Professor Wenjie Zhang
Wenjie Zhang is a Professor, ARC Future Fellow, Head of the Data and Knowledge Research Group ()and Deputy Head of School (Research) in the School of Computer Science and Engineering, the University of New South Wales, Australia. Her research interests include spatial-temporal data analysis, uncertain data analysis and graph data processing. Since 2008, she has published more than 160papers in top venues such asTKDE, TODS, VLDBJ, SIGMOD, VLDB, and ICDE. She received the Australian Research Council Future Fellowship (FT3) in 2021 and Discovery Early Career Researcher Award in 2011. In 2019, she received the Chris Wallace Award for her significant contributions to large-scale graph data processing. Her research has been well supported by 12 Australian Research Council grants and several industry funded projects. Wenjie is an Associate Editor for IEEE Transactions on Knowledge and Data Engineering and The VLDB Journal. The full list of her publications (and presentation slides) :
Mutiple PhD scholarships (living allowance around $35k-$40k/year plus tuition fee waive) available. Send me an email (wenjie.zhang@unsw.edu.au) with your CV if you would like to pursue PhD degree in the area of large-scale dynamicdata analytics and processing.
Current undergraduate students or master by course students in UNSW are encouraged to contact me if you are interested in research degrees (Master by research or PhD) or research projects (honors thesis project or master research project).
I will be co-chairing ICDE 2025 ()
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
National Competitive Grants:
- 2023 - 2025 Australian Research Council Discovery Project (DP230101445): Big Temporal Graph Processing in the Cloud, $495,000. Wenjie Zhang, Ying Zhang, Dong Wen, Xiaoyang Wang
- 2023 - 2029 Australian Research Council Centre of Excellence for Mathematical Modelling of Cellular Systems, $35 million. Chief Investigator and Research Theme Leader.
- 2022 - 2026 Australian Research Council Research Hub for Fire Resilience Infrastructure, Assets and Safety Advancements (FRIASA) in Urban, Resources, Energy and Renewables Sectors, $5 million. Chief Investigator.
- 2021 - 2025 Australian Research Council Future Fellowship (FT210100303): Efficient and Scalable Processing of Dynamic Heterogeneous Graphs, $1,085,000, Wenjie Zhang.
- 2021 - 2023 Australian Research Council Discovery Project (DP210101393): Efficient and scalable similarity query processing on big streaming graphs, $510,000, Ying Zhang and Wenjie Zhang.
- 2021 - 2025 ARC Industry Transformation Research Hub for Resilient and Intelligent Infrastructure Systems (RIIS) in Urban, Resources and Energy Sectors, $5 million. Chief Investigator.
- 2020 - 2022 Australian Research Council Discovery Project (DP200101116): Cohesive Subgraph Discovery on Big Bipartite Graphs, $430,000, Wenjie Zhang.
- 2018 - 2020 Australian Research Council Discovery Project (DP180103096): Efficient Processing of Large Scale Multi-dimensional Graphs, $407,974, Xuemin Lin, Wenjie Zhang and Ying Zhang.
- 2015 - 2017 Australian Research Council Discovery Project (DP150103071): Continuous Loyalty-based Similarity Queries over Moving Objects, $266, 300, Wenjie Zhang and Lei Chen.
- 2015 - 2017 Australian Research Council Discovery Project (DP150102728): Efficiently Processing Pattern-based Structure Queries over Large Graphs, $397, 500, Xuemin Lin and Wenjie Zhang.
- 2012 - 2014 Australian Research Council Discovery Early Career Researcher Award (DE120102144): Continuously Monitoring Uncertain Objects in a Multi-dimensional Space, $375, 000, Wenjie Zhang.
- 2012 - 2014 Australian Research Council Discovery Project (DP120104168): Ranking Complex Objects in a Multi-dimensional Space, $350, 000, Xuemin Lin and Wenjie Zhang
Other Industry and Government funded research projects:
- AI Trust and Trustworthiness: from responsible data management to retrieval-augmented generation for LLMs, $1.01 million.
- The Unification of Structured Multi-Modal Knowledge Base and Multi-Modal Foundation Models, $300, 000.
- Advanced Learning Analytics for Students with Cognitive Deficits (Google), $96,000.
- Data-driven AI in Business Analytics, $75, 000.
