International Conference on Applied Bayesian Statistics and Decision Analysis

ICABSDA

26th Nov – 27th Nov 2026 Rome, Italy

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Registration Summary

Conference ICABSDA

Date 26th Nov – 27th Nov 2026

Location Rome, Italy

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Bayesian Inference +

This track focuses on the latest methodologies and theoretical advancements in Bayesian inference. Researchers are invited to present novel approaches that enhance the understanding and application of Bayesian techniques.

SDG 4 SDG 9

02 Decision Theory and Bayesian Approaches +

This session explores the intersection of decision theory and Bayesian statistics, emphasizing frameworks for making informed decisions under uncertainty. Contributions that integrate Bayesian methods into decision-making processes are particularly welcome.

SDG 16

03 Prior Distributions: Theory and Applications +

This track delves into the formulation and application of prior distributions in Bayesian analysis. Participants are encouraged to share innovative techniques for selecting and justifying priors in various statistical models.

SDG 9 SDG 11

04 Posterior Analysis and Model Evaluation +

This session aims to discuss methods for posterior analysis and the evaluation of Bayesian models. Presentations should focus on techniques for assessing model fit and the implications of posterior distributions.

SDG 9 SDG 16

05 Markov Chain Monte Carlo Methods +

This track highlights advancements in Markov Chain Monte Carlo (MCMC) methods for Bayesian computation. Researchers are invited to present new algorithms, convergence diagnostics, and applications of MCMC in complex models.

SDG 9 SDG 17

06 Probabilistic Models in Applied Statistics +

This session focuses on the development and application of probabilistic models in various fields of applied statistics. Contributions that demonstrate the utility of these models in real-world scenarios are encouraged.

SDG 3 SDG 9

07 Uncertainty Quantification in Bayesian Frameworks +

This track addresses techniques for uncertainty quantification within Bayesian frameworks. Participants are invited to discuss methods for assessing and communicating uncertainty in statistical analyses.

SDG 13 SDG 16

08 Computational Methods in Bayesian Statistics +

This session explores computational techniques that facilitate Bayesian analysis, including software development and algorithm optimization. Contributions that enhance the efficiency and accessibility of Bayesian methods are welcome.

SDG 9 SDG 17

09 Bayesian Approaches to Statistical Modeling +

This track emphasizes the role of Bayesian methods in statistical modeling across diverse applications. Researchers are encouraged to present case studies that illustrate the effectiveness of Bayesian modeling techniques.

SDG 3 SDG 9

10 Applications of Bayesian Statistics in Industry +

This session focuses on the practical applications of Bayesian statistics in various industries, including healthcare, finance, and engineering. Participants are invited to share insights and case studies that demonstrate the impact of Bayesian methods in practice.

SDG 3 SDG 9

11 Emerging Trends in Bayesian Decision Analysis +

This track investigates emerging trends and future directions in Bayesian decision analysis. Researchers are encouraged to present innovative frameworks and applications that push the boundaries of traditional decision-making paradigms.

SDG 9 SDG 16