Christopher Strickland, PhD

Dr. Christopher Strickland

I defended my PhD in October of 2013 at Colorado State University and completed a three-year postdoc in applied mathematics at the University of North Carolina, Chapel Hill and SAMSI (the Statistical and Applied Mathematical Sciences Institute) in 2017. I currently conduct research modeling, analyzing, and optimizing complex systems in ecology and substance use disorder epidemiology. I am particularly interested in mechanistic and computational approaches to problem solving, and I am often confronting mathematical models with data. My research is always interdisciplinary in nature, and typically includes a blend of mathematics, computer science, and probabilistic modeling. I enjoy working directly with scientists and engineers, and I have been fortunate to collaborate directly with ecologists and biologists both domestically and internationally in order to shape my research problems.

EDUCATION

RESEARCH INTERESTS

Mathematical Ecology

PROGRAMMING SKILLS

Python (incl. Numpy, Scipy, Matplotlib, Pandas...)

MATLAB

Git, GitHub

The Strickland lab! (May 2022)

Dr. Tricia Phillips (click for website): (Birmingham-Southern College, 2020) Tricia received her PhD from the mathematical biology program at the University of Tennessee, Knoxville in 2020. For her dissertation, she built and analyzed models of opioid and heroin addiction and a discrete-time model of population structure in non-lethal harvest scenarios. Both projects were highly data-driven and involved a significant computational aspects.

Leigh Pearcy (click for website): Leigh is an NSF Graduate Research Fellow at the University of Tennessee, Knoxville who is pursuing both a PhD in Mathematics and an MS in Statistics. She is currently exploring the effect of stratification in susceptibility with regard to opioid and heroin addiction and is interested in the analysis and implications of relaxing the well-mixing assumption with regard to contact-based routes of addiction. She has also worked on optimal control and structural stability related results for substance use disorder epidemiology models.

David Elzinga (click for website): David is a mathematical biology graduate student who is conducting research on bee colony dynamics in the presence of pesticides and other stressors and biotic modeling of species spatial distributions in the context of niche modeling. He is pursuing both a PhD in Mathematics and an MS in Statistics. He has also published papers on the sylvatic plague in prairie dog towns (Natural Resource Modeling, 2020) and vaccination strategies to control white-nose syndrome in bat colonies (Ecological Modelling, 2019), and completed an internship at Liberty Mutual working in the area of machine learning (2021).

Kimberlyn Eversman: Kimberlyn is conducting research on the interface of dynamical systems and fluid dynamics using computational approaches using Planktos, IB2d, and 3D immersed-boundary fluid-interaction data. She is currently studying models of collective behavior for small organism movement toward targets immersed in various types of steady and non-steady fluid flow. She is also interested in modeling and numerically simulating PDE models of cultural change in bird song.

Ryan Champbell: Ryan is studying optimal search strategies of tiny wasps in the context of background fluid flow and where the target is another small, flying insect. He is also interested in the multi-scale problem of how these individual search strategies give rise to landscape-level distribution patterns. Ryan brings many mathematical tools together to analyze these problems, including probability theory, stochastic differential equations, mathematical and probabilistic modeling, and partial differential equations.

Owen Queen: Owen is a mathematics and computer science major studying agent-based models of opioid and heroin addiction on social networks. He uses a combination of mathematical modeling, Python- and NetLogo-based computation, and statistical analysis carried out in R to conduct his research. Owen Queen is a 2021 Goldwater Scholar and is interested in going to graduate school in bioinformatics.