Tony Wei
Tony Wei earned his BS in Biomedical Engineering & BS in Applied Mathematics and Statistics from the Johns Hopkins University. He is currently a PhD candidate in Biomedical Engineering in Dr. Sridevi Sarma’s Neuromedical Control Systems Lab at the Johns Hopkins University. His research interests include neural signal processing, machine learning applications in neuroscience, and chronic pain. For his PhD he is collaborating with Dr. Latremoliere and Dr. Alexandre from the Neurosurgery Pain Research Institute at Johns Hopkins to identify an EEG neuropathic pain biomarker from mice fronto-parietal brain activity during sleep.
Patrick Greene
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.
Daniel Dorman
Daniel Dorman earned his BS 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.