Chris Miles

We study how cellular functions arise from stochastic, spatially structured molecular processes. Our group builds mechanistic models grounded in biophysics and pair them with machine learning to analyze large, heterogeneous datasets from single-cell and single-molecule experiments. The goal is to turn rich measurements into testable theories and reusable computational tools.

Current interests include:

• Stochastic gene expression and transcriptional bursting
• Spatial transcriptomics and subcellular RNA localization
• Simulation-based inference and learning for stochastic dynamics
• Molecular motor transport and microtubule dynamics
• Mitotic spindle self-organization and chromosome mechanics