Task Force on AI for Time Series and Spatio-Temporal Data

Past Academic Activities

In recent years, we have engaged in a variety of academic activities that are pertinent to the objectives of this proposed Task Force. These activities have included workshops, seminars, collaborative research projects, and discussions aimed at addressing critical issues. Together, they have laid a strong foundation for the Task Force’s future initiatives. Here, we primarily list the related workshops and tutorials.

Time Series-Related Activities

Workshops

  • 2025 WWW Workshop on AI for Web-Centric Time Series Analysis (AI4TS): Theory, Algorithms, and Applications (WWW’25-AI4TS)
  • KDD Workshop on Mining and Learning from Time Series (KDD’23-MiLeTS, KDD’24-MiLeTS, KDD’25-MiLeTS)
  • AAAI Workshop on AI for Time Series Analysis: Theory, Algorithms, and Applications (AAAI’24-AI4TS, AAAI’25-AI4TS)
  • IJCAI Workshop on AI for Time Series Analysis: Theory, Algorithms, and Applications (IJCAI’23-AI4TS, IJCAI’24-AI4TS, IJCAI’25-AI4TS)
  • SDM Workshop on AI for Time Series Analysis: Theory, Algorithms, and Applications (SDM’24-AI4TS, SDM’25-AI4TS)
  • ICAIF Workshop on Foundation Models for Time Series: Exploring New Frontiers (ICAIF’24-FM4TS)
  • ICDM Workshop on AI for Time Series Analysis: Theory, Algorithms, and Applications (ICDM’23-AI4TS)

Tutorials

  • Yuxuan Liang, Jiaxi Hu, Ming Jin, Dongjin Song, Shirui Pan and Qingsong Wen, “Foundation Models for Time Series Analysis: A Tutorial”, Tutorial at the 39th AAAI Conference on Artificial Intelligence (AAAI 2025), Philadelphia, PA, USA, Feb. 2025.
  • Kun Yi, Qi Zhang, Wei Fan, Longbing Cao, Shoujin Wang, Guodong Long, Liang Hu, Hui He, Qingsong Wen, Hui Xiong, “Deep Learning in the Frequency Domain: Advances, Challenges, and Applications for Time Series Analysis,” in 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, Canada, Aug. 2025.
  • Yuxuan Liang, Haomin Wen, Yuqi Nie, Yushan Jiang, Ming Jin, Dongjin Song, Shirui Pan, Qingsong Wen, “Foundation Models for Time Series Analysis”, Tutorial at the 30th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Barcelona, Spain, Aug. 2024.
  • Qingsong Wen, Linxiao Yang, Tian Zhou, Weiqi Chen, Bingqing Peng, Liang Sun, “Robust Time Series Analysis and Applications: An Interdisciplinary Approach”, Tutorial at 23rd IEEE International Conference on Data Mining (ICDM 2023), Shanghai, China, Dec. 2023.
  • Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun, “Robust Time Series Analysis and Applications: An Industrial Perspective”, Tutorial at the 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2022), Washington DC, USA, Aug. 2022 (70+ onsite audiences).

Spatio-Temporal Data-Related Activities

Workshops

  • 2025 WWW Workshop on Spatio-Temporal Data Mining from the Web (WWW’25-WebST)
  • The International Workshop on Urban Computing (KDD’25-Urbcomp, KDD’24-Urbcomp, KDD’23-Urbcomp)

Tutorials

  • Yuxuan Liang, Siru Zhong, Xixuan Hao, Hao Miao, Yan Zhao, Qingsong Wen, Roger Zimmermann, “Multimodal Learning for Spatio-Temporal Data Mining”, Tutorial at the 33rd ACM International Conference on Multimedia (MM 2025), Dublin, Ireland, Oct. 2025.
  • Yuxuan Liang, Haomin Wen, Yutong Xia, Ming Jin, Bin Yang, Flora Salim, Qingsong Wen, Shirui Pan, Gao Cong, “Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey”, Tutorial at the 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2025), Toronto, ON, Canada, Aug. 2025.
  • Bin Yang, Yuxuan Liang, Chenjuan Guo, Christian S Jensen, “Data Driven Decision Making with Time Series and Spatio-temporal Data”, Tutorial at the 41st IEEE International Conference on Data Engineering, Hong Kong, China, May 2025.