Topics are interested but not limited to:

    Foundations
    Mathematical, probabilistic and statistical models and theories
    Machine learning theories, models and systems
    Knowledge discovery theories, models and systems
    Manifold and metric learning
    Deep learning
    Scalable analysis and learning
    Non-iidness learning
    Heterogeneous data/information integration
    Data pre-processing, sampling and reduction
    Dimensionality reduction
    Feature selection, transformation and construction
    Large scale optimization
    High performance computing for data analytics
    Architecture, management and process for data science

    Data analytics, machine learning and knowledge discovery
     
    Learning for streaming data
    Learning for structured and relational data
    Latent semantics and insight learning
    Mining multi-source and mixed-source information
    Mixed-type and structure data analytics
    Cross-media data analytics
    Big data visualization, modeling and analytics
    Multimedia/stream/text/visual analytics
    Relation, coupling, link and graph mining
    Personalization analytics and learning
    Web/online/social/network mining and learning
    Structure/group/community/network mining
    Cloud computing and service data analysis

    Storage, retrieval and search
     
    Data warehouses, cloud architectures
    Large-scale databases
    Information and knowledge retrieval, and semantic search
    Web/social/databases query and search
    Personalized search and recommendation
    Human-machine interaction and interfaces
    Crowdsourcing and collective intelligence