Tom is passionate about Bayesian statistics, interdisciplinary collaboration, and using math and computers to study humanity’s most interesting questions.
Tom's academic background is in theoretical physics and computational chemistry. He applied insights from these fields to his work at Imperial College modeling infectious diseases, merging the policy-decision perspective with the fundamental questions of understanding stochastic processes with competitively-interacting dynamics.