Call for paper to PAKDD 2026

Theoretical Foundations: Generative AI, quantum ML, neuro-symbolic methods and reasoning, causal reasoning, non-IID learning, OOD generalization, representation learning, mathematical and statistical foundations, information theoretic approaches, optimization method, Theoretical foundations for fairness, trustworthy AI, safety, model explainability, and XAI
Learning Methods and Algorithms
– Clustering, classification, pattern mining and association rules discovery
– Supervised learning, semi-supervised learning, few-shot and zero-shot learning, active learning
– Reinforcement learning and bandits
– Transfer learning, federated learning
– Anomaly detection, outlier detection
– Learning in recommendation engines
– Learning in streams and in time series
– Learning on structured data, images, texts and multi-modal data
– Online learning, model adaption
– Graph mining and Graph NNs
– Trustworthy Machine Learning
– Fairness
– Data Proces

Data Processing for Learning
– Dimensionality reduction, feature extraction, subspace construction
– Data cleaning and preparation, data integration and summarization
– Learning in real-time
– Big data technologies
– Information retrieval
– Data/entity/event/relationship extraction
– User interfaces and visual analytics

Security, Privacy, Ethics, Information Integrity and Social Issues
– Modeling credibility, trustworthiness, and reliability
– Privacy-preserving data mining and privacy models
– Model transparency, interpretability, and fairness
– Misinformation detection, monitoring, and prevention
– Social issues, such as health inequities, social development, and poverty

Interdisciplinary Research on Data Science Applications
– Social network/media analysis and dynamics, reputation, influence, trust, opinion mining, sentiment analysis, link prediction, and community detection
– Symbiotic human-AI interaction, human-agent collaboration, socially interactive robots, and affective computing
– Internet of Things, logistics management, network traffic and log analysis, and supply chain management
– Business and financial data, computational advertising, customer relationship management, intrusion and fraud detection, and intelligent assistants
– Urban computing, spatial data science and pervasive computing
– Medical and public health applications, drug discovery, healthcare management, and epidemic monitoring and prevention
– Methods for detecting and combating spamming, trolling, aggression, toxic online behaviors, bullying, hate speech, and low-quality and offensive content
– Climate, ecological, and environmental science, and resilience and sustainability
– Astronomy and astrophysics, genomics and bioinformatics, high energy physics, robotics, AI-assisted programming, and scientific data