Research Interests

Miao Qiao joined the School of Computer Science, the University of Auckland, in 2018. Her research focuses on the theory and practices of databases with the past and current research topics on indexing, query optimization, big data management and graph analytics.

• Indexing and query optimization. Her past and ongoing research span over topics including graph distance queries, approximate nearest neighbor search in high dimensional space, range thresholding queries on data streams, multi-way join queries in relational databases, local dense subgraph search.
• Efficient processing and analysis of big data, in particular graph data. Her past and ongoing research have explored the computation of different graph metrics, densest subgraph search, community detection, hypergraph clustering, I/O-efficient algorithm design and streaming algorithms.
• Brain network analysis. This is a long-term and interdisciplinary (with medical and health science) research aiming at understanding and explaining the functions of the human brain, and bettering the predictions of the malfunctioning of the human brain with graph analytical techniques.

Supervisions

• Current PhD students:
  John Yang
  Yizhou Dai
  Callum Cory (co-supervise with Yun Sing Koh, Yiping Ke, and Diana Benavides Prado)
• Graduated PhD students:
  Wentao Li (2017-2020): Wentao is currently a Postdoc Researcher at The Hong Kong University of Science and Technology (Guangzhou) and was a Postdoc Researcher at UTS, Sydney.
  Zijin Feng (2019-2024): Zijin is currently a researcher at Huawei, Hong Kong.

Selected Publications (full list DBLP)

• Zijin Feng, Miao Qiao , Chengzhi Piao, Hong Cheng.
  On Graph Representation for Attributed Hypergraph Clustering
  To appear in SIGMOD, 2025.
  
  
• Jiaxing Xu, Kai He, Mengcheng Lan, Qingtian Bian, Wei Li, Tieying Li, Yiping Ke, and Miao Qiao.
  Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification.
  In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM) , 2024.
  
  
• Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang, Yiping Ke, Miao Qiao, Wei Zhang, Wei Khang Jeremy Sim, Balazs Gulyas.
  Contrastive Graph Pooling for Explainable Classification of Brain Networks.
  IEEE Transactions on Medical Imaging, 2024. PREMIA Best Student Paper Honourable Mention Award. (pdf)
  
  
• Yizhou Dai, Miao Qiao, Ronghua Li.
  On Density-based Local Community Search.
  Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS), 2024. (pdf, code)
  
  
• Chaoji Zuo, Miao Qiao, Wenchao Zhou, Feifei Li, Dong Deng.
  Range-Filtering Approximate Nearest Neighbor Search.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2024.(pdf)
  
  
• Zijin Feng, Miao Qiao, Hong Cheng.
  Modularity-based Hypergraph Clustering: Random Hypergraph Model, Hyperedge-cluster Relation, and Computation.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2023.(pdf)
  
  
• Jiaxing Xu*, Yunhan Yang*, David Tse Jung Huang*, Sophi Shilpa Gururajapathy*, Yiping Ke, Miao Qiao , Alan Wang, Haribalan Kumar, Josh McGeown, and Eryn Kwon.
  Data-Driven Network Neuroscience: On Data Collection and Benchmark.
  Proceedings of Neural Information Processing Systems (NIPS), Datasets and Benchmarks Track, 2023. (pdf)
  
  
• Wen, Grace, Vickie Shim, Samantha Jane Holdsworth, Justin Fernandez, Miao Qiao, Nikola Kasabov, and Alan Wang.
  Machine Learning for Brain MRI Data Harmonisation: A Systematic Review.
  Bioengineering, 2023. (pdf)
  
  
• Yizhou Dai, Miao Qiao, Lijun Chang.
  Anchored Densest Subgraph.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2022. (pdf, slides)
  
  
• Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, Xuemin Lin.
  On Scalable Computation of Graph Eccentricities.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2022. (pdf, code)
  
  
• Zijin Feng, Miao Qiao, Hong Cheng.
  Clustering Activation Networks.
  International Conference on Data Engineering (ICDE), 2022. (pdf)
  
  
• Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, Xuemin Lin.
  Distance labeling: on parallelism, compression, and ordering.
  International Journal on Very Large Data Bases (VLDBJ), 2022. (pdf)
  
  
• Miao Qiao, Yufei Tao.
  Two-Attribute Skew Free, Isolated CP Theorem, and Massively Parallel Joins.
  Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS) , 2021. (pdf)
  
  
• Hao Zhang, Miao Qiao, Jeffrey Xu Yu, Hong Cheng.
  Fast Distributed Complex Join Processing.
  International Conference on Data Engineering (ICDE), 2021.
  
  
• Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, Xuemin Lin.
  Scale Distance Labeling on Graphs with Core-Periphery Properties
  Proceedings of the International Conference on Management of Data (SIGMOD), 2020. (pdf)
  
  
• Lijun Chang, Miao Qiao.
  Deconstruct Densest Subgraphs
  Proceedings of the World Wide Web Conference (WWW), 2020. (pdf)
  
  
• Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, and Xuemin Lin
  Scaling Distance Labeling on Small-World Networks.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2019. (pdf)
  
  
• Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, and Xuemin Lin
  Exacting Eccentricity for Small-World Networks.
  IEEE International Conference on Data Engineering ( ICDE ), 2018. (pdf) Its extended (version) on VLDBJ.
  
