Research Staff

My research includes methodologies for approximate inference, particularly variational inference and Monte Carlo methods, as well as stochastic modelling for time series data. On the applied side, I primarily work on multi-object tracking, distributed sensor fusion, and intent inference.

I obtained my PhD in Information Engineering from the University of Cambridge, and previously held research associate positions at the Alan Turing Institute and the University of Cambridge.

I have served as a reviewer for international journals and conferences, including IEEE Transactions on Aerospace and Electronic Systems and IEEE Transactions on Signal Processing. I also organised a special session at the IEEE Statistical Signal Processing Workshop 2025.

I am a Royal Academy of Engineering Research Fellow, currently investigating the viability of deploying nanobubbles for enhanced water-treatment processes. My research covers high-fidelity numerical modelling of interfacial heat and mass transfer, non-equilibrium fluid mechanics, and phase change, with a special interest in cavitation.

PhD University of Edinburgh 2020

• Thesis title: Cavitation dynamics of surface nanobubbles

MEng University of Edinburgh 2016

• Thesis title: Modelling Propulsion of Nano-Swimmers

My research uses Molecular Dynamics (MD) simulations and theoretical modelling, covering interfacial heat and mass transfer, non-equilibrium fluid mechanics, and phase change, to model non-trivial nanoscale fluid phenomena, including:

• bulk nanobubble diffusive stability and growth dynamics
• cavitation bubble nucleation, rapid growth and oscillations, and violent collapse
• electrophoretic motion of nanobubbles/nanoparticles under electric fields

I welcome enquiries from prospective PhD students, postdoctoral researchers, visitors, and industrial/non-academic collaborators.