The DSAA’2023 Research Track solicits high-quality, original papers presenting novel issues s of Data Science and Advanced Analytics across various disciplines and domains, including business, government, health and medical science, physical sciences, and social sciences.

Topics of interests include but are not limited to:

    Data science foundations and theories
    Mathematics and statistics for data science and analytics
    Understanding data characteristics and complexities
    Machine/deep/statistical learning-based algorithms
    Advanced analytics and knowledge discovery methods
    Computer vision and pattern recognition
    Optimization theories and methods
    Large-scale databases, big-data processing, distributed processing, and ethical analytics
    Model explainability and provenance
    Theories and methods for evaluation, explanation, visualization, and presentation
    Survey and review

Submissions for the DSAA’2023 Research Track should very clearly specify the problem being solved, what methodologies were used to solve the problem, what data was used, how the results were evaluated, and how the solution is being used. Applying new data science methods to public data or data downloaded from competition sites (such as Kaggle), without a real problem (and problem owner) will not be accepted in this track.