ABOUT ME
I am a New Orleans native and a defiantly proud product of the Louisiana public school system. My passions include mathematics, teaching, foreign languages, and classical music. During my undergraduate years at Tulane University I pursued Mathematics and Spanish as majors, though I also amassed considerable coursework in Physics, French, Portuguese, music theory, and piano performance. I'm in constant pursuit of foreign language conversation or a patient duet partner.
EDUCATION
RESEARCH INTERESTS
Reaction-Diffusion Systems
The diffusion of ligand and cytokines on intercellular spatial scales is critical to biological processes such as immune signaling, would healing, and embryonic cell differentiation. Diffusion in the body is limited to this scale, meaning the efficacy of diffusion as a delivery mechanism may act as a metric against which tissues measure themselves. Hypoxia in growing tumors due to insufficient diffusion of oxygen can lead to tumor angiogenesis, the first step in the cancer pathogenesis. In this way, diffusion, though a passive process, can play a crucial role in the organization of tissues, especially when considered in concert with reaction processes. Alan Turing famously outlined the idea of diffusion-driven instability in his 1952 paper "A chemical basis of morphogenesis."
2018 - 2020
North Carolina State University
Ph.D., Applied Mathematics
2015 - 2018
North Carolina State University
M.S. Applied Mathematics
2011 - 2015
Tulane University
B.S. Mathematics
B.A. Spanish
Cellular Automata
Large systems of PDEs quickly become impractical as the the number of biological phenomena to be modeled and the dimensionality of the simulated space increase. Cellular Automata encode for state transitions governed by stochastic processes which PDE models can only approximate in the mean-field sense. In addition to being more biologically relevant, the stochastic nature of CA models importantly allow for phenomena that are classically forbidden in the continuous case such as asymmetric spatial spread. Whereas PDEs consider continuous, real-valued densities which are deterministically evolved forward in time, the CA framework allows one to consider individuals explicitly. In some simple cases, CA models can be shown to upscale directly to PDE models, but in more complex cases,