Hi I’m Michael! I’m interested in machine learning, particularly the Bayesian flavour.
Recently I have been working on Equivariance in Deep Learning, and various COIVD-19 statistical modelling efforts.
Previously I’ve worked on Architecture Search of Bayesian Neural Networks, and Differential Privacy for Federated and Continual Bayesian Learning.
Broadly I’m interested in statistically principled machine learning. I’m working on pushing the theoretical boundaries of this, and help make it useful in the real world!
My interests aren’t completely settled however, and I’m always keen to explore new areas. Reinforcement Learning is the next on my todo list.
I recently started a PhD course at the University of Oxford through the StatML course, supervised by Yee Whye Teh and Max Welling. Before that I completed a Masters of Engineering at the University of Cambridge, supervised by Dr Rich E. Turner.
PhD in Statistical Machine Learning, 2019-2023
University College, University of Oxford
MEng in Information and Computer Engineering, 2018-2019
Christs College, University of Cambridge
BA in Engineering, 2015-2018
Christs College, University of Cambridge
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