International Conference on Machine Learning and Big Data in IT Service Management

ICMLBDITSM

23rd Jan – 24th Jan 2027 Bali, Indonesia

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Registration Summary

Conference ICMLBDITSM

Date 23rd Jan – 24th Jan 2027

Location Bali, Indonesia

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

Calculated based on 5.8% of the registration fee

Discount USD 0.00

Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Machine Learning Algorithms +

This track focuses on the latest developments in machine learning algorithms that enhance data processing capabilities. Researchers are invited to present innovative approaches that improve predictive analytics in IT service management.

SDG 9 SDG 4

02 Big Data Analytics in IT Service Management +

This session explores the role of big data analytics in optimizing IT service management processes. Contributions should highlight case studies and frameworks that demonstrate effective data integration and analysis.

SDG 9 SDG 12

03 Intelligent Systems for IT Infrastructure +

This track examines the implementation of intelligent systems in managing IT infrastructure. Papers should address the integration of AI algorithms to enhance system performance and automation.

SDG 9 SDG 11

04 Cloud Computing and Big Data Solutions +

This session focuses on the intersection of cloud computing and big data technologies. Authors are encouraged to discuss scalable solutions that leverage cloud resources for enhanced data analytics.

SDG 9 SDG 12

05 Performance Monitoring and Optimization Techniques +

This track delves into methodologies for performance monitoring and optimization in IT services. Submissions should present novel techniques that utilize machine learning for real-time performance enhancement.

SDG 9 SDG 12

06 Data Processing Frameworks for IT Services +

This session invites papers on innovative data processing frameworks tailored for IT service management. Contributions should emphasize efficiency and effectiveness in handling large datasets.

SDG 9 SDG 12

07 Automation in IT Service Management +

This track explores the role of automation in streamlining IT service management processes. Researchers are encouraged to present solutions that utilize machine learning to enhance operational efficiency.

SDG 9 SDG 12

08 Business Intelligence and Predictive Analytics +

This session focuses on the integration of business intelligence tools with predictive analytics in IT service management. Papers should discuss methodologies that facilitate data-driven decision-making.

SDG 9 SDG 12

09 Data Integration Techniques for Enhanced Analytics +

This track examines advanced data integration techniques that support comprehensive analytics in IT services. Contributions should highlight innovative approaches to unify disparate data sources.

SDG 9 SDG 12

10 AI-Driven Solutions for IT Challenges +

This session invites discussions on AI-driven solutions addressing contemporary challenges in IT service management. Researchers should present case studies that illustrate the practical application of AI technologies.

SDG 9 SDG 12

11 Future Trends in Machine Learning and Big Data +

This track explores emerging trends and future directions in machine learning and big data within the context of IT service management. Authors are encouraged to speculate on the impact of these trends on industry practices.

SDG 9 SDG 12