Dongjie Wang

Assistant Professor, University of Kansas.

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Dongjie Wang is an assistant professor in the Department of Electrical Engineering and Computer Science at the University of Kansas. His research focuses on data-centric AI, causal graph learning, spatial-temporal data mining, user profiling, and graph mining. During his Ph.D., he interned at prestigious institutions like Nokia Bell Labs, NEC Labs America, and JD.COM Silicon Valley Research Center. He has published over 30 papers in leading journals (e.g., TKDE, KAIS) and conferences (e.g., NeurIPS, KDD, AAAI, WWW). Three of his papers (SIGSPATIAL, ICDM1, ICDM2) were best paper runner-ups, and his NeurIPS paper was a spotlight. His work on automated urban planning received media coverage from Synced AI and UCF Today. He also serves as a PC member for conferences and journals such as KDD, IJCAI, AAAI, WSDM, CIKM, TNNLS, KBS, and TKDD.


For Perspective Students

[TA/RA positions available] We are seeking highly motivated Ph.D. students to join our team. If you’re interested in data mining and its applications, please contact me at wangdongjie100@gmail.com. Include your CV, transcripts, TOEFL & GRE scores, and other relevant materials. Use the subject format “Interested_Student_PhD_Your Name_…”.

The University of Kansas (KU), the state’s flagship university, is a member of the Association of American Universities (AAU) and recognized as a Research I (R1) institution by the Carnegie Classification. For more details on the Computer Science Ph.D. program application process, visit the website.


Announcement

We will host the third Data-Centric AI Workshop at CIKM 2024 📊. If you are interested in this topic, we welcome you to submit your paper 📝. For more details, please visit this link.

Additionally, we will host the first tutorial, “Tabular Data-Centric AI: Challenges, Techniques, and Future Perspectives,” at CIKM 2024 📚. If you are interested, we invite you to participate and engage in discussions with us 🤝.


News

2024/07/17 Congratulations! I will host the third data-centric AI workshop and the first data-centric AI tutorial at CIKM 2024. :fireworks:
2024/07/17 Congratulations! My four papers was accepted by the CIKM 2024 conference. :fireworks:
2024/05/17 Congratulations! My one papers was accepted by the KDD 2024 conference. :fireworks:
2023/12/17 Congratulations! My two papers was accepted by the SDM 2024 conference. :fireworks:
2023/12/13 Congratulations! My paper was accepted by the TKDD journal. :fireworks:

Selected Publications [See More]

2023

  1. NeurIPS’23
    Reinforcement-enhanced autoregressive feature transformation: Gradient-steered search in continuous space for postfix expressions
    Dongjie Wang, Meng Xiao, Min Wu, Yuanchun Zhou, and Yanjie Fu
    Advances in Neural Information Processing Systems, 2023
  2. KDD’23
    Interdependent Causal Networks for Root Cause Localization
    Dongjie Wang, Zhengzhang Chen, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, and Haifeng Chen
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  3. KDD’23
    Incremental Causal Graph Learning for Online Root Cause Analysis
    Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, and Haifeng Chen
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
  4. AAAI’23
    Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning
    Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, and Yanjie Fu
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2023
  5. Reinforced Imitative Graph Learning for Mobile User Profiling
    Dongjie Wang, Pengyang Wang, Yanjie Fu, Kunpeng Liu, Hui Xiong, and Charles E. Hughes
    IEEE Transactions on Knowledge and Data Engineering, 2023

2022

  1. KDD’22
    Group-wise reinforcement feature generation for optimal and explainable representation space reconstruction
    Dongjie Wang, Yanjie Fu, Kunpeng Liu, Xiaolin Li, and Yan Solihin
    In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

2021

  1. AAAI’21
    Reinforced imitative graph representation learning for mobile user profiling: An adversarial training perspective
    Dongjie Wang, Pengyang Wang, Kunpeng Liu, Yuanchun Zhou, Charles E Hughes, and Yanjie Fu
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2021