I am a doctoral researcher aiming to develop interpretable machine learning methods to identify compound meteorological drivers of agricultural yield failure. Extreme weather events such as heat and drought are known to impact crops, but yield failure can also be caused by a compounding of more moderate weather events. The relationships between weather and climate events and crop yield are complex and nonlinear, and I hope to develop interpretable machine learning methods which can aid an increased understanding of these interactions.
I work in the compound weather and climate events group, led by Dr. Jakob Zscheischler, as part of the COMPOUNDX project which focusses on the use of machine learning to identify compounding meteorological drivers of extreme impacts. My background is in physics, and prior to my PhD I worked as a data scientist in industry for several years.
- compound climate and weather events
- meteorological drivers of agricultural yield failure
- interpretable AI for scientific discovery
- food security and sustainable agriculture