Flex Conference (Physical / Digital)

International Conference on Data-Driven Numerical Methods - (ICDDNM-27)

18th - 19th May 2027 , Linz - Austria

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Call For Papers

The (ICDDNM-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 Numerical Methods 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 numerical methods
  • Machine learning applications in numerical analysis
  • Numerical methods for big data problems
  • Adaptive algorithms for data-driven simulations
  • Statistical methods in numerical modeling
  • Data assimilation techniques in numerical methods
  • Numerical optimization using data-driven techniques
  • Uncertainty quantification in data-driven models
  • High-dimensional data and numerical methods
  • Parallel computing for data-driven simulations
  • Real-time data processing in numerical analysis
  • Data-driven error analysis in numerical methods
  • Numerical methods for nonlinear data-driven problems
  • Integration of AI in numerical simulations
  • Data-driven approaches to PDEs
  • Visualization techniques for numerical data
  • Data-driven model reduction techniques
  • Numerical methods for dynamic data sets
  • Applications of data-driven methods in engineering
  • Future trends in data-driven numerical methods

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.