- Fraud Detection and Risk Mitigation in Financial Systems, $150,000.
- Efficient Relational DBMS Development, $560,000.
- Underground mine LoRa network for monitoring/control/backup/rescue/robotics, CRC-Project, $2 million.
- BHP Tailings Challenge Proof of Concept Stage, $64,000.
- Rock Bolt Detection Based on LiDAR Point Cloud, $84, 000.
- Towards Enabling Real-time and Secure Geospatial Data Analytics, $145, 000.
- Enabling AI-based Intelligence via Privacy Preserving Graph Technology, $145, 000.
- Anomaly detection from large-scale dynamic networks, $360,000.
- Automatic and Integrative Business Solution for Valuation Data Warehousing, $30, 000.
- 2023 Best Paper Award in the 34th Australasian Database Conference (ADC 2023).
- 2022 Google Inclusion Research Award
- 2022 Distinguished Associate Editor Award from VLDB 2022.
- 2022 Equity, Diversity and Inclusion Award, Faculty of Engineering UNSW.
- 2022 Best Student Paper Award in the 33rd Australasian Database Conference (ADC 2022).
- 2021 Australian Research Council Future Fellowship (FT3).
- 2021 Academic Excellence Award (for both Educational Excellence and Innovation and Research Excellence), Faculty of Engineering UNSW.
- 2021 Best Demonstration Award nomination in CIKM 2021.
- 2021 ACM SIGMOD Research Highlight Award:TheSIGMODResearch Highlight Award showcases research projects that exemplify core database research. In particular, “the project must address an important problem, represent a definitive milestone in solving the problem, and have the potential of significant impact.”
- 2020 ACM SIGMOD One of the Best Papers: The extended version of the paper was invited to publish in the special issue of "Best ofSIGMOD" in ACM Transactions on Database Systems (TODS). A concise version was invited to publish in the ACMSIGMODRecord.
- 2020 Best Paper Award in the 25th International Conference on Database Systems for Advanced Applications (DASFAA 2020).
- 2020 Best Student Paper Award inThe 13th International Conference on Knowledge Science, Engineering and Management (KSEM 2020).
- 2019 CORE Chris Wallace Awardfor Outstanding Research Contribution in the field of Computer Science (for my research contribution inLarge-scale Graph Data Processing): The annual prize is awarded to at most one academic for post-PhD research undertaken within a university or research institution in Australia or New Zealand. The research should include a notable breakthrough or a contribution of particular significance.
- 2019 One of the Best Papers inthe 24th International Conference on Database Systems for Advanced Applications (DASFAA 2019).
- 2013 One of the Best Papers in the 29th IEEE International Conference on Data Engineering (ICDE 2013). The extended version of the paper was invited to publish in the speical issue of "Best of ICDE" in IEEE Transactions on Knowledge and Data Engineering.
- 2013 Best Paper Award in the 14th International Conference on Web Information Systems Engineering WISE 2013.
- 2013 CiSRA Research Publication Award, CSE UNSW.
- 2012One of the Best Papers in the 28th IEEE International Conference on Data Engineering (ICDE 2012). The extended version of the paper was invited to publish in the speical issue of "Best of ICDE" in IEEE Transactions on Knowledge and Data Engineering.
-2012 One of the Best Papers inthe 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012).
- 2012 Best Student Paper Award inthe 17th International Conference on Database Systems for Advanced Applications (DASFAA 2012).
- 2012 Australian Research Council Early Career Researcher Award (DECRA).
- 2012 CiSRA Research Publication Award, CSE UNSW.
- 2010 One of the Best Papers in the 26th IEEE International Conference on Data Engineering (ICDE 2010).The extended version of the paper was invited to publish in the speical issue of "Best of ICDE" in IEEE Transactions on Knowledge and Data Engineering.
- 2010 Best Paper Award in the 21st Australasian Database Conference (ADC 2010).
- 2010 CiSRA Research Publication Award, CSE UNSW.
- 2009 Best Paper Award in the Joint International Conference APWeb/WAIM 2009.
Associate Editor for:
- IEEE Transactions on Knowledge and Data Engineering (TKDE), since 2016
- VLDB Journal, since 2022
Steering Committee Member for:
- DASFAA, since 2017
- ADC (Australasian Database Conference), since 2021
Program Committee Chair for:
- The 41st International Conference on Data Enigneering (ICDE) 2025.
