I’m a PhD Student at the University of Oxford in the Autonomous Intelligent Machines and Systems CDT (AIMS) programme, supervised by Tom Rainforth, Eric Nalisnick, and Yee Whye Teh.

I spent the first portion of my PhD developing Bayesian models to evaluate the effects of nonpharamceutical interventions on COVID-19 transmission. This work resulted in publications in Science, PNAS, and Nature Communications. In addition, our work was cited in federal legislation, presented to the Africa CDC modelling group, and shared with the UK’s Scientific Advisory Group for Emergencies.

Following this, I worked on accelerating model training using ideas from probabilistic modelling and rethinking Bayesian neural networks.

Fun Stuff: I love meditation and dance. I’ve made a number of DJ sets that combine these interests, and can be used to cultivate beautiful qualities of the heart, like compassion and joy. You can find those sets mixcloud here.

Latest News:

• Check out my blog post, Researching from the Heart. I write about different ways of relating to research that lead to more joy, peace, and harmony.
• Do Bayesian Neural Networks Need To Be Fully Stochastic? has been accepted as an Oral Presentation at AISTATS23! See you in Valencia!