KOH-GPJax: GPU-Accelerated Bayesian Calibration

I developed KOH-GPJax, a Python package for GPU-accelerated Bayesian calibration, in collaboration with the UK Met Office and Stanford University.

Improved Climate Model Precipitation with Machine Learning

I am a co-author on a paper that uses Gaussian processes to model sub-grid variability, leading to improved precipitation patterns in climate models.

Stochastic Parameterization for Climate Models

Using Gaussian processes to model sub-grid variability and improve the accuracy of climate model simulations.