In this post, I’ll discuss some recent explanations for anomalous, yet Gaussian diffusion, including diffusing diffusivities and stochastic subordination.

I’m currently a 5th year graduate student in the mathematical biology research program.

My interests center around using mathematics to understand how biological systems function *because* of **randomness**, rather than in spite of it. One such canonical system (and my primary biological focus) is the utilization of **molecular motors.**
Work I have done in this realm includes:

- analysis of
**metastable switching**in populations of motors; - development of theory to study state-dependent
**jump-diffusion processes**; **collaboration with experimentalists**to understand motor-driven transport data.

CE Miles, SD Lawley, JP Keener.
“Analysis of non-processive molecular motor transport using renewal reward theory.” *
submitted*, 2017.

O Osunbayo, CE Miles, BJ Reddy, JP Keener, MD Vershinin.
“Complex nearly immotile behavior of microtubule-associated cargos.” *
submitted*, 2017.

CE Miles, JP Keener.
“Jump locations of jump-diffusion processes with state-dependent rates.” *
J. Phys. A: Theor. Math.*, 2017.

In this post, I’ll discuss some recent explanations for anomalous, yet Gaussian diffusion, including diffusing diffusivities and stochastic subordination.

In the previous post about limit theorems of stochastic processes, we considered when everything goes *right*, leading to Gaussian-like behavior. Here we’ll discuss when things go *wrong*, particularly when memory effects and infinite moments are introduced.

- miles@math.utah.edu
- LCB (LeRoy Cowles Building) 326, Salt Lake City, UT