Data-driven approaches to understanding collective behavior
Tuesday, June 15 at 02:15am (PDT)Tuesday, June 15 at 10:15am (BST)Tuesday, June 15 06:15pm (KST)
Maria Bruna (University of Cambridge, United Kingdom), Ulrich Dobramysl (University of Cambridge, United Kingdom), Simon Garnier (New Jersey Institute of Technology, USA)
Mathematical models of collective motion have a wide range of applications including cell motility, animal swarms and pedestrian traffic. A common goal is to use the models to gain insight into how some given individual-based interactions give rise to the observed collective. These models typically include complex interactions between individuals and individual motility rules that may in fact be very hard to parameterize given experimental observations. In addition, experimental data can be very noisy due to the large number of individuals common in real systems and the difficulty extracting individual trajectories. This mini-symposium aims to bring together mathematical modelers and experimental researchers to explore the state of the art of parameterizing individual-based models and model selection.