Justin Tan

Mr Justin Tan is a Cognia Junior Research Fellow at the London Institute. He studied mathematical physics at the University of Melbourne, followed by a PhD at Cambridge. His thesis focused on methods to extract physical predictions from string theories by developing a quantitative understanding of the geometry of compactification spaces—an important step towards being able to perform top-down computations for string theory. He is broadly interested in using AI as a tool to better understand longstanding problems in geometry and topology. Outside research, he enjoys optimising the geometry of his bike, playing football and the piano, with particular affection for Chopin and Schumann.

Mr Tan works on string theory, computational geometry, and reinforcement learning for interesting problems in pure mathematics.