Jing Du @ UNSW


Jing Du 

Postdoctoral Research Fellow.

School of Computer Science & Engineering, University of New South Wales.

Sydney, Australia

Email: jing.du2@unsw.edu.au

Biography

I am now a postdoctoral research fellow at the School of Computer Science & Engineering, University of New South Wales, supervised by Prof. Flora Salim. Previously, I worked as a postdoc at the School of Computing, Macquarie University, under the supervision of A/Prof. Jia Wu. During 2020 to 2024, I was a PhD candidate at the School of Computer Science and Engineering, the University of New South Wales, supervised by Prof. Lina Yao and Prof. Wenjie Zhang. I received my M.S. and B.S. degree from the School of Computer Science, Northwestern Polytechnical University , in 2020 and 2017, under the supervision of Prof. Bin Guo.


Research Interest

My research centers on the following 3 research focus:

  • Human-centric Intelligence
  • Graph Representation Learning
  • Spatio-temporal Modeling
aiming to design adaptive and trustworthy AI systems that can robustly interpret complex, multimodal data. I develop principled methods that advance both the theoretical foundations and practical applications of machine learning, with demonstrated impact in brain network analysis, personalized recommendation, epidemic forecasting, and societal decision-making. Looking ahead, my long-term vision is to establish next-generation human-centric AI frameworks that seamlessly integrate graph-based and spatio-temporal reasoning, enabling robust, interpretable, and equitable decision support across critical domains such as healthcare, public safety, and sustainable society.
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Publications

Conference Papers

    A Probabilistic Framework for Imputing Genetic Distances in Spatiotemporal Pathogen Models
    Haley Stone, Jing Du, Hao Xue, Matthew Scotch, David Heslop, Andreas Zufle, Raina MacIntyre, and Flora Salim
    TOPICS: Avian Flu Forecasting, Epidemic Modeling
    33rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2025)
    Minneapolis, MN, USA, November 3 - November 6, 2025


    Explicit and Implicit Data Augmentation for Social Event Detection
    Congbo Ma, Yuxia Wang, Jia Wu, Jian Yang, Jing Du, Zitai Qiu, Qing Li, Hu Wang, Preslav Nakov
    TOPICS: Event Detection, Data Augmentation, Large Language Models
    The 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025)
    Vienna, Austria, July 27–August 1st, 2025


    Enhanced Social Event Detection through Dynamically Weighted Meta-Paths Modeling
    Congbo Ma, Zitai Qiu, Hu Wang, Jing Du, Shan Xue, Jia Wu and Jian Yang
    TOPICS: Event Detection, Meta-path Modeling
    International World Wide Web Conference 2025 (The WebConf 2025)
    Sydney, Australia, 28 April - 2 May, 2025


    Counterfactual Brain Graph Augmentation Guided Bi-Level Contrastive Learning for Disorder Analysis
    Guangwei Dong, Xuexiong Luo, Jing Du, Jia Wu, Shan Xue, Jian Yang, and Amin Beheshti
    TOPICS: Data Augmentation, Brain Disorder analysis
    IEEE International Conference on Data Mining (ICDM) 2024(ICDM 2024)
    Abu Dhabi, UAE, 9-12 December 2024.


    Distributionally-Adaptive Variational Meta Learning for Brain Graph Classification
    Jing Du, Guangwei Dong, Congbo Ma, Shan Xue, Jia Wu, Jian Yang, Amin Beheshti, Quan Z. Sheng, Alexis Giral
    TOPICS: Brain Disorder Recognition, Graph Neural Network, Distributional Adaptation
    The 27th International Conference on Medical Image Computing and Computer Assisted Intervention 2024(MICCAI 2024)
    Marrakech, Morocco, 6-10 October, 2024


    Identifiability of Cross-Domain Recommendation via Causal Subspace Disentanglement
    Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Lina Yao
    TOPICS: Cross-domain Recommendation, Domain Adaptation
    The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR 2024)
    Washington D.C., USA, July 14-18, 2024


    NP-SSL: A Modular and Extensible Self-supervised Learning Library with Neural Processes
    Zesheng Ye, Jing Du, Yao Liu, Yihong Zhang, Lina Yao
    TOPICS: Probabilistic Meta-Learning
    The 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)
    United Kingdom, Oct. 21 - Oct. 25 2023


    Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation
    Jing Du, Zesheng Ye, Bin Guo, Zhiwe Yu, Lina Yao
    TOPICS: Graph Neural Network, Supervised Domain Adaptation, Cross-Domain Recommendation
    The 23rd IEEE International Conference on Data Mining(ICDM 2023)
    Shanghai, China, December 1 - December 4, 2023


    IDNP: Interest Dynamics Modeling using Generative Neural Processes for Sequential Recommendation
    Jing Du, Zesheng Ye, Lina Yao, Bin Guo, Zhiwen Yu
    TOPICS: Temproral Dynamics Modeling, Probabilistic Models, Sequential Recommendation
    The 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)
    Singapore Feb. 27 - Mar. 3 2023


    Socially-aware Dual Contrastive Learning for Cold-Start Recommendation
    Jing Du, Zesheng Ye, Lina Yao, Bin Guo, Zhiwen Yu
    TOPICS: Social Network Mining, Dynamic graph neural network, Cold-start Recommendation
    The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR 2022)
    New Madrid, Spain, July 11-15, 2022


    Hierarchical Task-aware Multi-Head Attention Network
    Jing Du, Lina Yao, Xianzhi Wang, Bin Guo, Zhiwen Yu
    TOPICS: Multitask learning, Context-aware Recommendation
    The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR 2022)
    New Madrid, Spain, July 11-15, 2022


Journal Papers

    Community-Structure Enhanced Brain Graph Mining
    Shichen Luo, Xuexiong Luo, Jing Du, Jia Wu, Jian Yang
    TOPICS: Brain Disorder Analysis, Graph Data Mining
    IEEE Transactions on Artificial Intelligence (IEEE TAI)


    Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference
    TOPICS: Cross-domain Recommendation, Joint Identifiability, Generative Modeling
    Jing Du, Zesheng Ye, Bin Guo, Zhiwen Yu, Jia Wu, Jian Yang, Michael Sheng, Lina Yao
    2019 IEEE Transactions of Knowledge and Data Engineering (under review)

    CrowDNet: Enabling a Crowdsourced Object Delivery Network based on Modern Portfolio Theory
    TOPICS: Task Allocation, Trajectory Analysis
    Jing Du, Bin Guo, Yan Liu, Liang Wang, Qi Han, Chao Chen, Zhiwen Yu
    2019 IEEE Internet of Things

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Awards & Honors

  • MICCAI Registration Grant, 2024
  • The Rising Stars Women in Engineering Workshop, 2022
  • SIGIR Student Travel Grant, 2022
  • Chinese Scholarship Council(CSC) Scholarship. from 2020 to 2024
  • UNSW Tuition Fee Scholarship. from 2020 to 2024
  • Outstanding Master Thesis, NWPU. 2020
  • Zhong Hang Talent Scholarships. 2019
  • First Prize of Northwestern Polytechnical University Scholarships. 2019
  • Second Prize of Northwestern Polytechnical University Scholarships. 2018, 2017
  • First Prize of Programming Competition, NWPU 2016
  • ... ...
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Academia Services

  • Area Chair, IJCNN 2025.
  • PC member, AAAI 2025.
  • PC member, ACL 2025.
  • PC member, SIGIR 2023, 2024, 2025.
  • PC member, WWW/TheWebConf 2024, 2025.
  • PC member, SIGIR-AP 2023, 2024, 2025.
  • Reviewer, CIKM 2023, 2024, 2025.
  • Reviewer, MICCAI 2024, 2025.
  • Reviewer, ADMA 2022, 2023, 2024.
  • Reviewer, IMWUT.
  • Reviewer, IEEE Transactions of Knowledge and Data Engineering.
  • Reviewer, IEEE Transactions of Information System.
  • Reviewer, Frontiers of Computer Science.
  • Reviewer, IEEE Transactions on Human-Machine Systems.
  • Reviewer, Knowledge-Based Systems.
  • External reviewer, KDD 2022.
  • External reviewer, PAKDD 2022.
  • External reviewer, SIGIR 2022.
  • Reviewer, PPNA 2021.
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Teaching Experience

  • ZZSC 9020 Data Science Project, 2025 Hexamester 5, Mentor.
  • COMP 9727 Recommender Systems, 2025 Term 2, Tutor.
  • COMP 9727 Recommender Systems, 2022 Term 2, Tutor.
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Last modified: 2025-02-20