Tom Gillam

Tom has a broad interest in the application of statistical learning to real-world problems. He has a PhD in High Energy Physics from Cambridge, working with the ATLAS experiment at CERN. Prior to joining Invenia, Tom worked for a quantitative hedge fund, specializing in portfolio optimization, risk modelling, and strategy development. His research interests include Bayesian methods, optimization, and the incorporation of symmetries, causality, and other physical structure into models.

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