SNRI

(ICMLITIBD - 26) | Hybrid Event
16th - 17th November 2026 | Milan, Italy

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International Conference on Machine Learning for IT Infrastructure and Big Data
(ICMLITIBD - 26)

16th - 17th November 2026 Milan, Italy (Hybrid Event)

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Call for Paper

The ICMLITIBD 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:

  • Machine learning algorithms for big data
  • Infrastructure challenges in machine learning
  • Big data processing frameworks comparison
  • Scalable machine learning techniques
  • Machine learning for data-driven IT solutions
  • Optimizing IT infrastructure with ML
  • Real-time analytics using machine learning
  • Machine learning in cloud environments
  • Data preprocessing for machine learning models
  • Ethical considerations in machine learning
  • Machine learning for IT service optimization
  • Big data analytics in machine learning
  • Applications of deep learning in IT
  • Machine learning model evaluation techniques
  • Big data storage solutions for ML
  • Federated learning in big data contexts
  • Transfer learning for big data applications
  • Machine learning for anomaly detection
  • Big data governance in machine learning
  • Future directions in ML for IT
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.

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