DSAA 2024 : IEEE 11th International Conference on Data Science and Advanced Analytics

The DSAA’2024 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.

Research Track

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.

Applications Track

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

Submissions are expected to address problems on real-life data and the results can ideally be reproducible through a public git repository. Furthermore, submitted papers are expected to provide interesting, insightful results to policy-makers, end-users, or practitioners of Data Science and Advanced Analytics or to highlight new challenges for researchers motivated by the specific needs and characteristics of application areas.

Topics of interests include but are not limited to:

Domain-specific data science and analytics practice, including business analytics, health/medical analytics, financial analytics, environmental analytics and analytics in scientific domains such as physics, astronomy, chemistry, biology and material science
Government analytics and enterprise analytics
Cloud, crowd, online, mobile and distributed data analytics
Business, economic, environmental, social impact modeling
Real-world applications, case studies and demonstrations
Operationalizable infrastructures, platforms, and tools
Deployment, management and policy-making
Ethics, social issues, privacy, trust, fairness and bias
Reflections and lessons for better data/analytics practices

Submissions for the DSAA’2024 Applications 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 (ideally in production). 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.