Call for papers:

Background:

Applied mathematics and statistics serve as the backbone of modern scientific inquiry and technological innovation. These disciplines provide the essential frameworks for analyzing uncertainty, modeling dynamic systems, and deriving insights from data that guide evidence-based decision-making. In today’s data-driven world, industries such as healthcare, finance, engineering, and cybersecurity rely heavily on applied mathematical and statistical methods to optimize performance and predict outcomes. The increasing complexity of global challenges demands professionals who can translate theoretical concepts into actionable solutions through quantitative reasoning. This symposium on Applied Mathematics and Statistics is designed to bridge the gap between abstract theory and practical application, enabling participants to harness mathematical modeling and statistical analysis to address real-world problems effectively. Through engaging discussions and hands-on exercises, attendees will strengthen their analytical foundation and gain confidence in applying these tools to diverse professional and research contexts.

Goal/Rationale:

The primary goal of this symposium is to address the growing need for professionals who can effectively apply mathematical and statistical principles to analyze complex, data-rich environments. In an era dominated by big data and artificial intelligence, many organizations struggle to extract meaningful insights from the massive amounts of information they collect. This challenge arises from a gap between theoretical understanding and practical implementation of mathematical and statistical methods. The symposium seeks to bridge this gap by providing participants with the tools and methodologies needed to model, analyze, and interpret real-world phenomena. It will focus on leveraging recent advances in computational statistics, data visualization, and machine learning to enhance accuracy and predictive power. By integrating theory with hands-on practice using software tools such as Python, R, and MATLAB, participants will learn to design models, evaluate uncertainty, and make data-driven decisions. Ultimately, this symposium empowers attendees to transform mathematical reasoning into actionable solutions that support innovation and evidence-based problem-solving across industries.

Scope and Information for Participants:

The Applied Mathematics and Statistics symposium encompasses a broad range of interdisciplinary applications where quantitative analysis drives innovation and informed decision-making. Participants will explore key themes such as mathematical modeling, statistical inference, probability theory, regression and correlation analysis, optimization techniques, and data visualization. The symposium will also highlight the integration of computational tools—including Python, R, and MATLAB—for implementing statistical models and analyzing large datasets efficiently. Contributors are encouraged to address emerging topics such as machine learning algorithms, stochastic modeling, uncertainty quantification, and predictive analytics in real-world contexts. The scope further extends to exploring ethical data use, reproducibility in research, and the role of mathematical reasoning in scientific discovery. Through lectures, demonstrations, and collaborative exercises, participants will gain both theoretical understanding and practical experience, enabling them to apply mathematical and statistical approaches effectively across academia, research, and industry.

Topics:

The main topics of this symposium are listed below.

Mathematics and Applied Mathematics

Meanwhile, submissions aligned with the overall conference theme are also welcome.

Computing Innovations

Applied Physics

Theoretical Physics