School of Computer Science


Professor Gavin Brown

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Who am I? What do I do?

Imagine you're trying to guess the price of a car. You are provided with various pieces of information, like the make and model, year of manufacture, etc. In solving any given problem like this, some pieces of information are relevant, some are irrelevant, and some are redundant in the context of others. In the car example, the number of miles on the clock clearly matters, while the colour of the wheel trim probably does not. The age of the car is probably redundant if you know the mileage. You know this because you (probably) know something about cars. What about predicting whether someone will have a relapse of a particular cancer? What things matter? Genetic factors? Lifestyle? Metabolic? In my field we use statistical methods to identify these factors, known as ``features'', automatically. In particular I work on information theory and probabilistic methods. Recently, I am particularly interested in incorporating prior (human) knowledge into the statistical processes.


Scientific Philosophy

I like the perspective on science put forward in chapter 3 of Infinite in All Directions, by Freeman Dyson.
Unifiers are people whose driving passion is to find general principles which will explain everything. They are happy if they can leave the universe looking a little simpler than they found it. Diversifiers are people whose passion is to explore details. They are in love with the heterogeneity of nature and they agree with the saying, "Le bon Dieu aime les details." They are happy if they leave the universe a little more complicated than they found it.
I've mostly been a unifier. Though I believe unifications can only come from looking at the details. So maybe I'm a bit of both.