This track focuses on the development and application of mathematical models to understand complex biological phenomena. Emphasis will be placed on modeling techniques that elucidate interactions within biological systems.

This session will explore the principles of chaos theory and its relevance in both biological and physical sciences. Participants will discuss how chaotic behavior can be modeled and predicted in various systems.

This track aims to highlight innovative computational techniques used in applied mathematics to solve real-world problems. Topics will include numerical simulations, algorithm development, and software applications.

This session will delve into the statistical methods employed in the modeling of infectious diseases and public health phenomena. Participants will share insights on data analysis and interpretation in epidemiological studies.

This track will cover optimization strategies applied to complex systems in both biological and physical contexts. Discussions will focus on algorithmic approaches and their implications for system efficiency and performance.

This session will explore the integration of machine learning techniques in biological research, emphasizing data-driven discoveries. Participants will present case studies where machine learning has significantly advanced understanding in biology.

This track will examine the role of differential equations in modeling physical phenomena across various disciplines. Emphasis will be placed on analytical and numerical solutions and their applications.

This session will focus on the intersection of data science and biostatistics, highlighting methodologies that enhance data analysis in health-related research. Participants will discuss innovative approaches to big data in biostatistics.

This track will address the application of quantitative methods to model environmental systems and processes. Discussions will include the challenges and advancements in modeling ecological dynamics.

This session will explore the application of probability theory in understanding biological variability and uncertainty. Participants will discuss models that incorporate stochastic processes in biological contexts.

This track will focus on the study of complex systems and their network dynamics in both biological and physical realms. Emphasis will be placed on the mathematical frameworks that describe interactions within these systems.