On-location / Digital Conference

International Conference on Big Data-driven Machine Learning for IT Optimization (ICBDMLITO-27)

24th - 25th Mar 2027,Nice, France

In Association With:

Call for Paper


Important Dates


Early Bird Registration

22nd Feb 2027

Paper Submission Deadline

27th February 2027

Registration Deadline

9th March 2027

Conference Date

24th - 25th Mar 2027

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Nice ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Nice conference.
  • Peer Review Process:
    The peer review process will begin soon for Nice conference.
  • Networking with Global Experts:
    Join global experts at our conference in Nice.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICBDMLITO bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Big Data-driven Machine Learning for IT Optimization, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Big data-driven optimization techniques
  • Machine learning for operational efficiency
  • Data analytics for IT optimization
  • Big data applications in performance tuning
  • Machine learning for resource allocation
  • Big data insights for decision making
  • Optimization strategies using big data
  • Machine learning for cost reduction
  • Big data in supply chain optimization
  • Real-time analytics for IT performance
  • Big data visualization for optimization
  • Machine learning for predictive analytics
  • Big data in customer experience enhancement
  • Optimization of IT infrastructure with ML
  • Big data applications in marketing strategies
  • Machine learning for process improvement
  • Big data-driven business model innovation
  • Data quality for optimization processes
  • Machine learning for competitive advantage
  • Future directions in big data optimization

Assessment

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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