ICDM'25 Workshop




AI4TS: AI for Time Series


Analysis:




Theory, Algorithms, and Applications


Time series data are becoming ubiquitous in numerous real-world applications, e.g., IoT devices, healthcare, wearable devices, smart vehicles, financial markets, biological sciences, environmental sciences, etc. Given the availability of massive amounts of data, their complex underlying structures/distributions, together with the high-performance computing platforms, there is a great demand for developing new theories and algorithms to tackle fundamental challenges (e.g., representation, classification, prediction, causal analysis, etc.) in various types of applications.

The goal of this workshop is to provide a platform for researchers and AI practitioners from both academia and industry to discuss potential research directions, key technical issues, and present solutions to tackle related challenges in practical applications. The workshop will focus on both the oretical and practical aspects of time series data analysis and aims to trigger research innovations in theories, algorithms, and applications. We will invite researchers and AI practitioners from the related areas of machine learning, data science, statistics, econometrics, and many others to contribute to this workshop.

This workshop encourages submissions of innovative solutions for a broad range of time series analysis problems. Topics of interest include but are not limited to the following:

  • Time series forecasting and prediction
  • Spatio-temporal forecasting and prediction
  • Time series anomaly detection and diagnosis
  • Time series change point detection
  • Time series classification and clustering
  • Time series similarity search
  • Time series indexing
  • Time series compression
  • Time series pattern discovery
  • Interpretation and explanation in time series
  • Causal inference in time series
  • Bias and fairness in time series
  • Federated learning and security in time series
  • Benchmarks, experimental evaluation, and comparison for time series analysis tasks
  • Time series applications in various areas: E-commerce, Cloud computing, Transportation, Fintech, Healthcare, Internet of things, Wireless networks, Predictive maintenance, Energy, and Climate, etc.

Call for Papers

Contact with us: ai4ts.ijcai@gmail.com

We will assign 3 reviewers to each paper submission, and a meta-reviewer will be assigned to make the final decision.

Authors of accepted papers will be invited to give a 10-minute oral presentation (8 minutes presenttions + 2 minutes Q&A). All accepted papers will be invited to give poster presentations during the poster session.

Submission link: Submission Link

Submissions should be 4-8 pages long, including references, and follow ICDM-25 template. Additional pages (up to 2) may be purchased if needed. The review process is single-round and double-blind (submission files have to be anonymized). Accepted papers will be included in the ICDM Workshop Proceedings (separate from ICDM Main Conference Proceedings), and each workshop paper requires a full registration. Meanwhile, duplicate submissions of the same paper to more than one ICDM workshop are forbidden.

Any questions may be directed to the workshop e-mail address: Contact Us

Key Dates

 

Workshop Paper Submission Due Date: Aug 29, 2025

Notification of Paper Acceptance: Sep 15, 2025

Camera-ready Papers Due: TBD

Date:Nov 12nd, 2025

Schedule

 

Workshop Organizers

 

Yifeng Gao

Assistant Professor
University of Texas Rio Grande Valley.

 

Dongjin Song

Assistant Professor, University of Connecticut

 

Jingchao Ni

Assistant Professor, University of Houston

 
 
 
 

Mucun Sun

Power System Research Engineer, Idaho National Lab