Tom joined the Allen Institute for Brain Science in 2018 as a member of the Modeling, Analysis, and Theory group, focusing on building large-scale biophysically detailed models of the human cortex. These simulations use data and models for single cells generated by the Human Cell Types team to expand our understanding of the unique network dynamics in the human cortex. The results will test hypotheses concerning both basic functions of brain circuits and potential treatments for neurological disorders such as epilepsy.

​Before joining the Allen Institute, Tom obtained a Ph.D. in Applied Mathematics at University of California, Davis, working with Professors Tim Lewis and Mark Goldman. For his dissertation research, he used computational and mathematical modeling to explore the effects of electrical synapses (gap junctions) on the synchronization of rhythmic neural activity, both spiking and subthreshold. This work showed how synchronization can depend critically on intrinsic cellular properties and vary across different cell types. Tom first became interested in the brain during his undergraduate studies at Reed College, where he obtained a B.A. in mathematics and physics in 2009.