Image source: https://en.wikipedia.org/wiki/Chlamydomonas#/media/File:Chlamydomonas_(10000x).jpg

During my PhD at Warwick, I studied how the swimming microalga Chlamydomonas reinhardtii interacts with passive microparticles, such as microplastics, in confined spaces. Combining microfluidic experiments, particle tracking, simulations and an analytical jump-diffusion model, we showed how active swimmers drive passive particles to accumulate and de-mix under confinement (Nature Communications, 2022). I'm now extending this work to understand how individual scattering events between swimmers and particles control where the particles end up.

Techniques: Statistical Physics, active particles, numerical simulations, data analysis, image analysis, active Brownian motion.

Image source: https://en.wikipedia.org/wiki/Euprymna_scolopes#/media/File:Hawaiian_Bobtail_squid.tiff

Within hours of hatching, the Hawaiian bobtail squid must recruit its bioluminescent symbiont, Vibrio fischeri, from the seawater it breathes. I build computational fluid dynamics models of the flows inside the squid's mantle cavity using the method of regularized Stokeslets, and use global sensitivity analysis to ask how thermal stress, through changes in breathing, affects the bacteria's chances of reaching the light organ (J. R. Soc. Interface, 2026). This work is part of INSITE, the NSF institute for symbiotic interactions.

Techniques: Computational fluid dynamics, numerical simulations, sensitivity analysis, active Brownian motion.

Image source:
https://sciencephotogallery.com/featured/2-vibrio-fischeri-dennis-kunkel-microscopyscience-photo-library.html

Alongside the squid, I'm interested in the bacteria themselves. With Daravuth Cheam and Prof. Michele Nishiguchi, I model how Vibrio fischeri forms biofilms and how populations adapt under repeated predator stress. We use identifiability and sensitivity analysis, together with genetic algorithms, to work out which data are needed to measure the parameters that drive these dynamics (Bulletin of Mathematical Biology, 2026).

Techniques: Population modelling, trait-structured models, natural selection, numerical simulations, model identifiability, sensitivity analysis, genetic algorithms.

Image source:
https://actiniaria.com/exaiptasia_diaphana.php

The sea anemone Exaiptasia diaphana is a model for coral symbiosis. With Kaden Muffett and Prof. Maggie Sogin, I've worked on how its microbiome responds to chronic and acute heat stress (Nature Communications, 2026). I'm also building size-structured models of anemone populations, with a focus on which parameters can actually be identified from experimental data.

Techniques: Delay differential equations, population modelling, generalized additive models, size-structured models, model identifiability, sensitivity analysis.

Cassiopea, the upside-down jellyfish, is an emerging model system for symbiosis. With Kaden Muffett, I'm developing a deep-learning imaging pipeline that measures the timing of strobilation, the life stage in which polyps produce juvenile jellyfish, from daily photographs.

Techniques: Deep learning, object detection, image analysis, automated image acquisition.