- NeuRec: Advanced Neural Algorithms and Theories for Recommender Systems
- SENTIRE: Sentiment Elicitation from Natural Text for Information Retrieval and Extraction
- DMS: Data Mining for Service
- CLEATED: Continual Learning and Adaptation for Time Evolving Data
- MSDM: Multi-source data mining
- IncrLearn: Incremental classification and clustering, concept drift, novelty detection in big/fast data context
- HDM: High Dimensional Data Mining
- DMBIH: Data Mining in Biomedical Informatics and Healthcare
- LITSA: Large-scale Industrial Time Series Analysis
- UDML: Utility Driven Mining and Learning
- MLLD: Mining and Learning in the Legal Domain
- DLC: Deep learning and clustering
- SSTDM: Spatial and Spatio-Temporal Data Mining
- BSDM: Blockchain Systems for Decentralized Mining
- EDMML: Evolutionary Data Mining and Machine Learning
- SDM: Social Data Mining in the Post-pandemic Era
- OEDM: Optimization Based Techniques for Emerging Data Mining Problems
- IAAA: Intelligence-Augmented Anomaly Analytics
- SFE-TSDM: Systematic Feature Engineering for Time-Series Data Mining (SFE-TSDM)
- WAIN: Workshop on AI for Nudging
- DMC: Data Mining and Machine Learning in Cybersecurity
