Hybrid Conferencee

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

29th - 30th July 2026 | Rome, Italy
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Conference Brochure
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Conference Notifications:

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

Call for Paper

The ICBMIS 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 Statistics,Data Science, 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
Bayesian modeling techniques in statistics
02
Applications of Bayesian inference in research
03
Bayesian methods for hierarchical models
04
Statistical challenges in Bayesian analysis
05
Bayesian approaches to causal inference
06
Computational methods for Bayesian statistics
07
Bayesian statistics in clinical trials
08
Machine learning and Bayesian methods integration
09
Bayesian modeling of time series data
10
Statistical software for Bayesian analysis
11
Bayesian methods for missing data
12
Bayesian networks in statistical modeling
13
Applications of Bayesian methods in epidemiology
14
Bayesian approaches to meta-analysis
15
Statistical education in Bayesian statistics
16
Future trends in Bayesian research
17
Bayesian methods for spatial data analysis
18
Bayesian statistics in environmental studies
19
Ethics in Bayesian statistical research
20
Bayesian methods for decision making