On-location / Digital Conference

International Conference on Bayesian Modeling and Inference in Statistics (ICBMIS-26)

10th - 11th Aug 2026,Biskra, Algeria

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Call for Paper


Important Dates


Early Bird Registration

11th Jul 2026

Paper Submission Deadline

21st Jul 2026

Registration Deadline

26th Jul 2026

Conference Date

10th - 11th Aug 2026

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Call For Papers

The ICBMIS bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Bayesian Modeling and Inference in Statistics, encouraging applied research, case studies, and industry-driven innovations.

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

  • Bayesian modeling techniques in statistics
  • Applications of Bayesian inference in research
  • Bayesian methods for hierarchical models
  • Statistical challenges in Bayesian analysis
  • Bayesian approaches to causal inference
  • Computational methods for Bayesian statistics
  • Bayesian statistics in clinical trials
  • Machine learning and Bayesian methods integration
  • Bayesian modeling of time series data
  • Statistical software for Bayesian analysis
  • Bayesian methods for missing data
  • Bayesian networks in statistical modeling
  • Applications of Bayesian methods in epidemiology
  • Bayesian approaches to meta-analysis
  • Statistical education in Bayesian statistics
  • Future trends in Bayesian research
  • Bayesian methods for spatial data analysis
  • Bayesian statistics in environmental studies
  • Ethics in Bayesian statistical research
  • Bayesian methods for decision making

Assessment

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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