🤵🏻 About Me

I am a machine learning researcher specializing in time series forecasting, spatio-temporal data mining, graph learning, and LLM. I obtained my doctoral degree from the Big Data College at the University of Science and Technology of China in June 2024. Currently, I am an assistant professor at the Suzhou Institute for Advanced Study at the University of Science and Technology of China.

My research interests include topics in time series, Ai4Science, multimodal learning, spatio-temporal data mining, and continual learning. Most recently, I am interested in the following topics:

📢: 欢迎对机器学习与人工智能感兴趣、具备编程基础且自我驱动力强的同学加入！ 有意者请将个人简历、成绩单及简要自我介绍发送至邮箱：wbw2024@ustc.edu.cn。

🎉 News

• 2026.07: Serve as an Area Chair of ICLR 2027!
• 2026.04: Two papers are accepted by ICML 2026!
• 2026.04: One papers are accepted by TKDE!
• 2026.04: One papers are accepted by ACL 2026 (Main)!
• 2026.01: Two papers are accepted by IJCAI 2026!
• 2026.01: Two papers are accepted by ICLR 2026!
• 2025.12: One paper is accepted by ACM WWW 2026!
• 2025.12: One paper is accepted by AAAI 2026!
• 2025.10: 恭喜王冠军、黄盛、马佳明获得国奖奖学金！
• 2025.10: Three papers are accepted by NeurIPS 2025!
• 2025.08: One paper is accepted by ACM MM!
• 2025.06: One paper is accepted by IEEE TMC!
• 2025.05: One paper is accepted by ICML 2025!
• 2025.04: One paper is accepted by IJCAI 2025!
• 2025.02: One paper is accepted by VLDB 2025!

📝 Publications

Conference Papers (#:Corresponding Author)

• Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models
  Zhiqing Cui, Binwu Wang#, Qingxiang Liu, Yeqiang Wang, Zhengyang Zhou, Yuxuan Liang, Yang Wang In: The Annual Meeting of the Association for Computational Linguistics (ACL 2026, CCF-A (main)).
  
• One for Two: A Unified Framework for Imbalanced Graph Classification via Dynamic Balanced Prototype.
  Guanjun Wang, Binwu Wang#, Jiaming Ma, Zhengyang Zhou, Pengkun Wang, Xu Wang, Yang Wang.
  In: The Fourteenth International Conference on Learning Representations (ICLR 2026, CCF-A, Oral).
  
• PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting.
  Jiaming Ma, Qihe Huang, Guanjun Wang, Haofeng Ma, Sheng Huang, Zhengyang Zhou, Pengkun Wang, Xu Wang, Binwu Wang#, Yang Wang.
  In: The Fourteenth International Conference on Learning Representations (ICLR 2026, CCF-A).
  
• We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification.
  Zhipeng Liu, Peibo Duan, Xuan Tang, Haodong Jing, Mingyang Geng, Yongsheng Huang, Jialu Xu, Bin Zhang, Binwu Wang#.
  In: The Fourteenth International Conference on Learning Representations (WWW 2026, CCF-A, Oral).
  
• Disms-ts: Eliminating redundant multi-scale features for time series classification.
  Zhipeng Liu, Peibo Duan, Binwu Wang#, Xuan Tang, Qi Chu, Changsheng Zhang, Yongsheng Huang, Bin Zhang.
  In: Proceedings of the 33rd ACM International Conference on Multimedia (ACM MM, CCF-A).
  
• Less but more: Linear adaptive graph learning empowering spatiotemporal forecasting.
  Jiaming Ma, Binwu Wang#, Pengkun Wang, Zhengyang Zhou, Xu Wang, Yang Wang.
  In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025, CCF-A).
  
• Mofo: Empowering long-term time series forecasting with periodic pattern modeling.
  Jiaming Ma, Binwu Wang#, Pengkun Wang, Zhengyang Zhou, Xu Wang, Yang Wang.
  In: International Conference on Machine Learning (NeurIPS 2025, CCF-A).
  
• Robust Spatio-Temporal Centralized Interaction for OOD Learning.
  Jiaming Ma, Binwu Wang#, Pengkun Wang, Zhengyang Zhou, Xu Wang, Yang Wang.
  In: International Conference on Machine Learning (ICML 2025, CCF-A).
  
• BiST: A Lightweight and Efficient Bi-directional Model for Spatiotemporal Prediction.
  Jiaming Ma, Binwu Wang#, Pengkun Wang, Zhengyang Zhou, Xu Wang, Yang Wang .
  In: International Conference on Very Large Data Bases (VLDB 2025, CCF-A).
  
• LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems.
  Pengkun Wang, Zhe Zhao, Haibin Wen, Fanfu Wang, Binwu Wang, Qingfu Zhang, Yang Wang.
  In: The ‌Annual Conference on Neural Information Processing Systems‌ (NeurIPS 2024, CCF-A).
  
• STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts.
  Binwu Wang, Jiaming Zhou, Pengkun Wang, Xu Wang, Yudong Zhang, Zhengyang Zhou, Yang Wang.
  In: ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024, CCF-A).
  
• Make Bricks With A Little Straw: Large-Scale Spatio-Temporal Graph Learning with Restricted GPU-Memory Capacity.
  Binwu Wang, Pengkun Wang, Zhengyang Zhou, Zhe Zhao, Wei Xu, Yang Wang.
  In: International Joint Conference on Artificial Intelligence (IJCAI 2024, CCF-A).
  
• Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective.
  Binwu Wang, Pengkun Wang, Yudong Zhang, Zhengyang Zhou, Xu Wang, Lei Bai, Yang Wang.
  In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2024, CCF-A).
  
• Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning.
  Binwu Wang, Pengkun Wang, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang.
  In: International Conference on Learning Representations (ICLR 2024, CCF-A).
  
• When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification.
  Wei Xu , Pengkun Wang , Zhe Zhao , Binwu Wang , Xu Wang , Yang Wang
  In: Proceedings of the ACM on Web Conference (WWW 2024, CCF-A).
  
• CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement.
  Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang, Zhengyang Zhou, Yang Wang
  In: Advances in Neural Information Processing Systems Datasets and Benchmarks (NeurIPS 2023, CCF-A).
  
• Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction.
  Binwu Wang , Yudong Zhang , Xu Wang , Pengkun Wang , Zhengyang Zhou , Lei Bai , Yang Wang
  In: ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023, CCF-A).
  

Journal Papers

• MobiMixer: A Multi-scale Spatiotemporal Mixing Model for Mobile Traffic Prediction.
  Jiaming Ma, Binwu Wang#, Pengkun Wang, Zhengyang Zhou, Yudong Zhang, Xu Wang, Yang Wang.
  In: IEEE Transactionson Mobile Computing (IEEE TMC, SQI-1, CCF-A).
  
• Modeling Spatio-Temporal Mobility across Data Silos via Personalized Federated Learning.
  Yudong Zhang, Xu Wang, Pengkun Wang, Binwu Wang, Binwu Wang, Yang Wang.
  In: Advanced Engineering Informatics (AEI 2025, SQI-1,CCF-B).
  
• Meta Koopman Decomposition for Time Series Forecasting Under Temporal Distribution Shifts.
  Yudong Zhang, Xu Wang, Zhaoyang Sun, Pengkun Wang, Binwu Wang, Limin Li, Yang Wang.
  In: IEEE Transactionson Mobile Computing (IEEE TMC, SQI-1, CCF-A).
  
• Adaptive and Interactive Multi-Level Spatio-Temporal Network for Traffic Forecasting.
  Yudong Zhang, Pengkun Wang, Xu Wang, Binwu Wang, Lei Bai, Yang Wang
  In: IEEE Transactions on Intelligent Transportation Systems (IEEE TITS, SQI-1区), in press, 2024.
  
• Condition-Guided Urban Traffic Co-Prediction With Multiple Sparse Surveillance Data.
  Binwu Wang, Pengkun Wang, Yudong Zhang, Xu Wang, Zhengyang Zhou, Yang Wang
  In: IEEE Transactions on Vehicular Technology (IEEE TVT, SQI-2区), in press, 2024.
  
• Face Anti-spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective.
  Limin Li, Binwu Wang#, Xu Wang, Peng-Kun Wang, Yu-Dong Zhang, Yang Wang
  In: Journal of Computer Science and Technology (JCST，CCF-B), in press, 2024.
  
• Knowledge Expansion and Consolidation for Continual Traffic Prediction With Expanding Graphs.
  Binwu Wang, Yudong Zhang, Jiahao Shi, Pengkun Wang, Xu Wang, Lei Bai, Yang Wang
  In: IEEE Transactions on Intelligent Transportation Systems (IEEE TITS, SQI-1区), in press, 2023.
  

🤝 Activities

Conference Committee

• Program Committee Member, WWW 2026.
• Program Committee Member, NeurIPS 2025.
• Program Committee Member, AAAI 2026.
• Program Committee Member, ICML 2025.

Journal Committee

• Reviewer for Nature Communications, IEEE TKDE, IEEE TITS, IEEE TVT, etc.