I just completed my PhD with the Machine Learning Research Group at the University of Oxford, where I studied as a Rhodes Scholar. I'm now focused on using causal machine learning to model complex problems. My guiding vision is a high-growth, sustainable, equitable world for all. I'd really like to automate science and the economy. You can find me on Twitter.
Previously, I researched causal machine learning at Babylon Health and helped build a new machine learning moonshot at X, Google's moonshot laboratory. My research focuses on how we can improve machine learning with causality and interpretability. I'm specifically interested in how we can use causal reasoning to improve learning efficiency and generalization; using pseudo-causal concepts to improve interpretability; and deploying machine learning to safety-critical human-use situations.
I've also researched the future of jobs, using machine learning to predict what tasks and occupations can be automated. I curate interesting papers here – you might like them.
In the past I've been an entrepreneur, salsa dancer, and rower. I started and ran RAIL, the Rhodes Artificial Intelligence Lab. I helped launch a biotech startup, a fellowship for social entrepreneurs, and worked for a long time to help kids with Arthritis.