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Call for Paper

The ICBDASM emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Statistics are explored to promote cross-domain knowledge exchange and collaborative innovation.

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

01
Big data analytics techniques and tools
02
Statistical modeling for large datasets
03
Data mining and statistical methods
04
Machine learning applications in big data
05
Statistical challenges in big data
06
Predictive analytics in business intelligence
07
Big data visualization techniques
08
Statistical methods for real-time data
09
Applications of big data in healthcare
10
Big data ethics and privacy concerns
11
Statistical modeling in social media analysis
12
Big data applications in finance
13
Data quality and statistical reliability
14
Statistical methods for streaming data
15
Big data and machine learning integration
16
Statistical analysis of network data
17
Big data applications in environmental science
18
Statistical techniques for unstructured data
19
Big data in education and research
20
Future trends in big data analytics

All submissions will undergo peer review to ensure quality and interdisciplinary relevance.

Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

👉 Register Now

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.

👉 Submit Your Research Work

Event Highlights

  • Keynote sessions by experienced speakers
  • Technical paper presentations across multiple topics
  • Opportunities for academic and professional networking
  • Discussions on current research developments

Contact Us

    Have questions about submission, registration, or publication? We’re happy to help.

  • Email: [email protected]
  • Phone:+91 9940952512

We look forward to your participation and contribution to the ASPHER Conference.