Hybrid Conferencee

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

7th - 8th July 2026 | Geneva, Switzerland
Sample Abstract
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Conference Brochure
Sample Full Paper
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Conference Notifications:

"Be sure to check this section regularly for all Research Plus International Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Geneva. 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 Geneva 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 Geneva conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Geneva, 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 Geneva."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICSMLBDIT aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Big Data,Machine Learning,Information Technology, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

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