Hybrid Conferencee

International Conference on Big Data and Machine Learning in IT Infrastructure Management (ICBDMLITIM - 26)

21st - 22nd November 2026 | Chelyabinsk, Russian Federation

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Chelyabinsk. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Chelyabinsk event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Chelyabinsk conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Chelyabinsk, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Chelyabinsk."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

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
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
SDG 11
SDG 11 Sustainable Cities and Communities
Track 01

Advancements in Big Data Analytics

This track focuses on the latest methodologies and technologies in big data analytics. It aims to explore innovative approaches to data processing and visualization that enhance decision-making in IT infrastructure management.

Track 02

Machine Learning Applications in IT Infrastructure

This session will delve into the application of machine learning techniques to optimize IT infrastructure management. Participants will discuss case studies and frameworks that demonstrate the effectiveness of AI algorithms in real-world scenarios.

Track 03

Predictive Analytics for Infrastructure Optimization

This track emphasizes the role of predictive analytics in forecasting infrastructure needs and performance. It will cover models and tools that leverage historical data to improve resource allocation and system reliability.

Track 04

Intelligent Systems for IT Management

This session explores the development and implementation of intelligent systems in IT infrastructure management. Discussions will focus on how these systems can automate processes and enhance operational efficiency.

Track 05

Cloud Computing and Big Data Integration

This track examines the synergy between cloud computing and big data technologies. It will highlight strategies for integrating these domains to improve scalability and flexibility in IT infrastructure.

Track 06

AI Algorithms in Data Processing

This session will investigate the role of artificial intelligence algorithms in enhancing data processing capabilities. Participants will share insights on algorithmic advancements that facilitate faster and more accurate data analysis.

Track 07

Frameworks for Scalable Computing

This track focuses on the design and implementation of frameworks that support scalable computing in big data environments. It aims to address challenges and solutions related to performance and resource management.

Track 08

Automation in IT Infrastructure Management

This session will explore the impact of automation technologies on IT infrastructure management. Discussions will include tools and techniques that streamline operations and reduce human intervention.

Track 09

Data Integration Techniques for Business Intelligence

This track will cover advanced data integration techniques that enhance business intelligence capabilities. Participants will discuss best practices for consolidating data from diverse sources to support informed decision-making.

Track 10

System Optimization Strategies Using Machine Learning

This session will focus on strategies for optimizing IT systems through machine learning techniques. Case studies will illustrate how these strategies can lead to improved performance and reduced costs.

Track 11

Emerging Trends in Big Data and Machine Learning

This track will highlight emerging trends and future directions in the fields of big data and machine learning. Participants will engage in discussions on the implications of these trends for IT infrastructure management.