Hybrid Conferencee

International Conference on Advanced Topics in Statistical Modeling and Analysis (ICATSMA - 26)

5th - 6th October 2026 | Madrid, Spain

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

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 4
SDG 4 Quality Education
SDG 8
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

Innovations in Statistical Modeling

This track focuses on the latest advancements in statistical modeling techniques, emphasizing novel approaches and methodologies. Researchers are encouraged to present their findings on innovative models that enhance data interpretation and decision-making.

Track 02

Computational Statistics and Algorithms

This session will explore the intersection of statistics and computational methods, highlighting algorithms that improve statistical analysis. Contributions that demonstrate efficient computational techniques for large datasets are particularly welcome.

Track 03

Machine Learning in Statistical Analysis

This track examines the integration of machine learning techniques within statistical frameworks. Participants are invited to discuss applications and theoretical advancements that bridge these two fields.

Track 04

Predictive Analytics and Its Applications

Focusing on predictive analytics, this session will cover methodologies that enhance forecasting accuracy across various domains. Papers that illustrate practical applications of predictive models in real-world scenarios are encouraged.

Track 05

Data Science and Statistical Methods

This track aims to highlight the role of statistical methods in the broader context of data science. Contributions that showcase the synergy between data science practices and statistical rigor are sought.

Track 06

Probabilistic Models in Modern Research

This session will delve into the development and application of probabilistic models in contemporary research. Submissions that address theoretical advancements or practical implementations are highly encouraged.

Track 07

High-Dimensional Data Analysis

This track focuses on the challenges and solutions associated with analyzing high-dimensional data. Researchers are invited to present methodologies that effectively handle the complexities of such datasets.

Track 08

Multivariate Statistical Methods

This session will explore multivariate statistical techniques and their applications across various fields. Papers that demonstrate innovative uses of multivariate analysis in real-world problems are welcome.

Track 09

Statistical Inference and Decision Making

This track examines the principles of statistical inference and their implications for decision-making processes. Contributions that provide insights into inference techniques and their practical applications are encouraged.

Track 10

Bayesian Approaches in Statistics

This session will focus on Bayesian statistical methods and their applications in various research areas. Participants are invited to discuss advancements in Bayesian inference and its relevance to contemporary statistical challenges.

Track 11

Ethics and Transparency in Statistical Research

This track addresses the ethical considerations and transparency issues in statistical research. Papers that explore best practices for ensuring integrity and reproducibility in statistical analysis are particularly welcome.