Hybrid Conferencee

International Conference on Bayesian Networks and Decision Analysis (ICBNDA - 26)

31st - 1st January 2027 | Dallas, USA

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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 Dallas. 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 Dallas 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 Dallas conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Dallas, 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 Dallas."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICBNDA 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 Probability Theory,Statistics, 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 networks for decision support
02
Applications of Bayesian decision analysis
03
Modeling uncertainty with Bayesian methods
04
Bayesian inference in complex systems
05
Decision-making under uncertainty frameworks
06
Bayesian approaches to risk assessment
07
Graphical models in Bayesian analysis
08
Dynamic Bayesian networks applications
09
Comparative studies of Bayesian methods
10
Integration of prior knowledge in analysis
11
Bayesian methods in machine learning
12
Statistical challenges in Bayesian networks
13
Real-world applications of Bayesian analysis
14
Bayesian decision theory in healthcare
15
Bayesian optimization techniques
16
Hierarchical models in decision analysis
17
Bayesian methods for big data
18
Ethical implications of Bayesian decisions
19
Future directions in Bayesian research
20
Collaborative decision-making using Bayesian models