Daniel Dorman received his B.S. in biomedical engineering from LeTourneau University in Longview, Texas, and his PhD in neuroscience from George Mason University. His doctoral dissertation focused on developing biophysically detailed computational models of individual neurons of the striatum to investigate mechanisms underlying synaptic plasticity, learning, and memory. He joined the Neuromedical Control Systems Lab as a postdoc in 2021 as an IRACDA postdoctoral fellow in Johns Hopkins University's ASPIRE program. In the NCSL his research focuses on models of decision making and analysis of EEG data collected during decision making experiments to identify brain networks that support decision making and executive function.

Patrick Greene is a Postdoctoral Fellow in the Institute for Computational Medicine at Johns Hopkins. He received his B.S. in Mathematics from University of Chicago and his Ph.D. in Applied Mathematics from University of Arizona. His doctoral research was in neural signal processing, where he worked on incorporating biophysical properties of the brain into a Bayesian statistical framework in order to improve discriminability between signals from different neurons. He is currently working on projects involving the relationship between neuropathic pain and sleep, as well as on the neural correlates of decision making.