International Conference on Scalable Machine Learning for Big Data in IT
(ICSMLBDIT - 26)

7th - 8th August 2026 Budapest, Hungary (Hybrid Event)

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Call for Paper

The ICSMLBDIT is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Big Data,Machine Learning,Information Technology, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Scalable machine learning algorithms
  • Big data challenges in scalability
  • Distributed machine learning techniques
  • Real-time big data processing frameworks
  • Machine learning for large datasets
  • Big data analytics for IT scalability
  • Cloud computing and machine learning integration
  • Scalable architectures for data processing
  • Machine learning for resource optimization
  • Big data in edge computing environments
  • Applications of big data in IoT
  • Machine learning for performance tuning
  • Big data storage solutions for scalability
  • Federated learning for big data applications
  • Scalable data pipelines for ML
  • Machine learning for network optimization
  • Big data visualization for scalability
  • Machine learning for operational analytics
  • Big data governance in scalable systems
  • Future trends in scalable machine learning
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

Sponsored & Indexed by

Advancing Research Stability

SNRI maintains uninterrupted academic processes in the current global situation. Participants can engage and publish through online and blended conference formats.

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