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Biography

I am currently serving as an Associate Researcher at the Suzhou Institute for Advanced Research, University of Science and Technology of China. I was awarded my Ph.D. from University of Science and Technology of China in 2024, and I obtained my Bachelor of Science degree from Northeastern University in 2017. My research interests encompass Spatiotemporal Data Mining, Time Series Analysis, and the application of Artificial Intelligence in scientific research.

I am actively seeking students who are passionate about the following areas: diffusion models, molecular generation/design, and specular analysis. If you are interested in collaborating on these exciting topics, please do not hesitate to contact me at wx309@ustc.edu.cn.

Publications

  • Wang, X., Wang, P., Wang, B., Zhang, Y., Zhou, Z., Bai, L., & Wang, Y. (2023). Latent Gaussian Processes based Graph Learning for Urban Traffic Prediction. IEEE Transactions on Vehicular Technology.
  • Wang, X., Zhang, H., Wang, P., Zhang, Y., Wang, B., Zhou, Z., & Wang, Y. (2023, August). An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2409-2418).
  • Xu Wang, Pengfei Gu, Yudong Zhang, Binwu Wang, Pengkun Wang, Yang Wang*. Gradient Reactivation Enhanced Causal Attention for Out-Of-Distribution Generalizable Graph Classification. ICASSP'24
  • Wang, X., Chen, L., Zhang, H., Wang, P., Zhou, Z., & Wang, Y. (2023, February). A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (pp. 294-302).
  • Zhou, Z., Shi, J., Zhang, H., Chen, Q., Wang, X.*, Chen, H., & Wang, Y. (2024). CreST: A Credible Spatiotemporal Learning Framework for Uncertainty-aware Traffic Forecasting. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining 2024.
  • Hongbo Zhang, Guang Wang, Xu Wang, Zhengyang Zhou, Chen Zhang, Zheng Dong, Yang Wang*. NondBREM: Nondeterministic Offline Reinforcement Learning for Large-Scale Order Dispatching. AAAI'24.
  • Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Lei Bai, Yang Wang*. Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective. AAAI'24.
  • Binwu Wang, Pengkun Wang*, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang, Yang Wang*. Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning. ICLR'24.
  • Wei Xu, Pengkun Wang*, Zhe Zhao, Binwu Wang, Xu Wang, Yang Wang*. When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification. WWW'24
  • Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Yang Wang*. Condition-Guided Urban Traffic Co-Prediction With Multiple Sparse Surveillance Data. TVT.
  • Yudong Zhang, Pengkun Wang, Binwu Wang, Xu Wang, Zhe Zhao, Zhengyang Zhou, Lei Bai*, Yang Wang*. Adaptive and Interactive Multi-Level Spatio-Temporal Network for Traffic Forecasting. TITS.
  • Binwu Wang, Jiaming Ma, Pengkun Wang, Xu Wang, Yudong Zhang, Zhengyang Zhou, Yang Wang*. STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts. KDD'24.
  • Li, L. M., Wang, B. W., Wang, X., Wang, P. K., Zhang, Y. D., & Wang, Y. Face Anti-spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective. Journal of Computer Science and Technology.
  • Wang, B., Zhang, Y., Wang, X., Wang, P., Zhou, Z., Bai, L., & Wang, Y. (2023, August). Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2223-2232).
  • Yang, K., Zhou, Z., Sun, W., Wang, P., Wang, X., & Wang, Y. (2023, August). EXTRACT and REFINE: Finding a Support Subgraph Set for Graph Representation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 2953-2964).
  • Zhou, Z., Huang, Q., Yang, K., Wang, K., Wang, X., Zhang, Y., ... & Wang, Y. (2023). Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 3603–3614).
  • Wang, B., Zhang, Y., Shi, J., Wang, P., Wang, X., Bai, L., & Wang, Y. (2023). Knowledge Expansion and Consolidation for Continual Traffic Prediction With Expanding Graphs. IEEE Transactions on Intelligent Transportation Systems.
  • Wang, K., Liang, Y., Wang, P., Wang, X., Gu, P., Fang, J., & Wang, Y. (2022, September). Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective. In The Eleventh International Conference on Learning Representations.
  • Wang, P., Wang, X., Wang, B., Zhang, Y., Bai, L., & Wang, Y. (2023, April). Long-Tailed Time Series Classification via Feature Space Rebalancing. In International Conference on Database Systems for Advanced Applications (pp. 151-166). Cham: Springer Nature Switzerland.
  • Zhang, Y., Lu, W., Wang, X., Wang, P., & Wang, Y. (2023, June). Pondering About Task Spatial Misalignment: Classification-Localization Equilibrated Object Detection. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE.
  • Wang, B., Zhang, Y., Wang, P., Wang, X., Bai, L., & Wang, Y. (2023, April). A Knowledge-Driven Memory System for Traffic Flow Prediction. In International Conference on Database Systems for Advanced Applications (pp. 192-207). Cham: Springer Nature Switzerland.
  • 周正阳，刘浩，王琨，王鹏焜，王旭，汪炀*， 基于教师-学生时空半监督网络的城市事件预测方法. 电子学报 2023.
  • Wang, K., Zhou, Z., Wang, X., Wang, P., Fang, Q., & Wang, Y. (2022). A2DJP: A two graph-based component fused learning framework for urban anomaly distribution and duration joint-prediction. IEEE Transactions on Knowledge and Data Engineering.
  • Wang, P., Zhu, C., Wang, X., Zhou, Z., Wang, G., & Wang, Y. (2022). Inferring intersection traffic patterns with sparse video surveillance information: An st-gan method. IEEE Transactions on Vehicular Technology, 71(9), 9840-9852.
  • Wang, P., Wang, X., Wang, B., Zhang, Y., Bai, L., & Wang, Y. (2022, November). Countering Modal Redundancy and Heterogeneity: A Self-Correcting Multimodal Fusion. In 2022 IEEE International Conference on Data Mining (ICDM) (pp. 518-527). IEEE.
  • Wang, P., Ge, C., Zhou, Z., Wang, X., Li, Y., & Wang, Y. (2021). Joint gated co-attention based multi-modal networks for subregion house price prediction. IEEE Transactions on Knowledge and Data Engineering.