Flex Conference (Physical / Digital)

International Conference on High-Performance Data Analytics and Scientific Modeling - (ICHPDASM-27)

4th - 5th June 2027 , Cape Town - South Africa

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Call For Papers

The (ICHPDASM-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:

  • High-performance computing for data analytics
  • Data modeling techniques for scientific research
  • Big data challenges in scientific modeling
  • Machine learning applications in data analytics
  • Real-time data processing in research
  • Visualization techniques for scientific data
  • Data management in high-performance computing
  • Collaborative tools for data analysis
  • Impact of AI on scientific modeling
  • Case studies in high-performance data analytics
  • Future trends in data-driven research
  • Ethics of data usage in science
  • Interdisciplinary approaches to data analytics
  • Data-driven decision making in research
  • Optimization techniques for data processing
  • Data sharing and collaboration in science
  • Innovative tools for scientific computing
  • Uncertainty quantification in data analysis
  • Applications of AI in scientific research
  • Challenges in high-performance data analytics

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.