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International Conference on Mathematic, Statistics and Applied Science - (ICMASTAS-27)

24th - 25th March 2027 , Philadelphia - USA

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Call For Papers

The (ICMASTAS-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 Mathematics, 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:

  • Statistical methods in scientific research
  • Applications of mathematics in industry
  • Data analysis techniques for decision making
  • Mathematics in public health and epidemiology
  • Statistical modeling and inference techniques
  • Mathematics education: challenges and innovations
  • Role of statistics in social sciences
  • Mathematics in environmental studies
  • Computational statistics and data science
  • Mathematical approaches to optimization problems
  • Statistics in business and economics
  • Mathematics for technology and engineering
  • Interdisciplinary research in mathematics and statistics
  • Ethics in statistical research practices
  • Mathematics in artificial intelligence applications
  • Future trends in statistics and applied mathematics
  • Mathematics for sustainable development goals
  • Statistical quality control in manufacturing
  • Case studies in applied statistics
  • Mathematics and statistics in education technology

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.