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:


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.

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
SDG 12 — Responsible Consumption and Production
SDG 16 — Peace, Justice and Strong Institutions
Session Tracks
Track 01
Innovative Applications of Big Data in Engineering

This track explores the transformative applications of big data within engineering disciplines. It focuses on case studies and methodologies that leverage big data for enhanced decision-making and operational efficiency.

Track 02
Machine Learning Techniques for Predictive Analytics

This session delves into advanced machine learning algorithms and their applications in predictive analytics. Participants will discuss the effectiveness of various models in forecasting trends and optimizing processes.

Track 03
Cloud Computing Solutions for Scalable IT Infrastructure

This track examines the role of cloud computing in developing scalable IT infrastructures. It highlights innovative strategies for leveraging cloud technologies to enhance data storage, processing, and accessibility.

Track 04
Intelligent Systems and Automation in Engineering

This session focuses on the integration of intelligent systems and automation in engineering practices. It aims to showcase advancements that improve efficiency, accuracy, and safety in engineering operations.

Track 05
Data Analytics Frameworks for Business Intelligence

This track investigates various data analytics frameworks that support business intelligence initiatives. Participants will explore how these frameworks can be utilized to derive actionable insights from large datasets.

Track 06
AI Algorithms for Enhanced Decision-Making

This session highlights the application of artificial intelligence algorithms in decision-making processes. It emphasizes the importance of AI in improving the quality and speed of engineering decisions.

Track 07
System Optimization Techniques in IT Infrastructure

This track focuses on innovative techniques for optimizing IT infrastructure systems. Discussions will center on methodologies that enhance performance, reduce costs, and improve reliability.

Track 08
Big Data Analytics in Smart Manufacturing

This session explores the application of big data analytics in the context of smart manufacturing. It aims to highlight how data-driven insights can lead to improved production processes and product quality.

Track 09
Challenges and Solutions in Machine Learning Deployment

This track addresses the challenges faced during the deployment of machine learning models in real-world applications. Participants will discuss best practices and innovative solutions to overcome these obstacles.

Track 10
Data-Driven Strategies for IT Innovation

This session examines how data-driven strategies can foster innovation in IT. It focuses on the intersection of data analytics and IT development to drive forward-thinking solutions.

Track 11
Future Trends in Big Data and Machine Learning

This track looks ahead to future trends in big data and machine learning technologies. Participants will explore emerging technologies and their potential impact on engineering and IT innovation.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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