447, 2019.


33. Jiayuan He, Jianzhong Qi, and Kotagiri Ramamohanarao. A Joint Context-Aware Embedding for Trip Recommendations. ICDE, 292-303, 2019.


34. Zhen Wang, Rui Zhang, Jianzhong Qi, and Bo Yuan. DBSVEC: Density-Based Clustering Using Support Vector Expansion. ICDE, 280-291, 2019.


35. Bayu D. Trisedya, Jianzhong Qi, and Rui Zhang. Entity Alignment between Knowledge Graphs Using Attribute Embeddings. AAAI, 297-304, 2019. (source code)


36. Wenkai Jiang, Jianzhong Qi, Jeffrey Xu Yu, Jin Huang, and Rui Zhang. HyperX: A Scalable Hypergraph Framework. TKDE, 31(5): 909-922, 2019. (source code)


37. Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. KDGAN: Knowledge Distillation with Generative Adversarial Networks. NeurIPS, 775-786, 2018.


38. Bayu D. Trisedya, Jianzhong Qi, Rui Zhang, and Wei Wang. GTR-LSTM: A Triple Encoder for Sentence Generation from RDF Data. ACL, 1627-1637, 2018. (source code)


39. Jianzhong Qi, Fei Zuo, Hanan Samet, Jia Cheng Yao. K-Regret Queries Using Multiplicative Utility Functions. ACM TODS, 43(2): 10:1-10:41, 2018.


40. Jianzhong Qi, Rui Zhang, Christian S. Jensen, Kotagiri Ramamohanarao, and Jiayuan He. Continuous Spatial Query Processing: A Survey of Safe Region Based Techniques. ACM Computing Surveys, 51(3): 64:1-64:39, 2018.


41. Jianzhong Qi, Yufei Tao, Yanchuan Chang, and Rui Zhang. Theoretically Optimal and Empirically Efficient R-trees with Strong Parallelizability. PVLDB, 11(5): 621-634, 2018. (binary package)


42. Jianzhong Qi, Vivek Kumar, Rui Zhang, Egemen Tanin, Goce Trajcevski, and Peter Scheuermann. Continuous Maintenance of Range Sum Heat Maps. ICDE, 1625-1628, 2018. (source code)


43. Saad Aljubayrin, Jianzhong Qi, Christian S. Jensen, Rui Zhang, Zhen He, and Yuan Li. Finding Lowest-Cost Paths in Settings with Safe and Preferred Zones. VLDB Journal, 26(3): 373-397, 2017.


44. 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, 2015.


45. Jianzhong Qi, Rui Zhang, Kotagiri Ramamohanarao, Hongzhi Wang, Zeyi Wen, and Dan Wu. Indexable Online Time Series Segmentation with Error Bound Guarantee. World Wide Web, 18(2): 359-401, 2015.


46. Jianzhong Qi, Rui Zhang, Yanqiu Wang, Andy Yuan Xue, Ge Yu, and Lars Kulik. The Min-dist Location Selection and Facility Replacement Queries. World Wide Web, 17(6): 1261-1293, 2014. (source code)


47. Chuanwen Li, Yu Gu, Jianzhong Qi, Ge Yu, Rui Zhang, and Wang Yi. Processing Moving kNN Queries Using Influential Neighbor Sets. PVLDB, 8(2): 113-124, 2014. (source code)


48. 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.


49. Rui Zhang, Jianzhong Qi, Martin Stradling, and Jin Huang. Towards a Painless Index for Spatial Objects. ACM TODS, 39(3): 19:1-19:42, 2014.


50. Rui Zhang, Jianzhong Qi, Dan Lin, Wei Wang, and Raymond Chi-Wing Wong. A Highly Optimized Algorithm for Continuous Intersection Join Queries over Moving Objects. VLDB Journal, 21(4): 561-586, 2012. (source code)


51. Jianzhong Qi, Rui Zhang, Lars Kulik, Dan Lin, and Yuan Xue. The Min-dist Location Selection Query. ICDE, 366-377, 2012. (Slides) (source code)


52. Jianzhong Qi, Zhenghua Xu, Yuan Xue, and Zeyi Wen. A Branch and Bound Method for Min-dist Location Selection Queries. Australasian Database Conference (ADC), 51-60, 2012 (Runner-up for Best Paper). (source code)