- The 8th International Conference on Web Technologies and Big Data (APWeb-WAIM) 2024.
- The 22nd International Conference on Web Information Systems Engineerng
- The 2nd International Workshop on Large Scale Graph Data Analytics, in conjunction with VLDB 2020
- The 5th International Workshop on Big Data Quality Management, in conjunction with DASFAA 2020
- The 1st International Workshop on Large Scale Graph Data Analysis, in conjunction with ICDE 2019
- The 27th Australasian Database Conference (ADC) 2016
- The First International Workshop on Management of Spatial Temporal Data
Program Committee Track Chair for:
- PVLDB 2023 (Associate Editor)
- ICDE 2023
- ICDM 2023
- PVLDB 2022 (Associate Editor)
- ICDE 2019
Organizing Committee for:
- Tutorial Chair for TheWebConf 2025
- Anniversary Chair for ADMA 2024
- Tutorial Chair for DASFAA 2024
- Demo Chair for DASFAA 2021
- TKDE Poster Track Chair of ICDE 2019
- Doctoral Colloquium co-chair of MDM 2018
- TKDE Poster Track chair of ICDE 2017
- Workshop co-Chair of
- Chair for Research Student Symposium of
- Publicity Chair of
- Publication Chair of
- Publicity Chair of
Program Committee for:
- 2023: SIGMOD 2023, VLDB 2023 (Associate Editor), ICDE 2023 (Track chair), ICDM 2023 (Track Chair)
- 2022: SIGMOD 2022, VLDB 2022 (Associate Editor), ICDE 2022, CIKM 2022 (SPC), KDD 2022
- 2021: SIGMOD 2021, VLDB 2021, ICDE 2021, CIKM 2021 (senior PC), KDD 2021, SIGIR 2021, AAAI 2021, WSDM 2021, BigData 2021, DASFAA (senior TPC) 2021
- 2020: VLDB 2020, KDD 2020, SIGIR 2020, CIKM 2020, SIGSPATIAL 2020, PAKDD 2020
- 2019: VLDB 2019, ICDE 2019 (Track Chair), KDD 2019, CIKM 2019 (senior PC), SIGSPATIAL 2019, PAKDD 2019, ICDSC 2019, DASFAA 2019, ER 2019
- 2018: VLDB 2018, EDBT 2018, CIKM 2018, SIGSPATIAL 2018, DASFAA 2018, PAKDD 2018
- 2017: CIKM 2017, PAKDD 2017, DASFAA 2017
- 2016: EDBT 2016, PAKDD 2016, WAIM 2016, SIGSPPATIAL 2016
- 2015: EDBT 2015, CIKM 2015 (senior PC), SSTD 2015, SIGSPATIAL 2015, PAKDD 2015, WISE 2015
- 2014:, SIGSPATIAL 2014, VLDB PhD Workshop 2014, CIKM 2014, PAKDD 2014, WISE 2014, WebDB 2014
- 2013:,,,,
- 2012:,,,,
- 2011:,,
- 2010:,
- 2009: MOUND 2009 (workshop associated with ICDE 2009).
My Research Supervision
Multiple PhD positions available with full support of tuition fee and living stipend. Please send me a copy of your CV if you are interested in doing PhD with me. Currently undergraduate and master by course students of UNSW are welcome to discuss with me if you are interested in research degrees of either PhD or Master by Research / Master of Philosophy.
Some topics include:
Graph Data Processing: graph is a powerful model to captures objects as well as the relationships / connections among them, and is a commonly used tool in many different areas including world wide web, social networks, biology networks, protein interaction networks, traffic networks, etc. My research in this area focuses on supporting structure based queries over large scale graphs and cover various graph types including multi-dimensional graphs, attributed graphs, bipartite graphs, and heterogeneous information network.
Spatial Data Processing: the widely available positioning devices foster a rich amount of multi-dimensional spatial data. My research in this area focuses onspatial keyword search andspatial-social data processing.
AI / Machine Learning Techniques for Large-scale Data Analytics and Processing: to apply machine learning techniques to improve efficiency and effectiveness in managing large-scale data.
Large language models: harness the power of large language models for AI and data science tasks.