Mathematical Biology

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 …

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, …

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 …