Time Series Analytics

I. General Description of the Session’s Scope:
The TSA session will explore theoretical advances and practical applications in sequential and temporal data analysis. It will cover both traditional approaches and recent advances in deep learning and graph-based models. Topics include forecasting, anomaly/change-point detection, imputation, classification, causal inference, and representation learning, especially under challenges such as missing data, irregular sampling, non-stationarity, and scalability. Application domains include healthcare, finance, energy, IoT, transportation, and climate science.

II. List of Relevant Topics

• Forecasting: univariate, multivariate, probabilistic, hierarchical, global models
• Transformer-based and hybrid architectures for time series
• Anomaly and change-point detection in batch and streaming data
• Missing-value imputation, irregular sampling, data augmentation
• Self-supervised and contrastive representation learning
• Causal time-series analysis, counterfactuals, uplift modeling
• Classification, clustering, segmentation, motif discovery
• Federated, privacy-preserving, and edge time-series learning
• Robustness, uncertainty quantification, and evaluation frameworks
• Applications in energy, healthcare, finance, IoT, transportation, and climate

II. Submission link: click here

III. Special Session Chairs:

• Dr. Nguyen Ngoc Phien — Ton Duc Thang University (TDTU). Email: nguyenngocphien@tdtu.edu.vn
• Dr. Tran Trung Tin — Ton Duc Thang University (TDTU). Email: trantrungtin@tdtu.edu.vn
• Dr. Duong Thi Thuy Van — Ton Duc Thang University (TDTU). Email: duongthithuyvan@tdtu.edu.vn
• Assoc. Prof. Duong Tuan Anh — HCMC University of Foreign Languages – Information Technology (HUFLIT)