  
• Miao Qiao, Hao Zhang, and Hong Cheng
  Subgraph Matching: on Compression and Computation.
  Very Large Database Endowment (PVLDB), 2018. (pdf)
  
  
• Yufei Tao, Xiaocheng Hu, Miao Qiao
  Stream sampling over windows with worst-case optimality and l-overlap independence.
  International Journal on Very Large Data Bases (VLDBJ), 2017. (pdf)
  
  
• Miao Qiao, Junhao Gan, and Yufei Tao
  Range Thresholding on Streams.
  Proceedings of ACM Conference on Management of Data (SIGMOD), 2016. (pdf)
  
  
• Xiaocheng Hu, Miao Qiao, Yufei Tao
  *Join Dependency Testing, Loomis-Whitney Join, and Triangle Enumeration
  Symposium on Principles of Database Systems (PODS), 2015. (pdf) Its extended (version) on JCSS.
  
  
• Xiaocheng Hu, Miao Qiao, Yufei Tao
  *External Memory Stream Sampling
  Symposium on Principles of Database Systems (PODS), 2015. (pdf)
  
  
• Xiaocheng Hu, Miao Qiao, Yufei Tao
  *Independent Range Sampling
  Symposium on Principles of Database Systems (PODS), 2014.(pdf)
  
  
• Miao Qiao, Lu Qin, Hong Cheng, Jeffrey Xu Yu, Wentao Tian
  Top-K Nearest Keyword Search on Large Graphs
  Very Large Database Endowment (PVLDB), 2013.(pdf)
  
  
• Miao Qiao, Hong Cheng, Lu Qin, Jeffrey Xu Yu, Philip S. Yu and Lijun Chang
  Computing Weight Constraint Reachability in Large Networks
  International Journal on Very Large Data Bases (VLDBJ), 2012. (pdf)
  
  
• Lijun Chang, Jeffrey Xu Yu, Lu Qin, Hong Cheng, Miao Qiao
  The Exact Distance to Destination in Undirected World
  International Journal on Very Large Data Bases (VLDBJ), 2012. (pdf)
  
  
• Miao Qiao, Hong Cheng, Lijun Chang and Jeffrey Xu Yu
  Approximate Shortest Distance Computing: A Query-Dependent Local Landmark Scheme
  International Conference on Data Engineering (ICDE), 2012. (pdf, slides, poster) Its extended (version) on TKDE.

Funding

• Subgraph Matching: Theory and Practice
  Royal Society of New Zealand, NZD 300,000, 2018-2024
  


• Advanced Graph Analytics for Human Brain Connectivity
  The Ministry of Business, Innovation and Employment, NZD 3,000,000, 2020-2024
  

Professional Services

• I was the review board member of PVLDB 2021
• I am/was a program committee member for the following conferences:
  • Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS), 2023
  • Australasian Database Conference (ADC), 2018
  • International Joint Conferences on Artificial Intelligence (IJCAI), 2019, 2020, 2021
  • International Conference on Information and Knowledge Management (CIKM), 2019
  • Association for the Advancement of Artificial Intelligence (AAAI), 2020, 2021


• I am/was an invited reviewer for the following conferences/journals:
  • Symposium on Computational Geometry (SCG), 2019
  • Transactions on Database Systems (TODS), 2015, 2018, 2019
  • Transactions on Knowledge and Data Engineering (TKDE), 2018, 2019, 2021
  • ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016
  • International Conference on Data Mining (ICDM), 2013, 2014
  • Web Information Systems Engineering (WISE), 2013
  • International Journal on Very Large Data Bases (VLDBJ), 2013, 2018, 2019, 2021
  • Neural Information Processing Systems (NIPS), 2021


• I was the program chair of the following conference:
  • Doctoral Consortium of International Semantic Web Conference (ISWC), 2019
  • Australasian Database Conference (ADC), 2021

Teaching Experiences

• Database Systems (2017-2023)
• Algorithms for Massive Data (2018-2019)
• Systems Analysis and Modeling (2016-2018)
• Algorithms(2017-2018)

Honors and Awards

• 2013, VLDB 2013 Travel Fellowship.
• 2008, Shanghai Jiao Tong University 1st Class Scholarship.
• 2007, ACM/ICPC, 3rd Place, Singapore.
• 2007, Computer World Scholarship.
• 2006, Singapore Technology Engineering Scholarship.
• 2005, ACM/ICPC, 1st Place, Korea.
• 2004, Silver medal nationwide, National Olympiad in Informatics, China.

Talks

• 2024, Scalable Query Processing with Graphs. Data Systems Seminar Series, University of Waterloo
• 2024, Scalable Query Processing with Graphs. Database group, CMU