Background
My academic journey began with a deep fascination for the complex dynamics of natural systems. I completed a Master of Physics (MPhys) in Astrophysics at the University of Southampton, spending a transformative year as a Visiting Student Researcher at the Harvard-Smithsonian Center for Astrophysics (CfA) — an experience that shaped my approach to computational modeling.
From there I pursued a PhD in Physics at Imperial College London, funded by the STFC. My doctoral research focused on computational astrophysics: using 3D Magnetohydrodynamic (MHD) simulations to investigate how stellar winds from active M-dwarf stars strip the atmospheres of close-in exoplanets. I showed that magnetized stellar winds play a dominant — often underestimated — role in driving atmospheric escape, and developed 1D multifluid models that moved beyond simple hydrogen/helium to include complex chemistry (water, oxygen).
During my PhD, I became increasinglydrawn to applying these powerful computational methodologies to pressing societal challenges. A placement with Save the Children and Brunel University London ignited my transition into humanitarian computing.
Current Research
I am now a Researcher in the Department of Computer Science at Brunel University London, where I build Agent-Based Models (ABMs) to simulate human migration and displacement driven by climate disasters. My work partner directly with the UNHCR and draws on the same "bottom-up" computational philosophy I developed in astrophysics — modeling individual decisions to reveal emergent large-scale behaviors.
A core thread running through all my work is transparency and auditability. Whether modeling plasma interactions or refugee return decisions, I prioritize rule-based, interpretable models where every outcome can be traced to understandable mechanisms. This is especially vital when models inform humanitarian policy.
I'm also engaged with the ExCALIBUR programme (Exascale Computing Algorithms & Infrastructures Benefiting UK Research), contributing to Verification, Validation, and Uncertainty Quantification (VVUQ) for large-scale simulations via the SEAVEA project.
Research Philosophy
At its core, my work is about understanding how simple rules at the individual level create complex, often surprising, behavior at the population level. In astrophysics, that means plasma particles responding to electromagnetic fields producing atmospheric outflows observable from Earth. In humanitarian science, it means individual humans responding to flood risk, economic pressure, and social cues producing migration waves that shape geopolitics.
The mathematics — complex systems, partial differential equations, stochastic processes — turns out to be remarkably similar. The difference is the stakes.
Technical Skills
- Simulation: 3D MHD (BATS-R-US), 1D multifluid hydrodynamics, Agent-Based Modeling (Flee/DFlee)
- Computing: High-Performance Computing (HPC), Python, C, Verification, Validation & Uncertainty Quantification (VVUQ) , Uncertainty Qualification
- Data: Demographic data, Geographical datasets
- Analysis: Uncertainty quantification, push/pull factor modeling, migration flows