On-location / Digital Conference

International Conference on Big Data and ML-driven IT Innovation Strategies (ICBDMLITIS-26)

17th - 18th Oct 2026,Tokyo, Japan

In Association With:

Call for Paper


Important Dates


Early Bird Registration

17th Sep 2026

Paper Submission Deadline

22nd September 2026

Registration Deadline

2nd October 2026

Conference Date

17th - 18th Oct 2026

Conference Updates:

"Stay updated with Science Cite Conference news."

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

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

  • Strategies for ML-driven innovation
  • Big data analytics for business strategy
  • Case studies of innovative IT solutions
  • AI applications in strategic planning
  • Data-driven decision making in organizations
  • Impact of big data on innovation strategies
  • Challenges in implementing ML strategies
  • Future trends in IT innovation strategies
  • Collaboration between IT and business units
  • Data governance in innovation initiatives
  • Predictive analytics for market trends
  • User experience in innovative solutions
  • Ethical implications of data usage
  • Scalable solutions for business innovation
  • Machine learning for operational improvements
  • Data-driven insights for competitive advantage
  • Innovative tools for business analytics
  • Real-time analytics for strategic decisions
  • Integration of big data in business models
  • Customer engagement through data innovation

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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