About Me

I graduated with my PhD from the Department of Mathematics at the University of Utah in May 2023, under the supervision of Sean Lawley. My work involved modeling biophysical systems using high-dimensional partial differential equations and stochastic processes and developing simplified models to capture key behaviors.

I am also an intern at Sandia National Laboratories in the Cognitive & Emerging Computing department, where I work with Frances S. Chance on modeling the dragonfly nervous system to study how dragonflies capture their prey.


  • Applied Mathematics

    I love using mathematics to develop models of real-world phenomena and analyze their resulting traits using analysis and simulations.

  • Domain Details

    I am excited by learning new scientific domains in order to formulate and solve complex problems, especially by learning and incorporating the fine-scale details.

  • Advance Science

    Through collaboration, mathematical thinking, and domain knowledge, I will to continue to make meaningful contributions to our understanding of the world.


I have taken several approaches to different topics of emergent phenomena in biology. I am interested in how fine-grain details inform macroscale behavior of biological systems, especially when stochasticity is involved.

Spatial Constraints on Reaction Rates

Many biological, chemical, and physical processes are characterized by two objects interacting with each other, such as a protein finding a receptor on a cell membrane. In many cases,these interactions only occur at localized areas of the particles, planes, or both. We developed mathematical models of three of these types of systems and then used perturbation theory to calculate simplified models that capture the key behaviors of these localized areas of reactivity.

In addition to the mathematical analysis, we developed simulation code to confirm the results of our analysis as well as calculate the value of some parameters that have no known analyical formula. These simulations are kinetic Monte Carlo simulations of diffusing particles, which break the diffusive process into two simple stages that can be simulated exactly, allowing for greater efficiency and accuracy.

Sensory Processing

Dragonflies are excellent hunters that perform aerial interception to capture their prey. In order to do this, dragonflies must transform sensory input from the dragonfly eye's frame of reference to the body's frame of reference. We developed a model of the dragonfly nervous system to study how the dragonfly performs these calculations. This model dragonfly successfully computes the turns required for interception and indicates testable predictions for how these calculations occur in the biological dragonfly. By understanding the dragonfly nervous system, neural-inspired neuromorphic implementations of coordinate transformations can be developed in future work.

Subtle Patterns in Communication

I have used machine learning techniques to study subtle patterns in human communication for two internship projects. Available information, such as typing dynamics or word choice, can be used to indicate hidden mental states or intents that we may not be able to consciously recognize. These interedisciplinary projects stretched both my understanding of machine learning and applied mathematics as well as my understanding of human cognition.

At Sandia National Laboratories, I worked on a project on natural language processing to categorize documents of interest using spaCy.

With the CoNECt Lab at University of Illinois Chicago, I developed 3 hidden Markov models in Pyro to identify the underlying mental state of a user based on their anonymized typing dynamics. This was part of the BiAffect project, focusing on using typing dynamics to understand mood and cognition.


  • Modeling Coordinate Transformations in the Dragonfly Nervous System
    Claire E. Plunkett and Frances S. Chance
    NICE '23: Proceedings of the 2023 Annual Neuro-Inspired Computational Elements Conference | April 2023

  • Boundary homogenization for patchy surfaces trapping patchy particles
    Claire E. Plunkett and Sean D. Lawley
    The Journal of Chemical Physics | March 2023

  • Bimolecular binding rates for pairs of spherical molecules with small binding sites
    Claire Plunkett and Sean Lawley
    Multiscale Modeling & Simulation | January 2021

  • Temporal stability vs. community matrix measures of stability and the role of weak interactions
    Amy L. Downing, Craig Jackson, Claire Plunkett, Jayne Ackerman Lockhart, Shannon M. Schlater, Mathew A. Leibold
    Ecology Letters | August 2020