Flex Conference (Physical / Digital)

International Conference on Data-Driven Statistical Modeling and Analysis - (ICDDSMA-27)

29th - 30th March 2027 , Toulouse - France

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Call For Papers

The (ICDDSMA-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Statistics are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Data-driven approaches in statistical modeling
  • Machine learning techniques for data analysis
  • Predictive modeling in various fields
  • Statistical challenges in data-driven analysis
  • Applications of data-driven methods in finance
  • Big data analytics and statistical modeling
  • Causal inference in data-driven research
  • Statistical software for data-driven analysis
  • Data mining techniques for statistical insights
  • Ethics in data-driven statistical research
  • Statistical modeling in healthcare data
  • Data-driven decision making in business
  • Time series forecasting using statistical models
  • Applications of AI in statistical analysis
  • Statistical power in data-driven studies
  • Meta-analysis of data-driven findings
  • Data visualization in statistical modeling
  • Collaborative approaches to data-driven research
  • Future trends in data-driven statistics
  • Integrating qualitative data in analysis

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.