Stuart T. Johnston

This paper introduces a Bayesian hierarchical framework to quantify both inter- and intra-experimental heterogeneity in dynamical processes using differential equations, demonstrating its robustness and flexibility.

This study develops a mathematical model to quantify heterogeneity in particle-cell interaction experiments and identifies optimal experimental time points for accurate parameter estimation.

This paper develops thermodynamically-consistent, reduced models of gene regulatory networks for scalable agent-based simulations of cell populations.