This track focuses on the latest developments in applied mathematics, emphasizing innovative mathematical methods and their practical applications. Participants are encouraged to present research that bridges theoretical concepts with real-world problems.

This session aims to explore various numerical modelling techniques used in engineering and scientific research. Contributions should highlight the effectiveness and applicability of these methods in solving complex problems.

This track invites discussions on mathematical modelling approaches specifically tailored for engineering applications. Papers should demonstrate how mathematical frameworks can enhance the understanding and design of engineering systems.

This session will cover the intersection of data science and statistical methodologies, focusing on innovative techniques for data analysis. Researchers are encouraged to share insights on how statistical tools can inform decision-making in various fields.

This track highlights the role of computational science in simulating complex systems across different domains. Contributions should emphasize the computational techniques employed and their implications for scientific discovery.

This session addresses the critical aspects of model validation and verification in applied mathematics and engineering. Participants are invited to present methodologies and case studies that demonstrate the reliability of their models.

This track focuses on novel numerical methods that enhance computational efficiency and accuracy. Researchers are encouraged to present their findings on new algorithms and their applications in solving mathematical problems.

This session explores the interdisciplinary applications of applied mathematics in fields such as biology, finance, and environmental science. Papers should illustrate how mathematical techniques can address challenges in diverse domains.

This track investigates the integration of machine learning techniques with mathematical modelling. Contributions should focus on how these combined approaches can lead to improved predictive capabilities and insights.

This session emphasizes statistical learning techniques and their application in data analysis. Researchers are invited to share their work on methodologies that enhance the interpretation of complex datasets.

This track is dedicated to computational techniques that are pivotal in applied sciences. Participants should present research that showcases the synergy between computational methods and scientific inquiry.