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:
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 up to 10 pages long, including references, and follow ICDM-25 template. 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
Workshop Paper Submission Due Date:Aug 29th, 2025(AoE) Sept 1st, 2025(AoE)
Notification of Paper Acceptance: Sep 19, 2025
Camera-ready Papers Due: Sep 25, 2025
Date:Nov 12nd, 2025
| Time | Title |
|---|---|
| 8:30 - 9:00 am | Poster Setup |
| 9:00 - 9:15 am | Opening Remark |
| 9:15 am - 9:30 am | Deep Distance Measurement Method for Unsupervised Multivariate Time Series Similarity Retrieval |
| 9:30 am - 9:45 am | An Integrated Survey on Physics-Informed, Neuron-Symbolic, Temporal Foundation Models and Reinforcement Learning for Physical Time Series Analysis |
| 9:45 am - 10:00 am | TS-CausalNN: Learning Temporal Causal Relations from Non-linear Non-stationary Time Series Data |
| 10:00 am - 10:30 am | Coffee Break |
| 10:30 am - 11:15 am | Dr. Shuochao Yao, George Mason University |
| 11:15 am - 12:30 am | Poster Session |
| 12:30 pm - 13:30 pm | Lunch Break |
| 13:30 pm - 13:45 pm | Disentangling Time and Space: An Information-Theoretic Framework for Evaluating Spatio-Temporal Prediction |
| 13:45 pm - 14:00 pm | Forecasting Source Stability in Scientific Experiments using Temporal Learning Models: A Case Study from Tritium Monitoring |
| 14:00 pm - 14:15 pm | Rockfall Forecasting using Ensemble Deep Learning and Temporal Gradient-Based Explanation |
| 14:15 pm - 14:30 pm | Dynamic Graph Forecasting for Interacting Moving Objects via Multiplicative Interaction Networks |
| 14:30 pm - 14:45 pm | Classification of Variable Stars using Convolutional Neural Network |
| 14:45 pm - 15:15 pm | Poster Session |
| 15:15 pm - 16:00 pm | Dr. Panagiotis Papapetrou, Stockholm University |
| 16:00 pm - 16:30 pm | Coffee Break |
| 16:30 pm - 17:15 pm | Dr. Rex Ying, Yale University |
| 17:15 pm - 17:30 pm | Closing Mark |