This track focuses on the latest advancements in optimization methodologies, including both theoretical and practical aspects. Researchers are encouraged to present innovative algorithms and frameworks that enhance optimization processes in various applied fields.

This session explores the role of control systems in engineering, emphasizing their application in real-world scenarios. Contributions that demonstrate the integration of control theory with engineering practices are particularly welcome.

This track invites discussions on the development and application of mathematical models to solve complex problems in applied sciences. Papers should highlight the significance of modeling in understanding and predicting real-world phenomena.

This session is dedicated to numerical techniques that address optimization challenges across various domains. Submissions should focus on the effectiveness and efficiency of numerical methods in achieving optimal solutions.

This track examines the application of probability theory and risk analysis in decision-making processes. Researchers are invited to present methodologies that quantify uncertainty and enhance decision-making frameworks.

This session highlights the intersection of data science and predictive analytics, showcasing techniques that leverage data for forecasting and decision support. Contributions should demonstrate the practical implications of data-driven insights in various sectors.