University of Florida Homepage

Math Dept Colloquium: Luis Sordo Vieira (UF Laboratory for Systems Medicine)

339 Little Hall (The Atrium)

My trajectory towards mathematical modeling of pulmonary infections The immune response to respiratory infections is highly complex and multiscale, making it amenable for mathematical modeling. Fungal respiratory infections are becoming increasingly prevalent and pose the threat of antimicrobial resistance. The immune response to respiratory pathogens is highly complex and multiscale, making it difficult to predict

Arkaprava Roy (UF Biostatistics)

423 Little Hall

Novel Statistical Analysis Methods in Neuroimaging Using Diffusion MRI In this talk, I will discuss the fundamentals of diffusion MRI and explain how various features are extracted and their importance in neuroimaging analysis. I will then discuss some of the scientific applications and end with future possibilities.

Hemaho Taboe (UF Mathematics)

423 Little Hall

Unveiling the Hidden Threat: The Impact of Sub-Optimum Treatment on Acquired Immunity, Asymptomatic Cases, Malaria Dynamics Malaria remains a persistent global health issue, despite ongoing control efforts such as anti-malarial drugs and insecticide-treated bed-nets, indoor residual spraying, etc.. The greatest impact of malaria, a mosquito-borne illness, is felt in Africa. This study develops a compartmental

T.J. Sego (UF Laboratory for Systems Medicine)

423 Little Hall

Reproducible Stochastic Simulation Stochastic simulations are commonly used to quantitatively or semi-quantitatively describe the dynamics of biological systems. At various scales and in multiple applications, stochastic simulation better reflects observed biological processes and robustness. Various methods are widely used to incorporate stochasticity into biological simulation, such as the Gillespie stochastic simulation algorithm for systems biology

Harsh Jain (University of Minnesota Duluth, Mathematics & Statistics)

Zoom To obtain the Zoom link, please contact Tracy Stepien at tstepien@ufl.edu

Uncertainty Quantification in Complex Models of Complicated Biology Validated mathematical models of complex biological phenomena are increasingly recognized as invaluable for elucidating mechanisms that underlie real-world (experimental or clinical) observations. Agent-based models (ABMs) have emerged as a natural formulation of choice in such models, providing a logical structure for capturing the multiple time and spatial

Math Dept Colloquium: Claus Kadelka (Iowa State University, Mathematics)

339 Little Hall (The Atrium)

Including human behavior in infectious disease models The COVID-19 pandemic has revealed the good and the bad of infectious disease models. While a well-developed model provides invaluable insights needed to understand and combat the pandemic, many models suffer from imperfect or simplistic assumptions that result in inaccurate or even completely wrong predictions. In this talk,

Martina Conte (University of Parma, Mathematical, Physical, and Computer Sciences)

Zoom To obtain the Zoom link, please contact Tracy Stepien at tstepien@ufl.edu

A multi-scale approach for modeling cell dynamics The characterization of biological phenomena related to cell evolution and their interactions with the microenvironment often involves processes occurring across a range of spatial and temporal scales. As a result, mathematical models designed to describe cell dynamics must capture this inherent multi-scale complexity. In this seminar, we introduce

Andreas Buttenshön (University of Massachusetts Amherst, Mathematics and Statistics)

Zoom To obtain the Zoom link, please contact Tracy Stepien at tstepien@ufl.edu

How cells stay together; a mechanism for maintenance of a robust cluster explored by local and nonlocal continuum models Formation of organs and specialized tissues in embryonic development requires migration of cells to specific targets. In some instances, such cells migrate as a robust cluster. We here explore a recent local approximation of nonlocal continuum