Flex Conference (Physical / Digital)

International Conference on Data Analytics and Predictive Modeling Techniques - (ICDAPMT-26)

17th - 18th November 2026 , Hamburg - Germany

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Call For Papers

The (ICDAPMT-26) 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,Data Science 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:

  • Predictive modeling techniques in analytics
  • Data analytics for business intelligence
  • Statistical methods for predictive analytics
  • Machine learning in predictive modeling
  • Big data analytics for decision making
  • Predictive analytics in healthcare
  • Data visualization for predictive insights
  • Statistical modeling for customer behavior
  • Predictive analytics in marketing strategies
  • Data-driven approaches to risk management
  • Predictive modeling for financial forecasting
  • Real-time predictive analytics applications
  • Ethics in predictive modeling practices
  • Statistical techniques for anomaly detection
  • Data analytics for operational efficiency
  • Predictive analytics in social sciences
  • Integrating predictive modeling with AI
  • Future trends in predictive analytics
  • Statistical learning for predictive insights
  • Applications of predictive modeling in industry

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.