Dr. Wen Hua

Lecturer, ARC DECRA Fellow
Data Science Research Group (DS)
School of Information Technology and Electrical Engineering (ITEE)
The University of Queensland, Australia
Office: Room 637, Building 78, St Lucia Campus
Phone: (61-7) 3365 2988
Email: w.hua@uq.edu.au


Dr. Wen Hua currently works as a Lecturer (tenure) and an ARC DECRA Fellow at School of Information Technology and Electrical Engineering, the University of Queensland, Australia. From April 2016 to April 2017, she was appointed as a Postdoctoral Research Fellow at the University of Queensland. She received her PhD degree (under the supervision of Prof Xiaofang Zhou) and Bachelor degree (under the supervision of Prof Xiaoyong Du) in Computer Science from Renmin University of China in 2015 and 2010, respectively. She was awarded the ARC Discovery Early Career Researcher Award (DECRA) in 2021 and the Advance Queensland Early Career Research Fellowship (AQRF) in 2017, two highly-competitive fellowships for early-career researchers. Her current research interests include information extraction and retrieval, data mining, natural language processing, spatiotemporal data management, high performance query processing, and social media analytics. She has published actively in reputed journals and top international conferences including SIGMOD, PVLDB, ICDE, TKDE, VLDBJ, IJCAI, SIGIR, CIKM, WSDM, WWWJ, etc.

Research Interest

  • Information Extraction and Retrieval
  • Knowledge Graph
  • Large Scale Spatiotemporal Data Analysis
  • Data Integration
  • Natural Language Processing
  • Social Media Analytics

Available Projects for Prospective Students

We are looking for highly motivated PhD students for the following research projects. The University of Queensland ranks in the top 50 as measured by the Performance Ranking of Scientific Papers for World Universities. It also ranks 47 in the QS World University Rankings, 52 in the US News Best Global Universities Rankings, 60 in the Times Higher Education World University Rankings, and 55 in the Academic Ranking of World Universities.

  • [2021-2024] Joint PhD with Oracle Labs Australia, Context-aware Representation Learning for Code Analysis
  • [2021-2023] ARC DECRA Project, Information Extraction from Large-Scale Low-Quality Data
  • [2020-2025] ARC Training Centre for Information Resilience
  • [2020-2022] ARC Discovery Project, Making Spatiotemporal Data More Useful: An Entity Linking Approach

Selected Recent Publications [Full Publications]

  1. [WSDM 2022] Informed Multi-context Entity Alignment
    Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, and Xiaofang Zhou
  2. [ICDE 2021] Dynamic Hub Labelling for Road Networks
    Mengxuan Zhang, Lei Li, Wen Hua, Rui Mao, Pingfu Chao, and Xiaofang Zhou
  3. [ICDE 2021] Efficient Constrained Shortest Path Query Answering with Forest Hop Labeling
    Ziyi Liu, Lei Li, Mengxuan Zhang, Wen Hua, Pingfu Chao, and Xiaofang Zhou
  4. [ICDE 2021] Efficient 2-Hop Labeling Maintenance in Dynamic Small-World Networks
    Mengxuan Zhang, Lei Li, Wen Hua, and Xiaofang Zhou
  5. [CIKM 2021] Summarizing Long-Form Document with Rich Discourse Information
    Tianyu Zhu, Wen Hua, Jianfeng Qu, and Xiaofang Zhou
  6. [EMNLP 2021] ActiveEA: Active Learning for Neural Entity Alignment
    Bing Liu, Harrisen Scells, Guido Zuccon, Wen Hua, and Genghong Zhao
  7. [ECIR 2021] Knowledge Graph Convolution Networks for Ranking Diagnoses
    Bing Liu, Guido Zuccon, Wen Hua, and Weitong Chen
  8. [WISE 2021] An Ecient Approach for Spatial Trajectory Anonymization
    Yuetian Wang, Wen Hua, Fengmei Jin, Jing Qiu, and Xiaofang Zhou
  9. [TKDE 2021] A Noise-aware Method with Type Constraint Pattern for Neural Relation Extraction
    Jianfeng Qu, Wen Hua, Dantong Ouyang, and Xiaofang Zhou
  10. [WWWJ 2021] Temporal Knowledge Completion with Context-Aware Embeddings
    Yu Liu, Wen Hua, Jianfeng Qu, Kexuan Xin, and Xiaofang Zhou
  11. [WWWJ 2021] LoG: A Locally-Global Model for Entity Disambiguation
    Kexuan Xin, Wen Hua, Yu Liu, and Xiaofang Zhou
  12. [WWWJ 2021] Temporal Knowledge Extraction From Large-scale Text Corpus
    Yu Liu, Wen Hua, and Xiaofang Zhou