Gavin Brown is Professor of Machine Learning at the University of Manchester. I enjoy methodological / theory-based research, looking for connections and equivalencies between known methods in the jungle of ML, primarily with tools from statistics and information theory, and lately I’ve been exploring information geometry. Everything in ML is, ultimately, a special case of something else.

I find this research philosophy leads to novel methods with strong foundations: e.g. we have contributed methods for assessing the stability (reproducibility) of variable selection algorithms; methods for hypothesis testing in challenging non-standard scenarios; and, a new theory of diversity in ensemble learning. My current collaborations are with a large pharmaceutical company, looking at the reproducibility of biomarker identification procedures. This collaboration will form the basis of a PhD offered this year by the CDT.