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International Conference on Applied Machine Learning for Scientific Applications - (ICAML-SA-27)

13th - 14th January 2027 , Abidjan - Ivory Coast

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Call For Papers

The (ICAML-SA-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 Computational Science, 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:

  • Applied machine learning in scientific fields
  • Case studies of ML in scientific research
  • Real-world applications of machine learning
  • Machine learning for experimental data analysis
  • AI techniques for scientific modeling
  • Data-driven decision-making in science
  • Machine learning for predictive maintenance
  • Applications of ML in environmental science
  • Machine learning in social science research
  • AI for optimizing scientific workflows
  • Challenges in applying ML to science
  • Ethics of machine learning applications
  • Machine learning for data-driven discoveries
  • AI in computational biology applications
  • Interdisciplinary approaches to applied ML
  • Machine learning for sensor data analysis
  • AI for enhancing research reproducibility
  • Future trends in applied machine learning
  • Collaborative research using machine learning
  • Machine learning for scientific visualization

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.

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