Research
Five threads run through the group's work. Each is a short read.
Real-time digital twins
Physical models corrected on the fly by streaming sensor data, so that a simulation and the system it mirrors stay synchronised.
Read more →Bias-aware data assimilation
Ensemble Kalman filtering for nonlinear and chaotic systems — including estimating the model error the model does not know it has.
Read more →Reduced-order models & scientific ML
Autoencoders, reservoir computers and transformers, built to be forecast-stable and interpretable rather than merely accurate.
Read more →Control of partially observed systems
Once a state can be estimated from partial observations, it can be acted upon — assimilation and reinforcement learning, combined.
Read more →Turbulent and reacting flows
Thermoacoustics, wakes, wind farms, near-wall turbulence and urban dispersion — where the methods meet real data.
Read more →