麻豆AV

Scholarship

Selected Recent Publications

• Statistical Analysis of Stationary and Transition Probability Densities for Atmospheric Forcing in a Climate Change Model, 2026
  Journal Article, Academic Journal
• Stochastic modeling and first-passage-time analysis of oncological time metrics with dynamic tumor barriers, 2025
  Journal Article, Academic Journal
• Transition Probability Density Function for Number of Infections in a Population Satisfying a Stochastic SIS-Epidemic Model, 2024
  Book, Chapter in Scholarly Book-New
• Analysis of the impact of treatments on HIV/AIDS and Tuberculosis co-infected population under random perturbations, 2024
  Journal Article, Academic Journal
• Tumor growth and population modeling in a toxicant-stressed random environment, 2024
  Journal Article, Academic Journal

Research Interests

My research lies at the intersection of stochastic modeling of dynamical systems and statistical analysis, with a focus on applications in biological, medical, and public health contexts. A core theme of my work is developing and applying mathematical models to understand the dynamics of infectious diseases, tumor growth, and population health, especially under uncertainty. I incorporate time-dependent stochastic processes, differential equations, and statistical estimation frameworks to analyze complex, high-dimensional data from real-world systems.

A key contribution is the development of the Local Lagged Adapted Generalized Method of Moments (LLGMM), a patented (U.S. Patent No. 10,719,578) nonparametric estimation framework designed to infer time-varying parameters and hidden states in stochastic differential equations.