On-location / Digital Conference

International Conference on Machine Learning for Big Data Governance in IT (ICMLBDGIT-26)

16th - 17th Nov 2026,Jakarta Raya, Indonesia

In Association With:

Call for Paper


Important Dates


Early Bird Registration

17th Oct 2026

Paper Submission Deadline

22nd October 2026

Registration Deadline

1st November 2026

Conference Date

16th - 17th Nov 2026

Conference Updates:

"Stay updated with Science Cite Conference news."

  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Jakarta Raya ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Jakarta Raya conference.
  • Peer Review Process:
    The peer review process will begin soon for Jakarta Raya conference.
  • Networking with Global Experts:
    Join global experts at our conference in Jakarta Raya.
  • 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 ICMLBDGIT 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 Machine Learning for Big Data Governance in IT, encouraging applied research, case studies, and industry-driven innovations.

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

  • Machine learning for data governance
  • Big data compliance and regulatory issues
  • Data quality management in governance
  • Machine learning for data lineage tracking
  • Big data ethics in governance frameworks
  • Governance challenges in big data projects
  • Machine learning for risk assessment
  • Data stewardship in big data environments
  • Big data privacy regulations and compliance
  • Machine learning for data classification
  • Governance frameworks for machine learning
  • Big data transparency and accountability
  • Machine learning for data ownership issues
  • Big data governance best practices
  • Data lifecycle management in big data
  • Machine learning for data integrity
  • Big data in regulatory compliance
  • Machine learning for audit trails
  • Big data governance in healthcare
  • Future trends in data governance

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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