Flex Conference (Physical / Digital)

International Conference on Data-Intensive Scientific Computing and Simulation - (ICDISCS-26)

8th - 9th October 2026 , Paris - France

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Call For Papers

The (ICDISCS-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 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:

  • Data-intensive computing in scientific research
  • Simulation techniques for large datasets
  • High-performance computing for simulations
  • Data management in scientific computing
  • Parallel computing for data analysis
  • Big data challenges in scientific modeling
  • Integration of simulation and data analytics
  • Real-time data processing in simulations
  • Visualization of simulation results
  • Machine learning for data-intensive applications
  • Case studies in data-intensive computing
  • Cloud computing for scientific simulations
  • Data-driven approaches in scientific inquiry
  • Impact of AI on scientific simulations
  • Uncertainty quantification in simulations
  • Data sharing and collaboration in science
  • Innovative tools for scientific computing
  • Future directions in data-intensive research
  • Ethics of data usage in science
  • Interdisciplinary approaches to data-intensive science

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.