Professional Services

• Publicity Chair: SIGSPATIAL 2022 and 2023.
• WSDM Cup Chair: 2019.
• PC Chair: ADC 2020.
• Proceedings Chair: ADC 2015, ADC 2018.
• Session Chair: ICDE 2023, KDD 2021.
• PC member:
  • 2023: SIGMOD, SIGIR, WSDM, ICML, NeurIPS, ICLR, IJCAI, KDD
  • 2022: SIGIR, WSDM, ICML, NeurIPS, ICLR, AAAI, ACL, EMNLP, KDD, ICDM, CIKM, SIGSPATIAL, SDM, PAKDD
  • 2021: SIGIR, WSDM, ICML, NeurIPS, ICLR, EMNLP, KDD, ICDM, CIKM, JCDL, SIGSPATIAL, PAKDD
  • 2020: SIGIR, ICML, NeurIPS, IJCAI, CIKM, JCDL, SIGSPATIAL, PAKDD
  • 2019: NeurIPS, ICDE, SIGSPATIAL
  • 2018: CIKM, SIGSPATIAL
  • 2017: ICDE, CIKM, SIGSPATIAL
  • Journal reviewer:
    • ACM Computing Surveys
    • ACM Transactions on Database Systems
    • ACM Transactions on Privacy and Security
    • ACM Transactions on Spatial Algorithms and Systems
    • ACM Transactions on Internet Technology
    • ACM Transactions on Intelligent Systems and Technology.
    • GeoInformatica
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • IEEE Transactions on Image Processing
    • IEEE Transactions on Knowledge and Data Engineering
    • IEEE Transactions on Neural Networks and Learning Systems
    • IEEE Transactions on Mobile Computing
    • Information Systems
    • Journal of Machine Learning Research
    • Journal of Parallel and Distributed Computing
    • Parallel Computing
    • The VLDB Journal

  Grants and Awards

  • 2023 - 2025, ARC Discovery Project x 1, Australian Research Council.
  • 2020, MSE Platform Interdisciplinary Grant, Melbourne School of Engineering.
  • 2019, ByteDance Research Gift Grant, ByteDance Inc.
  • 2018 - 2021, ARC Discovery Project x 2, Australian Research Council.
  • 2017, Eshbach Visiting Scholar Fellowship, Northwestern University.
  • 2016, Early Career Researcher (ECR) Grant, University of Melbourne.
  • 2015, Early Career Researcher (ECR) Grant, Melbourne School of Engineering.
  
  
  • 2022, Excellence in Research, School of Computing and Information Systems.
  • 2021, Best Paper Runner-Up, SSDBM.
  • 2021, Best Paper, ALTA.
  • 2017, Best Vision Paper, SIGSPATIAL.
  • 2015, Nominee, MERIT Prize for the Best PhD Thesis in Engineering, Melbourne School of Engineering.
  • 2015, Nominee, John Makepeace Bennett Best PhD Thesis Award, Computing Research and Education Association of Australasia (CORE).
  • 2015, Best Poster, ADC.
  • 2012, Runner-up for Best Paper, ADC.

  Teaching

  • Semester 1, 2016 - 2023, Foundations of Algorithms (COMP10002).
  • Semester 2, 2022 - 2023, Intro. to Numerical Computation in C (COMP20005).
  • Semester 2, 2015 - 2021, Engineering Computation (COMP20005).
  • Semester 1, 2015, Advanced Database Systems (COMP90050).
  • Semester 1, 2014 - 2016, Programming and Software Development (COMP90041).

  Graduated Research Students

  • Nestor Cabello (PhD, co-supervised with Prof. Lars Kulik), 2023
  • Xinting Huang (PhD, co-supervised with Dr. Bayu D. Trisedya), 2022
  • Yunxiang Zhao (PhD, co-supervised with Dr. Bayu D. Trisedya), 2022
  • Yixin Xu (PhD, co-supervised with Prof. Lars Kulik), 2021
  • Aili Shen (PhD, co-supervised with Prof. Timothy Baldwin), 2021
  • Yimeng Dai (PhD, co-supervised with Prof. Rui Zhang), 2021
  • Bayu D. Trisedya (PhD, co-supervised with Prof. Rui Zhang), 2021
  • Xiaojie Wang (PhD, co-supervised with Prof. Rui Zhang), 2021
  • Minh Tuan Doan (PhD, co-supervised with Prof. Christopher Leckie), 2020
  • Zhuowei Zhao (MPhil), 2020
  • Jiayuan He (PhD), 2020
  • Wenkai Jiang (MPhil), 2019
  • Yiqing Zhang (MPhil), 2019
  • Chenxu Zhao (MPhil), 2019
  • Chuandong Yin (MPhil), 2018
  • Yu Sun (PhD, co-supervised with Prof. Rui Zhang), 2017
  • Gitansh Khirbat (MPhil), 2017
  • Han Li (MPhil), 2016
  • Jin Huang (PhD, co-supervised with Prof. Rui Zhang), 2016
  • Andy Yuan Xue (PhD, co-supervised with Prof. Rui Zhang), 2016

  Miscellaneous

  

  Visitor IP count:

  ---

  Created by Jianzhong Qi.
  Last modified: 28/05/2023.
  
  Mandatory disclaimer: This page, its content and style, are the responsibility of the author and do not necessarily represent the views, policies, or opinions of The University of Melbourne.