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Hybrid Event

17th - 18th October 2026 | Montreal, Canada

International Conference on Scalable Machine Learning for Big Data in IT (ICSMLBDIT - 26)

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4

Days

4

Hrs

07

Min

02

Sec

Call For Paper

The (ICSMLBDIT) is dedicated to advancing research excellence by bringing together leading scholars, scientists, and professionals from across the globe. It provides a platform for the dissemination of high-quality research and innovative methodologies.

With a strong focus on Big Data,Machine Learning,Information Technology, the conference promotes research that contributes to academic depth, practical insights, and interdisciplinary knowledge integration.

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

01
Scalable machine learning algorithms
02
Big data challenges in scalability
03
Distributed machine learning techniques
04
Real-time big data processing frameworks
05
Machine learning for large datasets
06
Big data analytics for IT scalability
07
Cloud computing and machine learning integration
08
Scalable architectures for data processing
09
Machine learning for resource optimization
10
Big data in edge computing environments
11
Applications of big data in IoT
12
Machine learning for performance tuning
13
Big data storage solutions for scalability
14
Federated learning for big data applications
15
Scalable data pipelines for ML
16
Machine learning for network optimization
17
Big data visualization for scalability
18
Machine learning for operational analytics
19
Big data governance in scalable systems
20
Future trends in scalable machine learning

Peer Review Process

All submissions evaluated through structured peer-review to ensure academic rigor. Accepted papers may be considered for high-quality journals.

Registration Details

Secure your participation early. Limited slots are allocated on a first-come, first-served basis.

Publication Opportunities

High-quality submissions prioritized for publication in recognized journals and proceedings.

Submit Your Paper Today Register Early
2026 UPDATE

Consistent Academic Support

Science Net ensures that research activities continue without interruption in the current global situation. Participants can engage through digital and hybrid conference formats.