| Abstract |
In this talk, we present a series of interdisciplinary studies that span epidemic modeling, biomedical data analysis, and combinatorial optimization. We begin with mathematical and data-driven approaches to epidemic analysis, including dengue fever and COVID-19, where models are developed to understand disease progression, optimize testing strategies, and support healthcare decision-making. Next, we explore applications in medical imaging and biomedical data analysis, where mathematical models and computational techniques are used to extract meaningful physiological information. At last, we discuss optimization problems by formulating them as quadratic unconstrained binary optimization (QUBO) models. Throughout the talk, we highlight a central theme: mathematical modeling provides a unifying framework that connects data, mechanisms, and computation across different domains. |
